Accenture plc (ACN)

Investor Day 2026

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Oct 14, 2026

Summary

The strategy targets at least mid-single-digit constant-currency growth in FY27–FY28, stepping up to mid- to high-single digits from FY29. Growth rests on AI-led reinvention, core expansion, and a network targeted to double by FY29.

Hello, everyone. Hello and welcome. We have many of you in the room and online, so thank you for joining us. Thank you to the people who actually make today possible. That is our reinventors and our clients around the world, the incredible technology companies that make up our ecosystem, and of course, our production team who is with us today. We are also joined by some of our board and many of our senior leaders. For those of you here today in person, you are going to be able to meet some of those senior leaders. We are really excited because you are investing time, and we have the opportunity to tell our full story. Our goal for today is that you leave with a deeper understanding of how we have become a business reinvention and technology company, and why we have significant growth ahead. Today, we are going to cover three things. First, why is AI making Accenture more essential than ever? Second, our new foundation for growth that we have been building for the last four years. Finally, third, our growth trajectory. How we are going to use that foundation to drive significant, durable growth and shareholder value creation. Let me start with some context. Twice in the last 20 years, there has been an economic reset in our industry. First, there was offshoring. Made possible by the internet and automation, offshoring drove down the cost of building software and routine IT services. In fact, at one point, there was a fear that automation would wipe out huge portions of the IT services industry. Then came cloud and digital. Cloud and digital drove down the cost of technology itself. You saw for the first time, software starting to replace some services. Over both eras, an important thing happened. Offshoring, cloud, and digital did drive down the cost of some of our services and eliminated some of our services. At the same time, the underlying technology allowed enterprises to do so much more that the new demand that was created far exceeded, over time, the demand that it replaced. In both cases, Accenture had significant growth and took significant market share. How did we do that? First of all, we embraced these developments quickly. We invested in innovation, and we were willing to reinvent ourselves from how we worked, to where we worked, to how we organized, to what we sold, and we invested each time in new sources of revenue that were being created by the technology wave. We are now four years into the next economic reset of our industry, the age of AI. We think the opportunity is bigger than ever before. While AI does have the potential with AI efficiencies to impact our business more than ever before, we again believe that ultimately, the new demand that will be created will far exceed the demand that is being replaced. Across both of these eras, clients, the ecosystem, and trust have been at the center of our strategy, and they remain so. We have confidence in our future because we have had a great track record in prior technology waves. We are running a playbook that is informed by the past, but accelerated. Now we can see it in the opportunities that we have created already and the new foundation. I am with clients almost daily. It is the best part of my job because it is so inspiring to be with CEOs with bold ambitions, and those ambitions are being driven by the twin catalysts of AI and the macro environment. Now, when I look at where we are across our client base, there is wide varieties of AI readiness. We have some clients who are moving from using AI to running on AI with enterprise-wide programs. Most are still quite early, starting to scale some things across the enterprise, and many more are just getting started. Wherever they are starting, there is one thing, though, that is very clear. Incremental change is not enough. We see it this way. AI is the breakthrough innovation. Only reinvention can unlock the value. This is what matters to Accenture. Our clients turn to us in times of change. The bigger the change, the more they need us. Reinvention is fundamental change. Our clients over the years have turned to us over and over again because we have delivered reinvention. That is why 85% of our top 200 commercial clients and all of the G7 governments have been clients for 20 years or more. They turn to us because we have a unique set of strengths that no other company can fully replicate. You are going to hear a lot about our strengths over the course of the day. I want to highlight a few that we have built over decades. Who we serve, who we build with, what we know, and what we have done. When you think about who we serve, we operate in every major market. 75% of the Fortune 100 and Fortune 500 are in our client base. We serve every G7 government. Half the world's economy run through our client relationships. We have an incredible ability to build trusted relationships, sometimes built over decades because we have a cadre of client account leads who wake up every day thinking about how to help their client be successful and what we can do to be a part of that. This means that we have unmatched insight and experience. Then there is who we build with. We have by far the largest and most strategic ecosystem of technology companies in our industry. We have over 200 in our network, but 18 of them make up about 65% of our revenue. They are the largest technology companies. They are the emerging technology companies. They are all at the center of the AI wave. Because of these relationships and our ability to invest, we use the latest technologies early and we build the skills our clients need. We understand technology, we understand the enterprise. We help our clients decide what is fit for purpose, and then we help them create value. We work with each of our technology companies in the ecosystem to create joint solutions that we take to our clients to help them accelerate value and lower risk. We have the largest distribution channel in the industry with over 9,000 clients, which means our technology partners know that we can help them scale. They also know that we will have the people, our Reinventors, that they need to scale because we have the best ability to attract, retain, and grow talent in the industry. That is why we are number four on the Great Place to Work global ranking. This is cross-industry, and that ranking is by far the highest in our industry. When you take all of these factors together, that is why decade after decade, we have been the number one partner to the ecosystem that matters to our clients. That brings me to what we know. We have over 800,000 people, and last quarter they were 93% utilized. Our clients value our Reinventors. Our people have deep experience across 13 industries in all major functions. That spans from corporate functions like HR and finance to core operations, manufacturing, R&D, the network, to everything customer, sales, marketing, service, product development. Our capabilities span from strategy, operating model, change management, process, data, AI, technology. These are all of the things that we talk about are so critical to reinvention, and we are able to deliver them in the way the client needs it through consulting, through managed services, with proprietary assets and platforms, and increasingly through software that we are either buying or building. That brings me to what we have done. Our purpose is to deliver on the promise of technology and human ingenuity. We use the word deliver very deliberately. This is our point of pride. People at Accenture get up every day proud because we deliver results. We have built our reputation, our brand on being at the center of every technology wave and delivering complex, hard programs. When you think about it, every year the number of clients who are doing $100 million quarters of bookings a quarter with us has increased. You do not have that level of relationship unless you trust your partner to deliver. When you think of each of these strengths, who we serve, who we build with, what we know, and what we have done, they are the reason why Accenture is a force multiplier for our clients. We help them do more than they can do alone. All of this adds up to our ultimate strength: trust. Our clients trust us. They trust our expertise, they trust our ability to deliver, and they trust our commitment to their success. Underpinning that trust is our commitment to live every day our core values and our leadership essentials. Whenever I am talking to a new, young managing director, I tell them that everything they need to know about how to be successful personally and how to help Accenture be successful is there in our core values and our leadership essentials. They matter. Before I take you to where we are going, I want to spend a few minutes on our starting position. Over the last four years, we have invested organically and inorganically to build a new foundation for growth. It is not just a new foundation. It is the strongest foundation we have ever built. Over the last four years, we have increased our addressable market from $1.5 trillion to $3 trillion. In the age of AI, we have built the largest AI and data workforce in our industry. While we have done that, we have added $12.6 billion in revenue. We've taken significant market share, growing more than 2x our investable basket, and we've returned $35 billion in cash to shareholders. We've made three big strategic moves over the last four years. The first I will call accelerating large-scale reinventions. Once generative AI emerged in November 2022, we knew that it was going to take a while for the AI to mature, to be able to have an impact. We made the deliberate decision to go after more large transformations. These transformations put us at the center of our clients' agenda, and we knew that not only would they deepen our relationships, but they would position us to do the next waves as AI matures, which is exactly what we're seeing now. We've been incredibly successful. We use our $100 million bookings a quarter as a proxy for reinventions. In FY22, that was 100. Today, it's 141 in the year that we just completed, which means over 500, 501 to be precise, that we have done over the last four years. Not only is that driving our growth, but it positions us for the next rounds of growth. The way that works is well illustrated by a meeting I had this week. Just a couple of days ago, I met with the CEO of a new client, a $20 billion annual revenue client, and they had come to us after looking at all of our competitors and we're signing our first reinvention with them. It'll be over $100 million. Our teams have already shaped wave 2 and wave 3, and by the end of breakfast, we had shaped wave 4. This is how these reinventions compound, wave after wave because we're strategically positioned at the top of the house in the agenda that matters. You can see that with our diamond client relationships, which are our largest relationships. In FY22, we had 267. We now have 317. Over the course of the four years, as we focused on reinventions, we also learned a lot. Just last year, in the spirit of reinventing ourselves, we made the biggest organizational change in our history and created Reinvention Services, which brought together all of our capabilities so that we could much more easily embed AI and data and move more quickly. Just a few months ago, we created seven units. We call them Reinvention Partners. Each of them is organized around how our clients operate, invest, and buy. You're going to hear more about these later today with Manish. That brings us to our second big strategic move, taking an early leadership position in AI. In November 2022, when generative AI emerged, we moved quickly. Within months, we had announced a $3 billion three-year investment specific to AI. The best way to evaluate our achievements is to look at the numbers. Let's start with, in November 2022, we had a handful of generative AI projects going when it hit the public. Today, we've done over 18,000 advanced AI projects. I just want to pause for a moment because when people ask me what reinvention means, I point to this statistic. This is over 18,000 around the globe in multiple industries from a starting standstill point of five. What it takes to do this is not operating the same way we operated before. We changed the way we worked, we invested, we focused, and this is an incredible number that is climbing every day. We also went from 40,000 AI and data professionals to nearly 110,000. We created nine new business groups with the emerging companies that mattered in AI and data, following our playbook that we build relationships with the technology companies that matter to our clients. We also expanded our AI and data partnerships with our largest ecosystem players, and today all of them are at the center of the AI wave. Just a couple of months ago, maybe it is only a month now, we also announced the creation of our new AI safety business using Faculty, our AI-specialized business that we bought earlier this year, and you are going to hear from Marc Warner, the CEO, a little bit later. When you think about why it is important that we took early leadership, mostly it is because this is where the demand is going to grow and it is where our clients want to spend their money. That early leadership also gave us another advantage. It helped us understand what the new growth would be. Our third strategic move has been to use acquisitions to accelerate into higher growth markets. Our strong balance sheet and our strong free cash flow gives us investment capacity that we can flex up and flex down. Over the years, we have used that to accelerate growth. When you look at our business today, we have multibillion-dollar businesses that were built initially through a lot of inorganic: cloud, cybersecurity, Song, supply chain, and engineering. This is something we know how to do, and we think of our acquisition experience as a growth accelerator. We have spent over the last four years, including the acquisitions that slipped into September, $19 billion. We have done so for the three reasons we make acquisitions. The first is to scale markets where we are already in, but have higher growth. Cybersecurity is one of them, traditional cybersecurity, and so you saw us, for example, buy CyberCX in Australia. The second reason is to deepen industry and functional skills. We have done a lot of supply chain acquisitions. Those tend to be smaller and more niche. The third reason is to expand into new markets. This is where, when you think about our move from $1.5 trillion to $3 trillion, this has contributed the most. Every technology reset creates new growth, and because we were in the center of what was happening with AI, we could see that there was going to be more opportunities than ever before: new markets, new buyers, new commercial models. This was the time to ratchet up our ability to use our competitive advantage, our knowledge of how to do acquisitions, our strong balance sheet, our strong cash flow, and invest. We have now created what we call a network of businesses. You are going to hear more about the specific businesses a little bit later. Those businesses followed a playbook. They were in large and growing markets. They would use the power of Accenture to achieve more than they could stand alone. They are AI-powered and AI-resilient, and they have revenue growth above the average of Accenture and increasingly non-FTE models. So that playbook we've executed and that brings us to our next chapter. Our next chapter is about scaled reinvention. The last four years, they've been about building, reinventing, expanding. The next chapter will be about scaling reinvention for our clients and for us. Our three-year financial ambition is to achieve at least mid-single-digit revenue growth in constant currency in FY27 and FY28, and then a step up in the range of growth from mid-single digit to high single digit starting in FY29 and taking market share throughout the entire period. Our ambition includes continuing to expand operating margin while investing at scale in our business and returning significant cash to shareholders. Angie is going to take you through more of the details at the end of the day. Now, our business goals are to continue to be the reinvention partner of choice and the leader in the safe, widespread adoption of AI, and to be the most client-focused, AI-enabled, great place to work for our reinventors. In the next chapter, our growth strategy has two components: grow the core and scale the network. These are mutually reinforcing, and our reinvention partners will drive both. We will continue to invest organically and inorganically in both the core and the network. Let's start with the core. The core was 94% of our business in FY26, growing approximately mid-single digits. We see a few growth drivers in the core. Most of our growth will continue to come from large-scale reinventions. Those will have different flavors depending on the client. For many, it's still about building the digital core, modernizing ERP, modernizing the mainframe, moving to cloud, eliminating tech debt, and creating the technology foundation needed for AI. For others, it'll be about transforming a function, creating investment capacity, doing cross-enterprise transformation, and in all cases, our clients value that we're embedding more and more AI, helping them execute on an AI strategy by leveraging our expertise and our platforms. We're starting to see the green shoots of companies who are already more mature in their digital foundation to do enterprise-wide programs. Another big driver will be creating the enterprise AI stack, which is necessary to actually run your company on AI. Everest recently put out a report that said only about 5% of clients have the foundation, the enterprise AI technology, to actually be able to scale AI in a repeatable way. That's exactly what we see. This is a massive opportunity that is net new and will help drive our growth. The third big driver, as we see the core, is going to be helping our clients use AI to do what they couldn't do before. Some of that's going to be about running the enterprise, but there's a lot of net new opportunities, like agentic commerce. Manish will talk later about these growth arenas that we've identified that are expanding our addressable market and are part of our long-term growth plan as we scale. So that's the core. Let's talk about the network. We're really excited about what we're building here. Today, it's only about 6% of Accenture, and it's growing double digit. But over time, we expect it to be a material contributor. The network, what makes it different is that these are companies that leverage all of our strengths, but they use different operating and commercial models in order to grow. We have two engines, the core and the network. We also grow by who we sell to. When you think about our client base, we have a ton of white space in our large enterprises and emerging large enterprises, which is where we've traditionally been. I just talked about the brand-new client, $20 billion of annual revenue. We'll grow with them by leveraging our Reinvention Partners to grow our market share within a client, then we'll take our credentials and continue to grow with similar profiles based on our credentials. At the same time, we and our ecosystem believe that the mid-market is an important growth opportunity. The mid-market is a $240 billion market growing high single digits. We've always been in the mid-market, but not as a growth strategy. Last year, it was about 8% of Accenture. Over the last couple of years, we've bought mid-market-focused companies to test our strategy. Starting in FY27, we are going intentionally into the mid-market to take market share. This means that we are able to grow by taking more of Accenture to more clients. The mid-market will be part of our core and part of our network. Before we go to the next section today, I just want to take a moment to summarize the big picture. We have invested for four years in building the foundation that we believe will allow us to step up our growth to mid-single digit, to high single digit in FY29. That belief is grounded on what we see today in our core and the network. It is also grounded in the reality that it is going to take some time to scale AI across the enterprise, and in the meantime, we're absorbing AI efficiencies in our business. We also have a macro that's contributing to challenging spending environment. As we look forward, what we actually achieve will of course reflect what's happening in the macro, but we're not waiting for a meaningful tailwind. Although we do expect, over the next three years, some normalization to occur. In our core, our growth will be large-scale reinventions, and as AI adoption accelerates, we'll have significant opportunities in existing work and in the new work, the new areas that we've identified. Our ambition is to grow on a very, very large base, mid-single digits, while absorbing AI efficiencies. With respect to our network, we believe that we have the potential to double the size, it's currently 6%, by FY29. We're excited to now be able to dive deeper into those growth opportunities. In a few moments, Manish Sharma, our Chief Strategy and Reinvention Services Officer, is going to come on stage to do so. Before we do that, we're going to hear directly from some of our ecosystem partners. Throughout the day, you'll hear more from our ecosystem partners as well as our clients. After Manish, John, our CEO of the Americas, and Mauro, our CEO of EMEA, will come and give you a market perspective. They'll take it from the client up and the market demand in our two biggest markets. I'll then be joined by Kate Clifford, our Chief Leadership and Human Resources Officer, to talk about how we're reskilling and upskilling and hiring the best talent in the world to make sure that we can hit our growth ambitions. Over lunch, you'll have the opportunity to meet with many of our senior leaders, and you've all been assigned a table to make sure that happens. Angie will take us home this afternoon. That's the day. Thanks again for investing the time. Now you'll hear directly from five of our ecosystem partners, all of whom we both use at Accenture and we help our clients use. Then Manish will join us. Thank you. Accenture is one of our largest and most strategic global systems integrator partners. At re:Invent 2025, they won 12 AWS partner awards, including Gen AI Consulting Partner of the Year, Gen AI Industry Solutions Partner of the Year, and Global Consulting Partner of the Year. This is partly because Accenture's expertise in helping customers adopt and scale generative AI, along with launching transformative applications across industries and delivering significant contributions in revenue, certifications, and customer outcomes, all on AWS. Accenture was also one of the first global systems integrators to recognize the transformational power of our technology and build an entire business group around AWS. One that we've grown together, backed by dedicated AWS certified practitioners. We've been building together for a long time, and we keep delivering for customers. Together, AWS and Accenture have helped enterprises around the world modernize their business and adopt AI faster. In fact, customers who work with a partner like Accenture get their AI projects into production about 25% faster. One great example is NatWest, one of the largest banks in the U.K. We're helping them transform into a data and AI-powered bank. Through a five-year collaboration together with Accenture, we're now modernizing how NatWest serves their 20 million customers with more personalized, intelligent experiences. This kind of work requires AWS's cloud infrastructure, our AI services, and security, alongside Accenture's deep banking expertise and ability to execute at enterprise scale. When you combine those strengths, no challenge is too complex for our customers to take on, and that is why this partnership is so central to how customers adopt AI. I can't wait to see what Accenture and AWS do next for customers. Congratulations on everything that Accenture has achieved. Google Cloud's partnership with Accenture is built on combining our full-stack AI capabilities with Accenture's deep industry expertise. For the fourth consecutive year, Accenture has been named Google Cloud's Global Partner of the Year. Accenture ranks number one globally in active Google Cloud certifications with nearly 50,000 Google Cloud skilled professionals. Deploying agentic AI is a top priority for enterprises today. To achieve real business value, companies need to rethink how AI will impact processes across their organization. This is where Accenture comes in. We launched the Accenture Gemini Enterprise Business Group to meet clients wherever they are in their AI and data journeys. 1,000 forward-deployed Accenture engineers work directly inside customer environments alongside our Google DeepMind and Cloud engineering teams. They'll build agentic solutions tailored to how specific industries operate, including marketing, cybersecurity, AI and data, contact centers, and sovereign programs. Together, we are helping enterprises move past pilot phases and delivering transformation at scale. Thank you for your continued partnership. For decades, Microsoft and Accenture have enabled companies to harness the power of technology to achieve their highest aspirations. Together, we have helped organizations across industries and around the world transform their business and accelerate their digital journeys. Today, that partnership is more important than ever. With more than 95,000 Microsoft certified professionals and 21 Partner of the Year awards, Accenture brings tremendous depth and expertise across the Microsoft portfolio. What really sets Accenture apart is that they are not simply advising clients on becoming frontier, they are living it themselves and at extraordinary scale. Accenture has deployed Microsoft 365 Copilot to their 743,000 employees and is driving significant business process improvements with more than 50,000 developers using GitHub Copilot. That firsthand expertise matters. It gives Accenture a unique understanding of both the AI opportunity and the complexity that it creates when you put it into the workforce across a massive enterprise. They are bringing that expertise to organizations like NHS England, Nestlé, Repsol, Essity, and so many more, helping them move from AI ambitions to meaningful business outcomes. I am grateful for the work our teams have delivered together to serve our customers, and I look forward to the continued partnership on the frontier transformation journey ahead. Thank you. Accenture is one of our most valued partners. Julie and the team are trusted advisors to me and our leadership team, especially when it comes to how we can make sure frontier AI is safe and useful for large organizations. On safety, Accenture is helping us do something no AI company has done before. Last month, I called on the AI industry to pace the frontier to ensure our capability and safety advance together. As part of that effort, we committed to bringing in independent evaluators to assess how we train and deploy frontier AI models, and we call on others to follow our lead. This is new territory. It was not a decision we took lightly, and Accenture is the first partner that we chose. Led by Faculty, Accenture's team will red team our models, study their alignment, and test our safeguards. Both companies expect to invest at least $1 billion over the next five years in this work. This is money well spent because getting this right will both manage risks and bring forward this technology's profound benefits to humanity. On AI usefulness and adoption, Accenture plays a similarly essential role. AI is advancing very quickly. Four years ago, it could barely write a line of code. Today, more than 80% of all code committed to Anthropic's main code base is authored by Claude. Accenture is bringing this exponential capability more deeply into the world's organizations to drive growth, increase productivity, and unlock innovation. Accenture was one of our launch partners, for example, on Enterprise Frontier Safeguards, which lets customers keep data on cloud infrastructure they control while still benefiting from Anthropic safeguards to detect misuse. EFS has been a significant unlock for companies looking to deploy frontier models in high-value sensitive contexts. Internally, Accenture also walks the walk in making the most of AI's capabilities. About 115,000 of its people use Claude in their work every week. Accenture's Anthropic Business Group has built a broad portfolio of Claude-powered offerings. These are now in use across nine industries and 18 markets. Cyber.AI, launched in March with Claude as its reasoning engine, is putting frontier capability to work in helping organizations defend against cyberattacks. Very few organizations can match Accenture's efforts here or their scale and economic impact. That's why we're proud to call them a global premier partner, our highest partnership tier. Thank you to Julie and the entire Accenture team for your leadership and your partnership now and in the future. My best wishes for the rest of today's session. At OpenAI, our mission is to ensure that AGI, or artificial general intelligence, benefits all of humanity, or people everywhere, as I like to say. Accenture's purpose, to deliver on the promise of technology and human ingenuity, speaks to that same belief. Progress matters when it makes life better for real people. We're proud to recognize Accenture as an elite partner and as OpenAI's AI Transformation Partner of the Year. Together, we're helping clients move from AI that finds information to AI that gets work done. Asking to actually doing. With a leading global hotel chain, we're building an experience that lets travelers explore destinations and book their entire trip through ChatGPT. We're helping clinical research teams at a leading life sciences company analyze complex findings and draft medical writing with experts guiding and reviewing the work. These capabilities give people more time to think, to create, and to solve problems. Building on its $3 billion commitment to data and AI, Accenture is training 100,000 people on ChatGPT, Work, and Codex. Thank you. Our teams work through a technical center of excellence with 700 Accenture forward-deployed experts specializing in OpenAI, helping clients realize value faster. Trust, of course, requires protected information, carefully tested systems, and strong governance, with safety and security built in from the very beginning. Through OpenAI's Daybreak cyber program, we're partnering with Accenture to help secure the networks, data, and core business applications that keep our world and our clients running. Our ambition is a future where people work alongside AI, and ultimately AGI, with the tools, confidence, and the opportunity to just do extraordinary things. Really excited to be here. I have a health warning before I start. I think just seeing these videos and everything else, I get very excited. As I get excited, I will speak even faster. Rod, you got to kind of just say if I am speeding too much. I thought it will be good to kind of get that out first. First, I think thanks, Julie. It was great to hear from our ecosystem partners and the role we play in helping companies adopt and deploy their technologies. As you heard from Julie, there are two important elements that define our growth strategy. First, it is about growing our core, and second is scaling our network of businesses. You also heard that we have doubled our addressable market, going from $1.5 trillion to $3 trillion. Here is the maths to kind of explain what we are saying here. You got the base, which was about $1.5 trillion. We added with 20 new AI growth arenas, another $700 million to that. This brings to a total of $2.2 trillion addressable market in the core. Then we add $800 million for our network of businesses. In total, this makes the $3 trillion addressable market. Now let me talk about how do we think about executing our strategy, and I am going to break it into three parts. Three. First, how we organize for growth and serve the enterprise through our Reinvention Partners. Second, how we grow the core. This is the vast majority, 94% of our business, and is growing mid-single digit. We believe there is tremendous opportunity out there, in many ways created by AI. Third, how we scale the network of businesses. This represents 6% of our business and is growing double digits. The network has been built through organic capabilities and acquisition, focused on large, fast-growing areas. I will take a pause and kind of now go into how do we serve the enterprise. We serve the key buyers and budget holders through our seven Reinvention Partners. Walsh, my friend, who is a CEO of Americas, we were chatting and said, "Manish, nobody understands what a Reinvention Partner means." I say, "Reinvention Partners is just think about them as the key budget holders, the key decision-makers in any enterprise." It is as simple as that, just focused on the budget holders. As I look across the patch, it is very clear every Reinvention Partner has a massive addressable market. We approach each of the seven areas the same. Start with the buyer and then understand the business outcome they need to achieve. These business outcomes are what clients measure to drive growth, improve performance, and create resilience. For example, any company that we take, chief revenue officer focused on revenue growth and customer loyalty. The chief supply chain officer is focused on new products and faster time to market. The CIO cares about lower cost, about figuring out higher productivity, about security, about deploying AI at scale. Tying our success to our clients' business outcomes helps build the kind of trust Julie referenced earlier. I always like to think about tying AI to EPS. Go away from the hype and the frenzy. It is about do I get the EPS out of the AI or not? From there, we bring the full power of Accenture, our services, industry expertise, ecosystem, assets, and platforms, and we do right from strategy to implementation to operations. We serve our client end to end. Now, let's think about any company that you know, in pharma, in utilities, in banking, telco, or any other industry. They all have finance, they all have HR, they have a digital core, they have customer, cybersecurity, and most have supply chain. Next, think about the parts that are unique to an industry. Unique. The core value chain. It is why our industry depth is so critical and where AI can unlock the most value. We call this partner industry and enterprise. For example, I'll give you a few of them. For pharma, you have R&D. Utilities, there is the grid. For banking, it has got core banking, and telco has network. That is the logic behind the seven Reinvention Partners, or in quote, the budget holders whom we are working very closely with. For all the partners, AI is expanding the opportunity. Clients can do things they have never been able to do before. This approach gives us several ways to grow deeper with an existing client, access to new buyers and budgets, or adding new clients. For example, we can start working with a client in digital core, move to the talent, and then on to supply chain. So just kind of moving gradually. One reinvention naturally creates the opportunity for the next. This is our compounding growth model. Deliver outcomes, deepen the relationship, and expand into the next opportunity. Let's look closer at how this translates into growth in our core. As I mentioned, the core is about 94% of Accenture. What's most crucial to remember about the core is that its biggest growth driver will continue to be large-scale reinventions for our clients. We see these reinventions show up in many different ways in our business. Let's look at four examples, some illustrations which can bring to life. Digital core, managed services, enterprise AI stack, and AI growth arenas. First, digital core. Even after years and years of cloud and digital transformation, there is substantial work ahead to build the foundation enterprises need for the AI era. Many of these companies are on a multi-year journey, and all will need to respond to the new tech evolution. Some of the stats which you will see here. Modernizing ERP is only 41% complete. Moving to the cloud, where only 28% of workloads have actually moved. Sovereign AI, an absolutely new thing that has emerged in the last few years. As clients seek more control, we are seeing new demand in sovereign cloud, already a $215 billion market. On modernizing the legacy technology, the hardest parts of technology estate are only starting to modernize. I'll give an example on core banking. In July of 2026, we announced a partnership with UniCredit and IBM to modernize the mainframe that runs a bank while moving the right workloads to the cloud. In this, I would like you to hear from Arvind, CEO of IBM, on the importance of our partnership. Can we roll the video? Hello, Julie, and everyone at Accenture's Investor and Analyst Day. Accenture is one of the largest systems integrators and operators of IBM technology with more than 30,000 of their employees holding IBM skills. IBM technology runs the payments and core banking that cannot fail. Much of it runs on IBM z17. At those volumes, nothing matches it on cost, security, or resilience. Together, IBM and Accenture keep modernizing these workloads so clients can keep getting that return, and IBM Z stays one of the most enduring platforms there is. That is hard work. You have to understand decades of undocumented change, rebuild everything connected to it, and migrate without going offline. IBM Bob, our AI development partner, makes Accenture's consultants more productive at this. We have also published a joint roadmap for clients modernizing on IBM Z. Accenture has built IBM Apptio into the tools it uses to assess cost and value so clients can see what their workloads on Z actually cost and what they are worth. Same is true in AI. Clients want AI inside the systems they already run. With governance, their regulators accept watsonx to orchestrate and govern it with any model. Red Hat and HashiCorp to run and secure it on any cloud. Confluent for real-time data. Accenture consultants work with these IBM technologies in these systems every day. Here is a great example of our partnership. In July, UniCredit, Accenture, and IBM announced that we will build Europe's next-generation banking platform. Accenture leads operation, IBM provides the technology underneath. I fundamentally believe the most demanding work is ahead of us. That is why this partnership matters now more than ever. It is always good to hear from our partners because it kind of just tells you how we are uniquely leveraging our partnerships in different ways. Now, I want to move to the next section, which is around the managed services. Just to remind you, I am still in the core, so that is my second section of the core which we are talking about. I have been with the firm for, this is my 32nd year. I have been in almost every single part of Accenture's business over the last three decades. Managed services is extremely dear and near to me. I spent most of my almost two decades in managed services. AI has really opened up exciting new ways we can serve our clients in this space. Because the question always comes is about efficiencies. As said, greater efficiencies have always created more demand. I have seen this through my own, whether it was when we came RPA, the cloud wave, and all the things that came out, I have always seen that. That it has always created more demand for us. I think client come to us for the managed services as they are seeking a partner to run all or part of their business function and achieve their desired business outcomes. This means they get a better, faster, and lower cost solution while getting expertise and talent. We are at the helm of delivering business outcomes for our client in a tangible and a sustained way. Managed services consists of multi-year contracts, creating some of our largest, our most enduring relationships, and represents 50% of our business. People ask me all the time, "What is the impact of AI on managed services?" Always. This is like the favorite question in the last, I would say, maybe more than a year, right? I would say AI is creating more demand. In FY 2026, we grew 7%, and we expect to grow in the coming years based on the opportunities we see in the managed services. We see AI really accelerating the managed services evolution. Traditional areas are changing. Because I remember our first one was in July of 2001, right? We were doing all the managed services differently. We got approval for doing 40 people that time, and I still remember even today, that day. In tech, agents are now embedded to run and modernize apps. That is the tech managed services. In business processes, we have gone from keystrokes and all the stuff that we used to do of transaction processing to delivering tangible, sustained business outcomes for our clients. We have new areas. New areas which I think are still I think they are exploding in some ways. Like security, where we are defending against AI era threats. A $58 billion addressable market growing at 12%. New area. AI and data managed services, $110 billion addressable market growing at 15%. It encompasses enterprises replatforming for AI, monitoring agents in production, managing the data sprawls that are out there, and addressing rising cost, governance, and the compliance pressure that we always have to think about. Finally, another massive exciting thing for me, right? Underneath it all, we have reinvention.ai. I just saw a report where it is mentioned as the best which is there on this planet, right? An integrated platform for agentification and automation where we have invested almost $1 billion over the last four years, reinvention.ai. To bring to life, I think I want to Estée Lauder Companies is a great example of large-scale cross-functional reinvention looks like. Julie recently sat down with Stéphane, the CEO of Estée Lauder Companies, to talk about the reinvention he is driving across the enterprise. Let's hear from them now. Well, Stéphane, welcome. Thank you so much for joining. I know about a year ago, the two of us were in India at our delivery center with your entire leadership team. You are going to be there again during our Investor and Analyst Day. Exactly. With your leadership team. I really appreciate you filming this in advance so that you could join us for Investor and Analyst Day. No. Thank you so much, Julie, for being here. I am so excited. I still remember this visit that we had together in India like it was yesterday. The leadership team and I had this view of the scale, but more importantly, I see the talent that you have at our disposal today in India. I am looking forward to be in your office again in a couple of days. Well, thanks. They are excited to welcome you back. Maybe we go back for a moment. to actually the beginning because I know we're going to talk about the partnership, but at the very beginning, when you and I first had those first couple of conversations, the thing that struck me was that you had this very clear strategy. But the pace at which you wanted to execute was faster, not only that we'd seen at Estée Lauder Companies in the past, but in cross-industry. Industry, yeah. Really fast you wanted to move, but also the scope. You basically said to me, "Julie, I'm looking at everything. I want your best views. I want to reinvent how we're working. Yeah. And there's nothing that is out of scope. I want to just really think about differently. You can talk a little bit about just who Estée Lauder Companies is. Yes. Not everybody may know you as well, but also what was kind of going through your mind at the beginning in terms of pace and scope and what you were trying to achieve. Well, first of all, thank you for giving me the opportunity to speak a little bit about The Estée Lauder Companies. As you know, we are celebrating our 80th anniversary today, so it's a special moment for us. We have more than 20 beauty prestige luxury brands around the world. Among some of them, we have six of them that are billion-dollar brands: Estée Lauder, Clinique, MAC, Jo Malone, Tom Ford, and even La Mer. When I became CEO now approximately 18 months ago, when you and I had this discussion, we introduced our new vision called Beauty Reimagined. This vision was really to fundamentally transform the company at every level. We were looking at partners on how we were going to do it, but we knew we needed to do it fast, and that's where Accenture came into play. You and I had a discussion at the beginning. It was a simple guidance that you were giving me on the way that the world is evolving. Clearly, what I appreciated, it's very early on understanding how we could transform, and we can transform absolutely every level. I'm happy to just say that today we are partners, and this partnership is actually more than just a cost-cutting partnership. It's actually a partnership that is going to help us as a company to reignite growth. I'm very proud of where we are today. Looking fast forward at the end of FY 2026, we just finished 3 months ago, we are back to organic sales growth. Our adjusted margin is increased by 300 basis points. As an example, we have a third of our business online that is growing and gaining market share. We are doing this transformation with speed. This transformation needed more than just growth. We needed to, I would say, free up resources to be able to invest in growth, and that's where, really, Accenture came into play. Today, this partnership is allowing us to just simplify, to create efficiency, to create speed, but more importantly, to also get access to AI and agentic strategy that is giving us the opportunity to not only see today, but also the future efficiency that we can bring to the company. Stéphane, maybe give our investors a bit of a view of just how broad it is. Yeah. Why you wanted to go so broad in terms of how do you think about. You talk about this being a platform for growth. Maybe we can just talk a little bit about the scope. Beauty Reimagined for us has a bold vision at the center. We simply, but boldly, want to become the best consumer-centric beauty prestige company in the world. For that, we needed to be fast, we needed to be agile, and we needed to just bring a set of partners that are just going to help us to do the transformation. I think the first thing that we had to realize is look at our own operation. How were we operating? We were doing it in a very fragmented way with thousands of vendors and partners around the world. The way we were operating our brand and our regions and our functions was very disconnected, and I needed to find a set of partners who will allow us to just change, again, from a simplification and efficacy and at the same time also speed. Today, when you look at the scope of what we had discussed at the beginning, there is not one area of the business that we are not looking into. Today, we are deploying our transformation, our simplification through multiple transformation in finance, in supply chain, in technology, in people, in consumer care, but also in many marketing pillars. So really is a fundamental transformation that is allowing us to leverage our scale. Because ultimately, we are one of the largest beauty company in the world. Beautiful brands operating in 150 countries around the world, but very fragmented. We needed to just be able to face an increased competition around the world and bring simplification so we can do best what we do, which is creativity, storytelling, innovation, and also consumer experience at scale and leverage the power of the scale of The Estée Lauder Companies. You mentioned earlier AI and agentic AI, and that's an area that we are always talking about because it's so exciting. Yeah. How did you think about the technology and the AI component as you approached our partnership? Very early on February 4, 2025, when we put Beauty Reimagined, I made it very clear that AI would be hardwired in absolutely everything we do. So I needed to find a partner that was going to allow us not only to transform and to simplify and standardize, I think, many of the processes that we did not have in the company, but also the right AI and agentic strategy that will allow us to just create the ongoing efficacy. Because I want to be very clear, what we are now doing together is not just a cost-cutting exercise because we were in the midst of a restructuring to rebuild operating margin. It is actually to create an ongoing efficient model that through AI and agentic, we will continue to unlock efficiencies over time. Well, thanks. This is something that you and I have done together, which has been really exciting, but also your entire leadership team. Yeah is involved because it is so broad. So maybe as we wrap up, it would be great in your terms, your words, why did you pick Accenture? First of all, you are very convincing, Julie. Thank you. I think that was very, very good, but I think I've really enjoyed this partnership since the beginning, because this transformation is the biggest transformation that this company has done in the last 80 years. It is a leadership, it is a cultural, and is an operational transformation. So we needed a set of partners that were going to be able to operate at the speed that you've described at the beginning, but also allows us to create the efficiency. And this is where Accenture came into play. And I think the way I would describe it is almost like four things that you and I looked at and that took into consideration in the decision to partner together. One was simplification. Accenture is very well known for it, and you really help us, and you are helping us today because we are really deploying, we are going live as we speak in things like CRM, consumer care, tech platform, and frankly, everything is just going to be transfer. Every single areas of the business is going to be transferred very, very soon. That was one of the first point. The second point was, I needed a partner that we're going to be able to just give us the right technology platform and the right AI tools. You, amongst other partners, are really helping us to transform these beautiful beauty companies to be really AI first in the way that we are going to see how we're going to look at consumer insights, how we are operating, or meaning like operationalizing all our processes internal with AI, how we are deploying in supply chain, how we're deploying it in consumer care to ultimately do what we do best. I think this is one of the thing that was very important. But I think there's two other things that becomes more apparent as we are developing this partnership. It is also the tech infrastructure. I've been very clear, we are hardwiring AI through everything that we are doing. Accenture, like other partners, is really helping us to really transform the company in so many ways that allows us to just improve our consumer insights, improve our supply chain, improve our financial processes and governance, across basically all the pillars that we've discussed that we are deploying. That's really key for us for ongoing and future benefit that we will create an efficiency for the company. The last point is, I know it is dear to your heart and to my heart, too, is also the talent. I think I saw that, the two of us since the beginning, having had this relationship, but the second thing is also the talent that you've deployed and the talent that we have in our organization. I don't think with this talent, we would have been able to just operate with the speed at which we are operating. Not only it is fast in Estée Lauder Companies standard, but it is also fast in industry standards, and I think I'm really proud of what we are doing. It's really thanks to the talent. Accenture is really helping us to develop and to really get the business outcome that we are looking at. We are entering FY 2027 in a very different company than we were in the past. We're much more agile. We simplified organization. We are growing again, which was the objective that we give ourself. I know there's a shared objective. I know Accenture doesn't look at this partnership only as a cost-cutting, but as a partnership that helps us to free up resources for us to invest in where we want to be the best and where we want to be unique, and to just go back in growing and delighting consumer around the world. I couldn't be more happy about the partnership that we are developing together. Thank you, Stéphane. Well, we feel really proud and privileged to be a part of it. Thank you for allowing us to partner, and it's just great to see where you guys are going, your results, and excited to see this next chapter. So take care. Thank you. Thank you, Julie. It was great to kind of hear directly from Stéphane. What he described is exactly what Julie and I have been talking about, what it takes to deliver reinvention at scale. At Estée Lauder, that means transforming how the company operates across finance, supply chain, technology, marketing, and consumer care across 150 countries. 150. I don't think so there's any company on the planet that can do this transformation across so many countries. It requires simplifying and standardizing processes, modernizing technology, embedding AI throughout the business, and bringing people together, the right talent to deliver change at speed, which Stefan described about. I think Stefan also mentioned one important point. It's not about just reducing costs, because sometimes we get caught up about like. It is also about creating efficiencies that free up resources to invest in growth. In this case, they have invested in marketing operations to really drive an uplift in revenue. That is just our partnership with Estée Lauder. Now I want to go on. I am still in the core, and I am going to now enterprise AI stack. This is the third example in our large-scale reinventions that we are going to talk about. Simply put, the enterprise AI stack includes all the capabilities in an organization that needs to run AI at scale. You can think of it as the new systems integration work that we really, really need to now help our clients with. The enterprise AI stack has an addressable market of $500 billion. Is that like a wow? This market was just not there earlier. Simply put, it is not about putting a model on top of the building and the building gets automated and AI, right? This is where there is a real amount of hours and work that needs to be done as you are building the enterprise AI stack. It includes the seven layers, which bring together the models, the data, and the infrastructure that companies need to integrate AI into operations, modernize systems, and turn, my favorite, experimentation into business outcomes. Because that is the real key on this. Now, safety is an important part of the stack. I think last month, we announced our partnership with Anthropic. As you heard from Dario, we established a team of embedded evaluators to work alongside Anthropic's internal teams and safety planners, partners to evaluate and red team models, conduct alignment assessments, and test model safeguards. Security is not just IT, it is also operational technology as well, and we will hear from CEO of Dragos, Rob Lee. As more systems and assets are connected, we will need more of this. The enterprise AI stack requires continuous care within an organization, and we see this market scaling. I will give you one stat because you are always looking for stats and proofs on this. In FY23, we had only four deals that were data and AI led. Four. Today, we have 50. Just a data point. Now, for bringing this to life, I recently had a chance to sit down with my client and my friend, Kim Krogh Andersen from Telstra, a leading telco in Australia. In 2025, we launched a seven-year JV to reinvent work, customer experience, and the ways of working, building the full enterprise stack from top to bottom. Let us roll the video to hear from Kim. Manish, thank you so much, and thanks for having me. The reason for us coming up with this untraditional partnership, the joint venture, the data and AI joint venture, that was really to accelerate our data and AI journey, take the five-year roadmap and cut that down to two years, get the foundation in place, and deliver on our ambition, which is to be an AI-first company. When you look at all the stuff that we are doing, I think a strong foundation matters. Yeah. What measurable returns are you seeing so far from accelerating the data foundation to putting AI into production? It become clear for us to scale AI in a sustainable way and create real value. But also fund the journey, we need to have some foundation in place. This foundation for us was really to clean up our data estates. We are now down to 17 data platform. Years back, we were close to 100 data platforms. That means now we can scale with using less tokens, but we can also scale use cases because we have built every use case we do in a repeatable way. On top of that, we are not just plumbing AI on top of existing processes. Together with Accenture, we have identified eight cross-functional areas where we really believe there is big value. One example is the front of house, where we start seeing scale and real benefit. We also see it when we migrate from old systems to new system, old products to new products. There we have really used AI to scale that in a very effective way. We have reinvented the way we do sales and sales proposition in our enterprise business, a way to generate these offers in days instead of weeks. We have massive value pools in our network, part of the operation. We of course also have massive value pools when it comes to AI in the HR, finance, corporate functions inside Telstra. This partnership help us extract that value. You have described the foundation as much more than data and technology. How do the capabilities, such as the AI control plane, which I know it's your favorite, and tokenomics, help Telstra scale AI with confidence? I think a lot of companies, they will run out of money quite fast if they don't get control of the use cases and the way they use tokens and LLMs. We have an ambition to get all our use cases into what we call the control plane. The control plane we have developed together with Accenture, a plane where we get control of each use case from a sustainability, responsibility point of view. So we monitor every single use case and see if it's behaved as intended. We want to ensure that all the value we get from AI, or most of that value, is captured to Telstra's customer, Australia. Can you talk about the approaches you are taking at Telstra to enable people and help drive the adoption of AI, Kim? Yeah, we've been on a journey when it's come to adoption. The Telstra AI Academy is really a way to systematically give our employees specific AI expertise in a holistic manner. Actually last year, we have more than 15,000 that all took a course in that AI Academy. We need to ensure that people understand AI, because if you understand, you can also know how to use AI in a more secure and responsible way. So that has been a journey we have been on from the beginning. Even more critical is to really ensure that, Manish, we are operating critical infrastructure as a telco. We cannot allow any risk when it's come to cyber, when it's come to resiliency. The whole way we have built the foundation together with Accenture is such a critical part of that. As you have built this foundation, where are you now seeing the greatest business impact? Can you share a couple of examples of how AI is helping reinvent key areas of Telstra and the outcomes you have started to see? Our approach to AI was to really look at the biggest pain points. We are a massive energy consumer because we run a lot of infrastructure. There we have used AI early on. I will say, I think the network and the network operations is probably where we have the biggest potential coming. What I really like with Accenture as our partner was there was deep expertise in AI, there was deep expertise in the telco industry, and then there was also the willingness to invest and reinvent. We had an ambition to be an AI-first company, and you're really reinventing your company with AI, and you ensure you have the right foundation in place. Accenture were the partner we looked at that had the most aligned ambition, and were most aggressive also because AI is about pace. We need to ensure we're in front of the pack. We needed a partner that have access to all the new knowledge and always were on top of what's coming next. We also needed a partner that were a little bit more objective. We wanted to have some freedom to move between LLMs, between hyperscalers, between software providers, et cetera. We ended up with this joint venture with Accenture because we felt Accenture had the right capabilities, the right expertise, and also the right ambition that resonated with our Connected Future 30 strategy. We wanted to reinvent, we want to be a leader, and we want to set the standards for industry. Thank you, Kim. Thank you for your time. You are welcome. It was a pleasure. Thank you as always, Manish. I think you heard from Kim describe the move from AI and data foundations to business outcomes from AI, really creating the full enterprise AI stack. I want to just repeat the stat that I mentioned earlier. We had in FY 2023, 450 million-plus deals. 450 million-plus deals, and today we are talking about 50 million-plus deals. Because I might have lost in my speed that I forgot to mention, because they are large-scale reinventions driven by data and AI, 50 million-plus. I want to now move to the fourth area. I am still in the core and still trying to tell you how we are going to grow the core, and I would like to highlight the real big, and I think one of the most exciting things is about AI growth arenas. AI growth arenas are entirely new categories of demand created by AI that did not exist one year back. AI is opening new possibilities and new budgets at almost every part of enterprise and with the new buyers of our services. We are seeing demand in the last count, about 20 growth arenas, and each of them we have industry, engineering, software, and AI capabilities that position us to win. I would like to highlight, I can go on for the full day, but I do not want to kill you guys, only two of the arenas. One is agentic commerce, and the second one is software-defined vehicles. Looking at agentic commerce. Very simply put, AI agents are changing who or what they discover, they recommend, they select, and they buy products and services. In January, the pipeline was zero. We did not have this service. Today, it is $1 billion, and we have already won $125 billion as we speak. Looking at software-defined vehicles, the industry is changing. The software is becoming one of the most important components. Automakers across, they need to build and integrate more software and AI, shorten the development life cycles, and improve vehicles long after they ship. My friend, Tracy, and you will meet her in a short time, she says, "Think of this as iPhone on wheels." It is a simple explanation about that. Again, very small at the beginning of this year on January 1, and now a $600 million pipeline and winning. The pattern is the same in all the 20 AI growth arenas. Identify the opportunity early, build the capabilities and the credentials, and be ready as demand scales. You heard me talk about how we organize for growth. Then you heard me talk about four of the ways we are growing our core business through large-scale reinventions. I talked about the digital core and the white space there, managed services, which I am still the most excited about, enterprise AI stack and how we got from 4 to 50 million-plus deals, and the AI growth arenas. There is a lot of opportunity out there. Now let me shift my focus to how we scale our network of businesses. Second part. So chapter one, now we are going to chapter two. The network of businesses represents 6% of our revenues today, growing at double digits. Today, we have nine network of businesses. For each of these, the model is the same, and it is simple. We identify large growing markets where Accenture has a right to win. We give the business the operating and the commercial model it needs. We connect it to Accenture strength. We will dig into several of the businesses on the panel that follows this, and then later with John and Mauro. But now let us talk a few of them. I want to talk about Accenture Construct, DLB, and LearnVantage. So before we get into Accenture Construct, I would like to share a little history first and really show how we build a network of businesses. In FY22, we had a capital projects business of about $300 million. We saw the opportunity early. AI is digital, but it needs physical infrastructure. We moved fast, marrying existing capabilities and adding targeted acquisitions like Anser in August 2023, and then we got DLB in July 2026. Four years later, as you can see in the graphics, the capital projects business is growing 55%, with roughly half of that growth coming organically. This is exactly how we want to use acquisitions, acquiring to accelerate our growth. Today, capital projects is comprised of two network of businesses, Accenture Construct and DLB. Let me talk about Accenture Construct. We help clients plan, deliver, and optimize large capital infrastructure programs. It is a $260 billion market driven by AI infrastructure, the energy transition, and the aging infrastructure replacement. We already serve 19 of the 20 utilities in Americas, 19. And Mauro, my friend in EMEA, serves all the 20 utilities in EMEA. Now, Construct opens the door to new buyers inside existing clients. Leaders running major capital programs we couldn't reach before. And connected to our supply chain and the re-engineering reinvention partner, we can now bring the full range of capabilities which our clients need. Think 19 and 20, we couldn't serve them earlier. Now we are there ready to serve with a totally new capability. Next, DLB. Data centers are one of the clearest examples of AI driving capital investments. DLB Associates brings specialized engineering, commissioning, and consulting for data centers and mission-critical facilities. With DLB, we support clients across the entire data center life cycle, right from site selection through commissioning to decommissioning. This is a $12 billion market, $12 billion, expected to double by 2030. Third one, LearnVantage. As I said, we have got nine. I am talking about three, and we will dig into slightly even deeper in the panel. LearnVantage is an AI-native learning platform serving a $110 billion market. As workforce capability is becoming a constraint on AI adoption, LearnVantage really, really helps clients upskill their people in technology, data, and AI at scale. And because it operates on a platform, it is also a non-FTE commercial model. So as we look ahead, we will selectively expand our network into new markets, and I am really looking forward to our next launch, where we will bring to market products built using our deep industry and functional domain expertise. I am saying the nine will become 10, and it will continue to grow. As I look across the network, these businesses are different, but the model is the same. Identify the opportunity early, build a differentiated position, use the right business model, and scale it with the power of Accenture. When I say the power of Accenture, we have got the world's largest client account leads, who are the trusted advisor, who are the orchestrators in more than 4,000 clients across the world. Largest, I think, the intelligence as a trusted advisor, which is what we bring. That was a lot that I covered on this. I talked about how we organize for growth, think budget holders, to reach our key buyers, and the budget holders. I talked about our core business, which goes through large-scale reinvention driven by AI, and I finally talked about nine fit-for-purpose network of businesses to capitalize on large, fast-growing markets. One of the most important points you have heard me say, and you will hear repeated throughout today, is this. I want to bring back to this chart, which is we have expanded our addressable market by 1.5 to roughly 3 trillion. That is the maths, and I was giving you a lot of tabs, but I wanted to summarize this again for you. If you even need any more details, very happy to engage. This is one of my favorite topics. The impact of AI is undeniable. Now, to help me bring this all to life and to dive also deeper, I would like to invite a few folks to join me on the stage. Lan Guan, who is our Chief AI and Data Officer. Tracey Countryman, she is a Reinvention Partner Lead for Supply Chain and Re-engineering. Rob Lee, he is the CEO of Dragos, our network of businesses, function focused on OT security. Marc Warner, CEO of Faculty, another network of businesses, and now also the Chief Technology Officer for Accenture. I will try to moderate the panel, but these guys are a bit unruly, so sometimes the panel might Really go on its own way, but I will try to do my best. I think one of the things I always find about Accenture, even after three decades, is just the incredible talent we have. For me, when I just see the four leaders walking in, I get goosebumps. Like, wow, who in the planet can have these kind of leaders? I am going to start with Lan. I am going to put you on the spot, Lan, on this, because I talked a lot about enterprise AI stack, $500 billion market, and all the good stuff there. What does it really mean in kitchen English? Otherwise, and I talked about it being the new systems integration work, but just explain to our investors and analysts what we are talking about in this Sure. By the way, you did great. In plain English, everybody can write code. Every company has cooked up some kind of AI pilot. But as what we talk to client every day, AI scaling is really hard. Accenture builds an enterprise AI stack, and you can think of that as the industrial kitchen to scale AI. Since ChatGPT launch, our team has done 18,000 AI projects. We know where companies stand. Most of them have baked a cake in their grandma's kitchen, so to speak. Now it's time for them to get industrial kitchen. That is equipment, repeatable processes, quality controls, so that all of them can make the cake consistently and safely for millions of times. That's what we mean by enterprise AI stack. This is not a quiz. Manish showed the seven-layer cake earlier. This is what I do every day. Seven-layer cake has data knowledge, models, agentic core, governance, security, and safety, scale AI operations, and then user front end. All of this need to be built on top of a robust AI infrastructure. My point here is model is only one ingredient. You need everything else in the kitchen to bake the cake. This is a lot of work for us. Also, I want to call out the work is durable. The work will never go away. Why? Because as new tech get launched every day, what does that mean to us? We have to do new work to integrate the new tech into the stack. Plus, Manish mentioned the AI-managed service before. The stack needs to be run all the time. Why? Because model will drift, data will get out of shape over time. Also, we believe that readiness drives demand because, Manish, I hope you agree with me, the industrial kitchen cannot be filled on top of some kind of a crumbling foundation. You talk about how companies will do cloud migration modernization first. I will add to that, they also need to get their data AI-ready as the new foundation. Last but not the least, why this is so important to us, because this role is very hard to replicate. I'm not bragging about it. I actually think we are the only one who can do this work because we bring a lot of industry knowledge, a lot of AI expertise. That is a perfect combination. Plus, we have done this hundreds of times. Thanks, Lan. It's always, I think, to demystify this enterprise AI stack, and that is why I got Lan to describe. Lan, one client example where you can illustrate where you're seeing how we are deploying this. Yeah, very quick client example. Actually, this is a personal project that I personally led. I think this is something that everybody can relate to. We built an AI travel companion for a large airline. Manish, I don't know about you, but to me, when I think about personal trip planning, it's full of what I call moments of anxiety. There's just so much in the air. The system that we build needs to be able to handle billions of customer inquiries with a messy prompt just like this one. "Oh, hey, I'm a loyal customer of your airline. I think I have $500 credit from the past canceled trip, and I want to take my family for the first time to Paris to stay in a great hotel, but I want to use that credit. How should I do it?" This is an everyday question. But we have to build a stack to actually get the work done. Initially, just like everybody else, we rush to the model. We connect to the very powerful models, but then the out-of-the-box LLM doesn't know anything about the customer, doesn't know anything about airline-specific things. So we have to give model the context. That is very important. We integrated a lot of data from airline. We also leverage a lot of airline's knowledge documents. Lots of them are standard operating procedures, policy document, very long, very messy. So we have to do a lot of work to cleanse them and actually bring them into AI. We also build a lot of semantics. You probably heard the term before. That's basically giving meaning to data so that AI will actually disambiguate a fuzzy term, like what I said earlier, great hotel, because great hotel means different things to different people. This is the kind of work that we do behind the scene, and then we build agents. Think about agent just like a team working in the kitchen, and you have the orchestrator agent that is a head chef, managing a bunch of specialist agent. While we're building agents, also it is very critical for us to make sure that we do governance and safety and security, which I know my friend Mark is going to expand on that later. But we want to make sure that agents are following policy, systems are secure, and user front end, the other layer that I talk about earlier, is very important because many people don't realize now users for agentic AI actually include both humans and agents. So humans interface, there's so many choices. I got asked by my client every day, how do I not get locked in? Agent interface also needs to be highly operational. Then we need to put all this together. It's almost like the industrial kitchen needs to have a command center to make sure that everything is running smoothly. All of this need to be built on top of a very robust infrastructure. I think the key takeaway I want you all to have from this example is enterprise AI stack is the linchpin to scale AI. Back to you. I think it is just, and for me, I know whenever I go for any discussion and people say, "Can you just quickly do some AI and get things out very quickly?" It is like really hard work on this. We see this, if you look back at history, always the technology change to get the value goes hand in hand with the process change, whether that is steam to electricity or containerization or original computers into enterprise. It is just bringing both together is the only way you ever get the value. 100%. That is why I love this team. Let me go to Rob. New in Accenture. He is likely six months. You are three weeks. Love it. Rob, happy to see you here. For all of us here, first of all, OT. Yeah. It's like IT, everybody is grinding, will go away. OT. For you develop every night, you are worried about, oh, my God, what is going to happen? None of us really think about this, and it's going to become a $59 billion market. Tell us, Rob, more about this. Yeah. OT is the physical world, and no one notices it until someone hits the light switch during a talk and the lights go up and down, you go, "Uh-oh, something's going on." That's OT. It's the physical aspect of data centers, water, electricity grids, pipelines. It's our world. All of the money has been spent on the enterprise IT side to secure it. That's not effective in OT at all. No CEO is confused about where they generate revenue. It's not the website, it's the operations side of the house. For governments and others to figure out that it's not protected, they're freaking out. We see it happening. We see 700 supermarkets across France in the last week, refrigeration units turning up the heat, spoiling food, fires in supermarkets. People are scared. They're looking for partners. They're looking for answers. They're looking for solutions. For Dragos to have the technology, for Accenture to have the reach, it's hitting a time and place that everybody is taking this seriously and needs an answer, and it simply hasn't been done before. You can't have an AI revolution or space revolution without energy and infrastructure. You can't keep it very long without OT security. I think it's just wonderful that we're doing it today. I first met Rob in Davos. It is pretty quick, actually. It looks like it was yesterday, right? I had a good tutorial on OT from Rob. He came to meet, and Walsh and I were together, and we were really having a good time. I think it just shows, again, a massive opportunity that we have and how we are going to build on this. With that, I am going to go to Tracy. Now that every time he gives me this example, I start wondering, getting worried. You are right in the middle of all the factories Yeah and all the plants and the maintenance and Yeah everything else going on. How has AI and security got to be designed as you are building this stuff? First of all, I am so glad you are with us. He is my best friend in what I do and what our teams do. We are seeing AI in supply chain engineering across the patch, right? It is early days, but if you think about it, R&D and engineering, core part of our client's business. We are deploying AI with clients now to figure out new discoveries, formulations, new products. An engineer spends 40%-70% of his time, depending on industry, looking for data, doing documentation, redoing engineering drawings, and then trying to get it certified and out the door. Agentic is brilliant for that space. Second, once we have designed a product, we have to make, we have to source the product and the materials. We are seeing AI in how we look at alternative materials and sourcing. We're seeing how we can leverage it for optimizing spend. It used to be we just cover the top categories of spend. Now we can cover all the categories of spend. Thank you, AI. Once we have the materials and we've designed this product, we got to make it. Manufacturing and facilities. I couldn't agree more. It is the heart of the client's business. It's literally the crown jewels. We're seeing AI being deployed with our clients, with our help, in driving optimization, production, yield, quality, energy usage. Almost every client's looking at this on how they can save money but also create growth. The last part of our chain, supply chain. How do we forecast better? How do we plan better? How do we respond more to the customer's demand and the signals, tie all the other driver together to drive more resiliency? We can't scale any of this without what Lan said, which is we got to have our OT data and modernization in order. We got to have the data foundations available. We got to have it secure. We got to bring our workforce, our engineering and operations workforce and supply chain along in this journey to be able to do this. Let me give you an example from a leading industry. One of the top industries we have in automation is automotive. One of our clients, the Renault Group, they're a European car manufacturer. They've spent seven years working on data foundations. The core data foundations. What does that mean? It's across 20 plants. It's connecting 25,000 machines. 25,000. I love the example of the billions of data for airline, but this is 5 billion data points a day. That's real-time operations and production, so that we can have cars. That's interesting for the visibility and how that all comes together. They've already saved by doing that and being able to look at what's happening in the lines. They've been able to save 120 million EUR a year, and they've been able to improve by 50% the ramp-up time for new cars. That's growth. Now that they have this amazing data foundation, they're figuring out how do they do an agentic layer on top to create an entirely new operating system for factories. The agentic layer that can figure out and anticipate disruption around energy, supply, and anything that might change the output of those facilities from a network perspective. That's unbelievable. The reality is what Julie said earlier, and that is most of our clients are not there yet on this journey on how they can bring that data set together. We're talking about decades-old plants and equipment. We're talking about the fact that 75% of our companies are still doing manual operations. We can't talk about agentic over here when we're talking about stuff that's not digital yet. The whole future is in front of us, and how we're going to scale and help our clients get there is absolutely in the forefront in the very beginning. To answer the second part of your question about OT security and my buddy over here, it's absolutely imperative. It's not a nice-to-have. We cannot do the digital and the AI in these critical parts of our client's business without OT security. Rob? Well, I love hearing that. I think it's the critical It is. part of critical infrastructure. Again, people understand that outside these rooms and in the field. No CEO wants to have a loss of human life, right? No. No national security leader wants to have a loss of human life. That's what we're talking about when we talk about cyberattacks on OT. It's catastrophic. It's power grid failures. We've already seen people try to kill people through cyberattacks. Nobody wants to talk efficiency in comparison to loss of life. 100%. Everybody wants to secure those facilities. I just think it's absurd sometimes that we spend so much time only focusing on one aspect of security when our entire world and our communities and our families depend on this other aspect. Again, I think that's only when you have trusted brands and partners like Accenture, you have all the expertise in one place. You have unique proprietary data models and insights that no one else has access to, and you can bring that into an outcome that not only takes businesses and allows them to transform, allows them to take advantage of AI, but it also protects people. The combination of those two things is a good mission, but of course, it's a huge market. The combination of those is just going to be something that I think we're going to be talking about for the next 30 years. Every time you give me with all the stats, you just make me worried, actually. I always come off like the doom and gloom guy at the panels. Yeah. The thing which Rob is talking about, not many people really understand the implications. That is why I said I got my first tutorial from him in January in Davos. Let me move to my next tutorial that I got, which was with Mark. I met Mark in London when we were having the first discussion. We were near the whiteboard, and we were fighting with each other who will take the pen on this. Mark, when we first met you, what I really liked about Mark and the team was they are a team of like 400 PhDs and all the good stuff, but their humility and being on the ground is incredible. They talked about safety 10 years back when it was not very cool. Now everybody has suddenly woken up about safety. Oh my God." These guys were talking about it 10 years back. Mark, tell us about what does safe mean in the world of models? Yeah, I guess, well, we've sort of always cared about safety because it was always obvious to us that if you anticipated AI playing a much bigger role in society, failures of it would also just be more impactful. I think sort of similar to what Rob and Tracy are saying, the thing people still miss is that safety is going to be the unlock to doing AI at speed and scale for exactly the sort of similar reasons that Rob is saying about OT security. No CEO wants to bring AI into their organization that they can't trust and can't control. We think of it much more like, well, imagine a car, you have your brakes, which are sort of fundamentally a safety system. If you want to do the fastest times going around the track, you don't throw away your brakes. It's getting the safety systems, the brakes, and the gas working together effectively that gets the fastest times. We think AI will be basically identical to that, and we're seeing it in practice. In the U.K., we did one of the first agentic system builds in the finance sector for a new bank called Tide, a growing business bank. Actually spotting the fraud there is to help them do fraud detection. Spotting the fraud was quite easy. It was building all the systems around it, many of the things that Gagan was talking about, that really took the time to get it right. Once you do that, the value is just obvious, and the organization can adopt it much, much more effectively. Now, again, this is where I tell you can get anything away from the discussion, but just see the talent and the wisdom that these people have. Talk to us about applied AI. Obviously, we talk about this, but you are not only safety. You are at the forefront of applied AI, solving large business problems for life sciences clients and others. Talk to us about this launch of this new lab that we are talking about. Yeah. We think of ourselves as an applied AI company. We started in 2014, back when there was only really people doing more academic foundational research. But we could see AI was going to be incredibly important, but we thought that it mattered that it actually affected people's lives in meaningful ways. So whether it was making education better or healthcare or products cheaper, all these kind of things. We actually coined the term applied AI to illustrate what we wanted to specialize in. Right now, there is basically an open problem, which is AI is this extremely dynamic technology. Every day even, week, month, certainly, there are new releases, and the capabilities are just increasing and increasing. Organizations don't know how to bring that into their businesses. Together with Accenture, we are going to invest in something that we are calling Faculty Lab, which is an organization that's going to sit at the intersection of frontier AI problems and real enterprise context so that organizations can actually start to understand how to bring this into their businesses. Think about something like software development. If you want to use coding agents as an individual, there's a ton of different blogs you could read. If you're a startup or a scale-up, there's small amounts of good insight. But if you're an enterprise that wants to use it in a regulated environment with tons of legacy systems across multiple geographies, multiple time zones, different teams, there's basically nothing on how you should manage that, how you should integrate these coding agents. That's a disaster when there's about three times the number of software engineers that operate in enterprise as compared to startups. We are just not able to get the value out of the technology at the moment. But soon we will be able to. I mean, the big deal that you were talking about with Anthropic basically came off the back of Faculty investing in safety, very, very small amount over the last 5 to 10 years. We are going to have 10 or 100x that budget in the lab and a much broader remit. I think we will be able to see some equivalently exciting things come out. You have got me overexcited as always. This is as usual. Rob, I am going to come to you. You are running a very successful, very fast-growing business. Accenture also is doing this OT security, and we are also the large cybersecurity business. What is the power of coming together here? Yeah. First, Accenture has already been doing this. When I started this company 10 years ago, nobody was really doing a lot of OT security. It was not really a market. Investors were not looking at it. They thought it was crazy. I remember getting laughed at plenty of times in Silicon Valley. And now it is the biggest market that people are chasing. But Accenture saw it 10 years ago. Nobody else was investing in the services and the expertise and the talent. A lot of your competitors, they were there, they left it. They sort of flirted with the idea, but they did not stick with it. And nobody in manufacturing, nobody in oil and gas wants to see somebody whose first OT environment is their OT environment. That is just not going to work. Yeah, that is true. For Accenture to have that level of commitment and talent, it resonates with the customers. For us, we have the technology and the expertise and the credibility as well, but we do not have the reach and scale. By partnering with Accenture, we were able to immediately start opening up new geos and markets. We had customers come to us that trusted the Accenture brand and knew they could be successful. And these are huge projects. These are massive multimillion-dollar deals, huge undertakings, and they are things that people have not done before. Every CISO knows how to evaluate the next security technology in an IT market. They just need help. But in OT, if they have never done the journey at all, they need a huge partnership. And they needed somebody to unlock the value, to operationalize it. Not just to deploy the software, but many times to manage the security services after the fact, and to be there, unfortunately, when it's the worst day. Everybody's worst day is that incident that takes place. It's scary. Something's going on. It's not anything that you've been through before. You need somebody to turn to. For Accenture and Dragos to combine that credibility, that authenticity, the expertise, the technology stack, it's just something that everybody's been waiting for. I hear from a lot of our clients that it's now time for them to accelerate. I hear a lot of CEOs going to the CISOs who don't understand OT historically, saying, "This is our number one board priority. We will give you new budget. This isn't taking away from your IT budget. We will unlock new budget. Just please go fast." It's going to be an Accenture Dragos combo that gets us there fast. Thank you. I think what Rob just described, I think IT has been focused and everybody's talking about IT for a long time. OT is going to be one of the biggest, I think, spends that we are going to really see. If I could say, no president and head of state has ever talked to me at Davos or anywhere else about their printer. Nobody has ever said, "Hey, can you help me with my cell phone?" It's always been in a conflict scenario, in major attacks. How do you help secure our country? All of that is just OT. Yeah. Man, so inspiring. Now, I'll go to Tracy. Back to you. Tracy, I think for the investors, I think they've seen us as IT, and we are doing all the functions and everything else. People with hard hats running around the place. Give us a window into what is AI doing into this world of yours. I love that. Hard hats and steel-toe boots. I wanted to just paint a picture there. Yeah. It's steel-toe boots. Multiple things. One really interesting example that you guys might find fascinating is that we were selected as a sole engineering partner for an aerospace company to do a lightweight transport 19-seater airline. And we did everything from early concept to structural design through digital replicas, through documentation and certification. And we did that using AI in every part of that process. One, that's kind of the R&D example around manufacturing. Little different than Renault. That example is really with a company called Unilever. You guys might use Unilever products. You'll be happy to know that when we deployed digital twin in a North Carolina plant with Unilever, you probably got more deodorant. Kidding aside, we did deploy a digital twin, and that effectively is looking at line stoppages. And how can we drive a 95% reduction in line stoppages on our deodorant line? How do we drive improvement in capacity of 10% on existing assets, and how do we reduce the waste by 20% as one example. We have other examples with mayonnaise. You will be happy to know that you get really good, consistent mayonnaise as well using a digital twin. I use those examples a little bit jokingly to bring it home, but the reality is, we are working with clients to deploy AI on the shop floor to optimize their production lines, both for cost and safety, but also for throughput and growth. The last example is the hottest topic besides OT, of course, and besides AI and all these other things, is really physical AI. One of the latest things that we are helping our clients figure out how they move things with robots and other capabilities. One of the challenges with doing physical AI is that often to deploy it, you have to stop production. We do not like to stop production. If you go into a warehouse, we are talking millions of packages that are running 24/7 to go out the doors. We partner with a company called KION, who is a leading provider of software and warehouse optimization, to simulate, to do a physical replica of a thing like this room, to then simulate thousands of scenarios exactly as it was built to train robots and models to be able to figure out how that is going to work with humans on a shop floor. Once we have the right layout, the right setting, and the right design, then we go deploy it in facilities. That is the future of physical AI and where things are going, doing things before they physically get put in. Those are just some examples. Our clients frankly need help. This is messy. It is complex. It is mission critical, for sure. Now they are looking and saying: How do we help our people on the shop floor go on this journey, and how do we help them transform with data, AI, and cyber in a very fragmented and critical set of operations? I want to just link what Tracy just mentioned to the graphics we were showing earlier. $300 million grown to $1.9 billion, 55% compounding rate of growth. Yep. That is why it is so exciting. Thanks for sharing. Now, Lan, I want to end this conversation with you. Everyone here, we get new models coming out. There are open-weight models coming out. What is so much confusion around this, and people are You explained how we make it work, but tell us a bit more about the models selection and the open-weight model. What do the clients need? Absolutely. It is really hard for me to follow the race car example, the airplane example. I do not know what I am doing here. But to me, Manish, this is pretty straightforward. I think the logic is these models are super powerful, but they are not easy to use. What we are seeing is companies not getting value, and they pull back. Our job is to put those models to work so the business get value, and also model partners that you and I work with every day, they get consumption. Manish, you and I have seen this in the earlier days with cloud. Companies were signing a very large, significant consumption commit, but buying capacity is only the beginning. We were the ones who actually helped them move the application, connect the data, change the way they operated so that those spend commit actually turn into productive use. We are seeing this again with AI, same logic. When companies are not getting value, they retract from their AI investment, and our model partners are not getting consumption. That is the dilemma. How do we get them unstuck? Three things. First, we make model work. We work with lots of model companies to build repeatable industry solutions, and we also help clients build all kinds of harnesses and supporting infrastructure to make the model work, so our business clients get value. Second, we help companies select the right model for the right work, so that the total consumption will go up. If I ask five people here, what are your favorite models? I will likely get 50 different answers because there are hundreds of models, and new models are coming out every week. In fact, Manish, the tokenomics research that you and I did a couple of months ago actually proved that there is only 10%-20% of the enterprise workflow justify the use of the frontier model capabilities. Many companies just started realizing that not every model, every workflow deserves the most expensive model. That is the work that we are helping them with by selecting the right model for the right work so that they get value and our model partners will get consumption. Third, we also work with companies to utilize open-weight models so that they can have better control over their data. Also, as you know, just a few weeks ago, we launched our full lifecycle services of helping companies onboard, manage, and run open-weight models in their secure environments. Yes, you heard it right, full lifecycle services. This will give companies many more options for them to use the models that they want, and this is even more critical in regulated industries such as healthcare and banking because they cannot leak their data. Also, the cost of managing their model is extremely critical, and regulatory compliance is non-negotiable. We got too excited about talking about models here. But as a veteran in this business, I have been doing this for 20 something years. I cannot have thought of a better and more exciting time and thrilled to be leading this business. As Julie mentioned earlier, AI is the tailwind to our business, and I firmly believe in it. Thank you. I think, always good to chat. When she says we did the tokenomics paper, she did it. She and her incredible team, I think they did it. I think just wanted to end this with saying that we see a massive opportunity. We see lot of white space in everything that we do. We see millions of hours that work that needs to be done in deploying some of the technologies that we have just been talking about. I think, again, the model for us is the same, which is identify the opportunities early, invest, build organically, acquire, and scale with the Accenture's power. But that is what you got from the team here. But thank you for listening, and thank you for the discussion. I think we will continue the discussions over lunch. But now it is back to Julie. Thank you. Thanks. Great job. Thanks, everyone. Great job. We now have a short break, so if you can join us and be back in your seat at 10:45 A.M. Our next section, we do have a live interview at one point with one of our clients, so it would be great if everybody can take a short break and be back here at 10:45 A.M. Thank you. For that, we are going to hear, again, directly from some of our key ecosystem partners, many of whom we both use at Accenture and implement at our clients. First, we are going to roll that video, and then we will go directly into John and Mauro, and then we are going to have a client join live from London. Let us roll the video. Accenture and SAP have been serving customers together for more than 50 years, from the early days of enterprise software, to the shift to the cloud, and now into the age of AI. What makes this partnership unique is not simply its long history, it is that both companies share a fundamental belief. We know that real value is created when enterprises use innovation to reimagine the way they run and grow. For decades, Accenture has been one of SAP's most strategic and trusted partners. Accenture combines industry expertise with large-scale business transformation. They understand how value is created across supply chains, finance organizations, customer operations, and workforces. They understand how technology can transform those businesses in practical and measurable ways. They deliver change at an enterprise scale that few firms can match. This becomes even more important in the age of AI. To succeed today, companies must unlock the value of their data, embed intelligence across their business, and accelerate decision-making. Accenture and SAP are helping clients to do exactly that. Embedding SAP Business AI across their core operations to create the autonomous enterprise. As SAP goes all in on AI with our full focus on the Business AI platform, we look to Accenture to build the agents on this platform, to support our customers on this journey with change management, and help them unlock the maximum value out of AI for their business. As we do this, our partnership will only grow stronger. Accenture doesn't just advise clients on SAP transformation, they live it. They run many of their own mission-critical systems on SAP technologies. Accenture is one of the first to apply SAP's latest innovations to create efficiency and business value in their own business. This experience makes them both a trusted advisor and practitioner. Looking ahead, the opportunity in front of us is significant. Every enterprise wants to realize the vision of the autonomous enterprise and transform for long-term growth. That is what SAP and Accenture deliver together. 50 years of partnership, and this is just the beginning. For nearly five decades, Oracle has helped organizations run their most critical operations. We understand their data, their industries, and what it takes to deliver results. Today, we are bringing that experience together with our infrastructure and applications to help customers put AI to work to deliver real, measurable outcomes. Accenture shares our focus on customer success and has been a leading global partner for 35 years. Together, Oracle and Accenture have certified tens of thousands of consultants worldwide. Accenture brings industry knowledge and implementation experience to help customers turn AI ambition into everyday practice. They have already built more than 300 custom agents in Oracle's AI Agent Studio, including agents for finance and procurement. With our advanced intelligence engine for Oracle, they have delivered sovereign AI solutions across the globe. That work has helped make Accenture our number one partner globally for Oracle ARR in fiscal year 2026. What matters most is what we help customers accomplish together, moving faster, simplifying operations and giving their teams more time to focus on the work that drives their business. Thank you to Accenture for 35 years of partnership and commitment to our customers. I am excited about what we will deliver together next. I would like to say a few words about Workday's partnership with Accenture. It is a partnership that means a lot to us. Earlier this year, Accenture was named Workday's 2026 Partner of the Year for Business Impact in North America. That award reflects the huge role they play in guiding some of our largest customers through their toughest transformations. What sets Accenture apart is simple. They understand Workday from both sides, as one of our most strategic partners and as one of our largest global customers, and that matters more than ever right now. Every organization is trying to figure out how to move AI from experimentation to doing real trusted work inside the enterprise. Accenture brings the scale, expertise, and reinvention mindset to help make that happen. They do not just talk about it, they live it. Accenture is one of our most advanced and forward-leaning customers when it comes to Workday AI, running more than 30 AI and agentic capabilities across their entire global workforce. That matters because when they advise clients, it is based on real-world practice, not theory. They are also true co-innovators with us, often helping to pressure test new capabilities like Workday Data Cloud and HiredScore before we bring them to market. And that co-innovation translates directly into real impact for joint customers like GE Vernova, Salesforce, and Crescent Energy. At the end of the day, great partnerships are built on shared values. Together, Workday and Accenture are grounded in trust, driven by customer impact, and committed to shaping the future of work safely and responsibly. We are proud of what we have built together and even more excited about what is ahead. It takes an ecosystem to change an industry, and that is why we are so proud to partner with Julie Sweet and Accenture. What makes this partnership so special is simple. We dream really big together, and we execute at mass scale. We are living through the greatest technology shift of our lifetime. CEOs do not need another pilot. They are done with that. They need growth, margin expansion, and stronger security. ServiceNow and Accenture closed the last mile of AI from technology to business reinvention. At ServiceNow, production AI deployments have increased ninefold in nine months, and Accenture has been instrumental in helping our customers turn innovation into impact. We are only just getting started. Accenture became the first partner in our joint forward deployed engineer program to really drive exceptional results. We are bringing our engineers closer to customers while unlocking over 300 pre-built agent skills to accelerate the journey from experimentation to adoption. Every day we come together to turn our customers' biggest challenges into their greatest opportunities. Together, we're combining ServiceNow's end-to-end cybersecurity platform with Accenture's AI capabilities to help our customers defend the enterprise at machine speed. That's why Accenture is our number one partner globally in every market. Also, our AI Customer Value and AI Domain award winner for 2026. Congratulations, Accenture. The next chapter of AI will be defined by who turns intelligence into action. That's what we do together, and together, Accenture and ServiceNow will change the world. Julie, I just want to thank you so much for 20 years of great partnership between Salesforce and Accenture. It's just been incredible the last two decades, what we've done together, customer success, innovation, incredible. I would just have to say that it's all built on the foundation of trust that both of our companies value so highly. What we saw at Dreamforce when both of our companies came together to pioneer the work of Claude, to use Slack with our largest and most important customers, and even some of this incredible next-generation work with our new Agentforce platform, the results were incredible. I can't wait to see how this is going to come together over the next year. It's been an incredible moment to be partnered with you, and I could not be more excited about the future. All the best, and thank you so much again for this great enduring partnership. We deeply value our partnership with Accenture that we've built over the last 20-plus years. It's a global partnership across all five regions, and Accenture has been our Customer Experience Orchestration Partner of the Year for six years now, and we're really proud to partner with them with hundreds of joint clients across the world. When you think about the work that we have delivered for clients, of helping them deliver personalized experiences at scale to all of their customers, millions of customers around the world, over a trillion experiences that we deliver every year. What Accenture does of bringing that content and data and journeys together for our clients is key to helping our clients get the full value of the investments they make in Adobe technology. As we go into the world of AI, what is really important is helping our clients get the value of AI faster, more cost efficiently, securely and accurately. That is what, together with Accenture, we are doing for all of our clients around the world as we deliver agentic software now for creativity, productivity, and customer experience orchestration. Accenture is a partner that has all eight of our specializations, so they really cover the entire range of Adobe technologies across these three critical areas of creativity, productivity, and customer experience orchestration. I look forward to continuing to strengthen and build our partnership well into the era of AI. Thank you. Okay. Good morning, everybody. My name is John Walsh. I am CEO for the Americas. It was really great to just hear from all of our ecosystem partners. With me, I am joined by my good friend, Mauro Macchi, who is the CEO of EMEA. As you might imagine, Mauro and I talk almost every day as we coordinate with all of our global clients. As much as I wish the best for my good friend Mauro and his team in Europe, I am always wishing America does just a little bit better. Well, thank you, John. Well, I can also say that I can share this competitive spirit all the time with you, but I am really enjoying and it is great to be here. As Julie laid out our new foundation for growth, and also Manish a few minutes ago showed you what our Reinvention Partners bring to markets, now John and I will take you to the client level. We really want to focus on the demand environment in our two largest market, how we build relationships and serve our clients, and the white spaces that we see. I believe that we come at this from different vantage points. John, you and I talk to CEOs all the time. What is one thing you keep hearing? If there is one thing that we are consistently hearing from CEOs, is that right now the cost of standing still is greater than the cost to change, and that is in spite of the fact that our clients are operating in one of the most complex environments we have seen in decades. Geopolitical conflict, changing trade relationships, rising sovereignty requirements, and a higher cost of capital is reshaping how companies invest and operate. Supply chains are being reconfigured, as you heard from Tracy, and cyber and OT have become board-level priorities. Every major investment right now is facing greater scrutiny for ROI. At the same time, AI is creating extraordinary opportunity for growth and productivity. Across the Americas, we are seeing this translate into investment around five major themes. I mention these because these are not short-term initiatives. These are cyclical spending or cyclical spending priorities. These are long-term structural investment cycles that we expect enterprises and governments to invest in for the next decade and beyond. Together, they represent hundreds of billions of dollars of technology, operations, and transformational spending initiatives. I highlight them because, as you heard from the panel today, Accenture really sits at the intersection of all five. AI-powered reinvention to drive both growth and productivity. This is where the enterprise AI stack that you heard Lan and Manish talk about plays such a critical role. Reindustrialization. Here in the U.S., everybody knows that's a huge priority, and supply chain resilience, as Tracy talked about, absolutely critical. AI infrastructure and energy. We're involved in both the build of the data centers as well as the energy infrastructure, and you heard from Rob about securing it with OT. Then cost and productivity transformation and cyber, of course. As you heard from Manish earlier, these are the exact areas that we're investing in to grow our core business and our network. While these themes might manifest differently across different industries, geographies, and clients, one thing is consistent. CEOs recognize that the combination of AI and new technology represents a once in a generation opportunity, which is putting them under enormous pressure to act. Well, John, these are the same trends. These trends are also very important across Europe, and I think particularly as our clients really struggle with long-standing challenges that we've been knowing for many years. Slower productivity growth, higher, let's say, energy cost, fragmented cost, fragmented markets, and slower adoption of technology such as cloud and AI. You remember the slide that Manish showed a few minutes ago about cloud, 72% of further potential. This is particularly true across Europe. So those pressures are creating a new urgency to invest, and I see this really every day. We see a big movement around modernization of Europe's infrastructure and industrial base, with energy becoming a critical topic and public services becoming more efficient. Talking about Europe, I like to draw your attention to three, let's say, major forces that are really shaping investments, and they are sovereignty, defense, and security. Allow me to start with sovereignty. This has become central to the strategy of many of our largest public and private sector clients. More than 60% of European organization today actively seek for sovereign AI solutions. This is because they're making fundamental choices and fundamental decision about where the data resides, how AI is going to be governed, which technologies they will use, and especially how they can have greater control over critical capabilities. It is clear that Europe's AI advantage will not come from outspending other markets, but it will come from putting its own strength to work, like its deep industrial data and expertise in regulated industries. They need the right data and the right partners who can help them navigate both global technological systems and European provider. That is why we are actively working across the full spectrum of our ecosystem. It was great, again, to see all these videos with all the leaders, and we work with their teams on a daily basis. We work with the hyperscalers, but we also work with the European native players, such as, for example, Mistral, and this is one of the new AI partnership that Julie mentioned early on. We really help clients to make choices, make decision, because they need to find the right balance between sovereignty, between resiliency, and global innovation, access to global innovation. This was sovereignty. The second force is defense. It is clear that Europe's military capabilities need to adapt to the current geopolitics. We see that there is an acceleration to close the gap to modernize the technology infrastructure and manufacturing. As defense spending increases, the focus is increasingly shifting from equipment alone to the technology, the data, and operational capabilities. This is also required for these players to deliver readiness and resilience. For Accenture, this creates a lot of opportunities across the entire value chain. Modernizing the digital infrastructure, securing critical systems, for example, transforming engineering and manufacturing operations, strengthening the supply chains, and helping defense organization to adopt AI responsibly at scale. After sovereignty and defense, the third topic is security. Security extend well beyond defense. Clearly, regulatory requirements, geopolitical tensions, and a growing number of cyber threats are now driving major investments in cyber resilience. This has create a lot of large opportunities for transformation. At the same time, we heard earlier on, protecting operational technology and critical infrastructure is becoming a top priority across all of the industries. John, the urgency to invest differ by markets, but I see Europe is focused on scaling AI responsibly. The Middle East, you see clients that are using it to leapfrog older technologies and diversify their economy. In all of our markets, this combination of traditional modernization and new technology adoption creates a very broad opportunity for Accenture. At the end, the underlying imperative is the same. Our clients need to reinvent, and they need help turning ambition into execution. That is where knowing the client really matters. You need to understand not just the technology, you need to understand the client strategy. You need to understand the industry in which it operates. I am glad that I saw in all the videos of ecosystem leaders talking about industry depth. We need to understand the core processes. We need to understand how the enterprise really operates on a day-by-day basis. This is going to be extremely important, and it is a great potential for us to develop in this context. John, does this resonates? It absolutely resonates with me, and it brings me to what I wanted to talk about next, which is how do we grow our client relationships, and how do they compound over time? As Julie Sweet said in her opening, 85% of our top 200 commercial clients have been clients of ours for 20 years or more. Our client model starts with our client account leads, and we believe our client account leads are the best in the business. These are senior leaders who live and breathe every day inside of our clients' businesses. They earn a seat at the table after years of successfully delivering results at those clients. That work builds trust and deep, deep knowledge of the company. Their job is to bring in the Reinvention Services capabilities that Manish Sharma talked about this morning, as well as our ecosystem partners, to really solve any business challenge that our clients have and to help them drive growth. You heard from Stéphane at Estée Lauder Companies this morning around how this works. Our client account leads, the first thing that they do is they actually start with our client's strategy. From there, they determine what needs to change. We use data-driven analysis with our clients to help them understand the costs and the benefits of different transformation opportunities so that our clients then can prioritize around what creates the most value. The second thing that we do is we really help modernize the technology and the data foundations underneath the business. This is something you heard Lan Guan talk about with the enterprise AI stack and what a critical role that plays in helping to do that. You have to recognize that when we engage with these large enterprises, we're generally dealing with decades of accumulated tech debt and process complexity. The stakes are particularly high. Rob Lee talked a little bit about it, but if you just think about it's mission-critical transactions in the infrastructure space, certainly, but financial transactions, healthcare records, personal information, often in regulated environments where reliability, security are absolutely essential. Moving pragmatically is not a sign of weakness or a lack of appetite on the part of these clients. It's really responsible leadership. Scaling AI to drive sustainable competitive advantage is absolutely possible in these environments, but there is no easy button to do it given the level of complexity. Once we've kind of looked at that, we then begin the process of redesigning the enterprise processes and operating models. Again, this is not easy work. It's complex, it's time-consuming, as the technology alone does not create the value. Organizations have to adopt the technology and then fundamentally change the way the work is performed to get the value. Then we work with our clients to deploy the changes at scale while helping their employees adopt the new ways of working. We do this through a combination of our consulting and managed services capabilities. Let me give you an example of how this works in practice at Dell, which is a client that I spend a lot of time with. As you might imagine, Dell has been a client and a partner of Accenture's for many years. But with the rise of AI, our relationship has become more strategic than ever. What makes Dell unique is that for us, they are three things at once. We call it a Dell 360 relationship. They are a key go-to-market partner. We work with them extensively in private and sovereign AI environments, as Mauro described. They are a critical supplier to Accenture, where their products actually power our business. And then finally, they are a key client, where we work with them to use these technologies to reinvent their own business. If I start with the reinventing, a few years ago, Dell launched an enterprise modernization program focused on increasing automation, intelligence, and speed across the enterprise. We started with a focused data transformation, consolidating fragmented data environments across the breadth of Dell into a unified data platform, which created the single source of truth. That foundation we put in place was critical, and it gave Dell the ability to run their business with real-time visibility into operations, supply chain, performance, customer demand, and ongoing decision-making, fundamentally changing the way they were able to run the business. That success built trust and opened the door to the next phase of reinvention, and today we are helping Dell scale AI across every part of the enterprise. At the same time as we were doing that, we also expanded our go-to-market relationship through the Accenture Dell Business Group. This is where we help governments and enterprises around the world deploy private and sovereign AI infrastructure in order to support their futures. The results speak for themselves. Over the last three years, our Dell 360 relationship has more than doubled on each of the three dimensions. Dell is not unique. Many of our strongest client relationships follow this same pattern, which is how our relationships compound over time. I think this is the key point about building client relationships, John, over time. That progression is important. It is very important because we understand what AI means for our business. It makes us more efficient and gives us a significant upside. In other words, those efficiencies create the capacity to do more. A client, and I see this every day, a client might start by asking us to take cost out. Take cost out of an existing operation. The savings then can help fund something that they wanted to do but could not afford in the past. For example, modernize another system, improve customer service, build a new capability. That is a big part of how we expect to grow in an AI-enabled world. Create productivity, reinvest with our clients, expand the relationship, and reinvent again. For example, we have seen this with one of our global life science clients I am an executive sponsor, proud executive sponsor of, where over more than 10 years, our presence has been consistent. That has allowed us to work across the entire enterprise. We started with a research and development program in the business unit. We created success, and success created trust. That enabled us to expand well beyond the original scope in other business units and in Europe, then worldwide. We have been with this client through many technology cycles. When GenAI emerged a few years ago, we decided to invest and bring it into our managed services, reviewing our contracts and our commitments, and share the value with the client. That has created further trust to expand across other parts of the organization. The productivity gains helped fund a broader multi-year reinvention across commercial operations, manufacturing, and R&D. Today, together, we are helping accelerate trials, reducing time to market for some of the most important and impactful medicines and therapies of our time, with beneficial outcomes for treatment and recovery. AI gave us efficiencies in how we serve the client, but it created even more opportunity for us to expand. This is what I think you see in many of our clients. Mauro, I think we have demonstrated that compounding model over decades. We now have over 317 diamond clients globally. These are our biggest relationships, and they are by no means transactional. The trust and depth of technical and functional understanding and our industry expertise is very difficult to replicate, which is why I have confidence that there is a lot of opportunity for us to continue to grow in our existing large enterprise clients. There is also significant amount of white space across the board. At the same time, emerging large enterprise and mid-market represent one of the largest growth opportunities that we see in Americas, and I think this is true globally. I agree that this is true globally. If I speak about Europe specifically, this company, these segments are the backbone of the economy, and they face many challenges, many of the same challenges as the larger enterprise, but with less access to capital and skills. Our ambition is to bring them solutions that are ready to deploy, faster to implement, and tailored to their needs. Our client strategy is simple. Combine our industry-led approach with our ecosystem-led model to scale repeatable solution and serve a much broader client base. I think for all these reason, we are really very well positioned to win. These are many of the consideration we share today that give us the strength and the confidence because we understand the client's environments, we understand the technology, and we are the bridge between the two. Okay. Now I will invite back Julie for a conversation with Simon Roberts, the Sainsbury's CEO, to bring to life our longstanding strategic partnership. Julie, to you. Thank you. Thank you. All right. Well, Simon is joining us live from London. This is when all the tech guys in the room are like, "Please make it work." Right. I am really excited to have Simon join us. I will just wait till he comes on camera. Hi, Simon. Hi. What is good? Thank you. Hello, Julie. I think I can hang up a little bit. Hi, Julie. Good to see you. All the technology's working good from here in London. That's good. Thank you. Good afternoon, everybody. Great. I am highly relieved. Yes. Simon and I actually became the CEO within a few months of each other. I have had the privilege of getting to personally sponsor our work at Sainsbury's from the beginning back in 2020. I have gotten to see what Simon has done up close which is pretty amazing. He has had a really huge impact, he and his team, a very clear strategy. They have moved at a very fast pace. We feel very privileged to be a part of Simon's strategy, and I personally feel really privileged because it has been just fantastic to work with Simon. Simon, thank you again for joining us. Because we do have a global audience, not everybody may know about Sainsbury's and your strategy. I thought we could just start there, and you can talk to us a little bit about what Sainsbury's is and the strategy you have been driving. Julie, thank you, and really great to be joining you this afternoon. Look, thanks for the introduction. Just a headline. Sainsbury's is the second in the market here in the U.K. in grocery. We have been serving customers actually since 1869, and obviously we work in a very intensely competitive industry, just as the same across the world in grocery and food retailing. We have been really focused on how we make sure we deliver for our customers a really differentiated experience. To do that, to what we were just hearing, making sure we create the efficiencies and the capacity, as Mauro was just saying and I was hearing, to actually be able to achieve more. We've got a plan really to make sure that we deliver for customers more reasons to shop with Sainsbury's, and putting food first in our business is absolutely front and center. Making sure we're creating the technology roadmap to really drive the change we need, and that's what we call our Save and Invest to Win plan. Then putting personalization and what we call Nectar, which we'll come back to, Julie, right at the heart of how we connect with customers. We're about six years into our turnaround plan now. Look, we've made some progress, but I'm sure, as everyone in the room will be reflecting today, there's just so much more opportunity as we look ahead. That's, I think, really all about this conversation, which is how we partner together to find the solutions to really unlock that value. Well, thanks, Simon. One of the things that's been so important is that our partnership began in one place and then has grown as your strategy has grown and evolved. Maybe you can talk a little bit about the scope of our partnership and the role we've played as you've evolved your strategy and moved from one success to the next success as you've driven this change. Julie, look, it's such an important point. I think just picking up on the previous conversation I was listening into, I think this has absolutely been a really clear example of our strategy and our relationship with Accenture working hand in hand. We've worked, haven't we, from a services support partner to now a real enabler of business transformation, and that's what I feel really excited about. We've really shifted up the way our teams are working together. We've become much more about trust, transparency, partnership, much less transactional, and we've got, I think, real alignment on the strategic outcomes we are looking to achieve. We're just coming to the end of our current three-year plan, which has been all about putting food front and center in our business. We're now imagining the next three to five years. I just see that partnership mindset, really thinking about how our teams are coming together to imagine the possibilities and the value, really stepping up. I think it's not just about cost, right? I think the big theme that we certainly feel in our business in the way we're working, it's about building capabilities and building that continuous improvement. More and more our teams are talking about how Accenture are helping us unlock that so we can build that capacity, we can build that new vanguard of capability, and that's giving us real confidence as we look ahead. Simon, we started with managed services. We started building- Yeah your technology backbone. We expanded the different functions that we were doing managed services, and now super exciting in our next extension of our partnership, what we are going to be doing in AI and helping you use it to drive growth. Maybe just talk a little bit about the business outcomes that we have delivered together, because it is together. This is a real team. Just to get a flavor of what we have already done, and then we will talk about where we are going. Yeah. Super clear, Julie. Look, I think if I reflect on our partnership and how we work together, I really think about the pyramid, right? Which is we are really leaning in with each other kind of 45 degrees to understand the shared outcomes that we want to achieve. That means from our business and our teams, we have got to be really open and clear with your teams about what it is we need to achieve. Also, let us be honest, facing into the change we need to accelerate. When I think about the outcomes, there are many that have just improved the way the business works today. We employ 140,000 colleagues right across Sainsbury's here in the U.K., and the work we have been doing in some of our HR self-service, for example, has just unleashed a totally new efficiency and friction-free environment for our people. We are working right now on a complete replatform of our core commercial capabilities in the business. It is right at the heart of a grocery business. How does the commercial function work? It is the work the teams have been doing to really deliver that big ERP change. It is just coming through really strongly. Then as I think about how we are looking at the way grocery stores have been working, need to work, need to accelerate the change that is happening in there, it is just a really joined-up mindset about what is it to deliver a really differentiated customer experience? What is it to create more capacity in our operating model? How do we need to rewrite our processes such that we can become the first choice of food here in the U.K.? And look, just to everyone there in New York, we feel pretty ambitious and pretty excited actually about what we can do. We think we've come quite a long way over the last period of time. But as we all know, there's just such an imperative to accelerate the pace of change and to make sure we take our colleagues and our customers with us as we do that. So, right at the heart of this partnership, as I say, it's about becoming more efficient, but it's about unlocking that capacity, that capability, that confidence to really drive forward. And Simon, part of what we've been able to do is use AI to actually give you more productivity and more efficiency, which you're then reinvesting in the business. And we're excited that we've just extended our partnership to 2033. Is there anything Yeah specifically that you're most excited in what we're going to do in this next chapter? Then I'll get to our last question. Yeah, no, Julie, it's such a good question. And look, I'm really conscious because we're going to be updating our kind of investor audience in a couple of weeks' time. So I'll talk a little bit about some of the things that we're working on, but also, just to kind of really sort of reflect the fact that this is a very focused program on this year, the next couple of years, but honestly, the next decade. And we're feeling very engaged in the long-term partnership that we've built together. Because when we think about, as I say, customer experience in this industry, customers are going to be expecting businesses like the one I'm part of to really change and adapt more quickly as people want to shop differently. They want to engage in the physical experience in store differently. They want to be able to shop online and on-demand more quickly. They want different recommendations of the kind of food products they want to buy. We are really thinking about how we are going to get in front of that curve and giving ultimately our customers more reasons to shop with Sainsbury's. What is this all about in the end? It is about creating competitive points of difference that we can stand really apart in what is a very competitive industry. The work we are doing together, and we have now started to map out for the next kind of three, five, and 10 years, I think, is going to really face into how does AI unlock not just efficiency and cost, but in my mind, a real gear shift in the customer experience. That is what I feel together we are really excited about, right? Because this is about improving the way we serve millions of customers every day. In an industry, we are serving 20, 25 million customers a week. It is a lot of people to have a more positive impact on than we can with today's capabilities. When we look ahead, the kind of thought leadership, the capacity we are building in our partnership, and the way we are starting to imagine that. I would just pull up actually, Julie, on we had a fantastic experience in India at the midway point of last year when I just felt the whole ambition of what we could do together really step up. It was one of those shared experiences when you are kind of staring at the opportunity, but you are also facing into the challenges that are out there in the market and really working out together how you are going to unlock that. That is why, as we both know together with our teams, we have committed to this partnership because we really want to become the first choice of food here in the U.K. with our customers, and this is going to really underpin that. Well, great. Maybe just as a final wrap-up, in your words, why have you chosen Accenture for all these years? Yeah. Well, look, I think right at the heart of this conversation, and we have discussed this many times over, is about trust, isn't it? It is about trust and commitment and credibility to drive powerful change. When I think about a retail business, retail businesses across the world, they involve. There are thousands of decisions every day that affect customers and stores and colleagues and range and promotions and pricing and the way our supply chains work. At the heart of this, we are very excited to partner with you to create the next generation of how the retail operating model, the grocery operating model is going to work, and to unlock those solutions together, powered by technology. We look at this opportunity as a challenging one, but one we are really engaged with because you can see the flywheel effect, which is we create the capabilities, we create the capacity. That means we can invest in a way that drives the returns our shareholders expect, and that in of itself creates the competitive advantage that is so at the core of winning in this industry and ultimately of serving customers every day. So, that trusted partnership, Julie, thank you for all that has happened to get us to this point, and we are really excited as we take it forward into the next exciting chapter. Well, Simon, thank you for allowing us to be part of this journey. We feel really grateful and appreciative. Thanks for joining us from London, and I look forward to seeing you in London soon. Thank you. Take care. See you soon, Julie. Thanks, everybody. So as they're bringing on another chair, I'm going to be joined by our Chief Leadership and Human Resources Officer. One of the things I hope that you've noticed is that every one of the leaders you're hearing from is working directly with clients. This is such an important part of our model. We stay on top of trends. We're close to our clients from the very top to the very bottom because clients are at the center of everything we do, and the only way to serve clients in that way is in fact to be at clients. It's an exciting part of our model. Our leaders at Accenture get the most energy when they're together with their clients. So Kate, can you please come join us? Kate might say she has the best job at Accenture because she gets to work with our people. You've heard a lot about our people from our various clients and our great talent. I'm going to start with the number one question I get, which is: Why do you have still so many people in the age of AI? So Kate, over to you. Oh, well, thanks, Julie. The question I get is, you have so many people, and are you going to continue to grow our headcount? As you already have 800,000 amazing Reinventors across the world. The answer is yes. I do expect that we're going to continue to grow our headcount. You heard from Manish, and I think he even bookended with, "We're going to double our TAM," or, "We have doubled our TAM." With that incredible growth, we will need incredible people. My job is to ensure that we are always fulfilling our client demand, that we have the right talent at the right time to meet that demand. I really think about it in three ways. First is our core. We will continue to add in our core, and that includes entry-level talent. We will also continue to add talent in our new businesses. You heard from Rob, you heard from Mark, Accenture Construct with Tracy. Those are brand-new businesses, brand-new jobs, and we will add talent to fulfill that incredible double-digit demand. Then finally, as we acquire new companies, we'll bring on that talent as well. But we will continue to manage our supply and demand with the rigor that we have. You talked about in your opening 93% utilization in Q4, and we've been running in the low 90s for the last 23 quarters, and we will continue that same rigor over our future. Now, I do expect that we'll slow the pace of bringing in talent a bit, but we will always have the talent that we need to fulfill our demand. Let's talk a little bit about the new jobs that are being created, both the jobs in the new businesses. You've talked about Tracy, but how about the new jobs in the core business and how we're preparing people for those jobs? Yeah. It's a great question because I do also believe, in addition to bringing on the talent to fulfill our clients' need, my job is to create the workforce of the future. I was reading something from the WEF a while back that said that there's going to be 170 million new roles in the next five years due to AI. Don't worry, I'm not creating 170 million new roles. But we are going to systematically change our jobs. We are re-architecting the jobs for everyone who works at Accenture, and it's really anchored in four key skills. It starts with data and AI. We expect every single one of our Reinventors to have a data and AI foundation. Industry skills, and that's the industries of our clients. So whether it's banking or retail or life sciences, the industry of our clients. Functional skills, so whether that's HR or finance, sales, marketing, they deeply need to understand the functional work they're doing for our clients. And then finally, our technology ecosystem. We're architecting new jobs with those four skills as the foundation. Now, the depth of the skill will change based on the work that our people do every day, but our competitive advantage is that people will have skills across all four. We have a long history of investing in learning. You've talked about it before. We invest $1 billion in learning. How we spend that money changes. We change and evolve where we spend those dollars. For example, we've spent a lot of time talking today about ecosystem partners. We have over 134,000 unique certifications across our AI and data ecosystem partners. And one of our aspirations is to be really seen as the elite university among corporates because the skills are changing so much that we have to really keep up with them. How do you think about how we're doing the skilling and how you're taking the skilling and then creating these new jobs? Maybe give an example of really how we've gone from new job to skilling and what that looks like. Yeah. I am happy to, and again, I think about it two ways. There is brand new jobs, I will talk about an example of that, and then we also have jobs that are not brand new, like we have had them for a while, but they are really changing. An example of a brand new job, and you heard it in some of the videos this morning, is this forward deployed engineer, this FDE. 18 months ago we did not have any FDEs at Accenture. It is a brand new job not only for us, but it is a brand new job in the market. That job is, I think about it is the intersection of a software engineer, a solution architect, a product manager, and a consultant all wrapped up into one who is solving real client problems to drive business outcomes. Again, a brand new job. Whenever we have a new job, I always go out and scan the market. Okay, we have got this new work. How am I going to go hire for this brand new talent? When I went out and scanned the market, I saw there was not that many people who had this skill set. I think it was roughly 2,000 across the market that had this skill. So we knew we had to build it. To your point, how did we build these skills? We partnered really closely with Lan and with Marc, who you heard from earlier, to build a 14-week program that takes a software engineer and makes them into or upskills them to become a forward deployed engineer. In that 14 weeks, it is not just training, it is real practical application of those skills in a client environment. It is hackathons, and it culminates in a certification. So we do not call someone a forward deployed engineer unless they have a certification in one of our AI and data partners. So that is a brand new job. Another example is just jobs that are changing. You heard from Tracey earlier, she talked about supply chain and engineering, and I think about a supply chain process consultant. A supply chain process consultant used to spend time process mapping, and they were really deep in the function, but that was really where it stopped. So we are now focused on upskilling those process people to understand robotics, to understand physical AI. Work that they have not had to do before because it is not just about mapping out the process, it is really re-architecting the work. Now, we are very proud that we are number 4 on the Great Place to Work global ranking, which is cross-industry. Can you talk a little bit about why it is so important and why we look at that metric? Yeah. I am also very proud, and one of the reasons I am very proud is because that is directly from the voice of all of our people. That is not something we can apply for. That comes in feedback from our global Reinventors, and we hear the things that they love about working here and the things that we need to work on, and we welcome both of those things so that we can continue to take action to be the number four and even better than number four. The reason that we should care about it is really two things. One, it drives real outcomes. Engaged teams drive higher profitability. Engaged teams are better with clients, and our clients tell us this through their NPS scores. We see client scores come in eight points higher with engaged teams. Leaders are two times less likely to leave if they are engaged. If they are engaged, they are engaging their teams. There are real outcomes that matter when it comes to engagement. Second, I talked about being out in the market and attracting new talent. As I am talking to candidates, whether they are very senior or junior, they often proactively bring this up to me. I say, "Why did you pick up the phone? Accenture called, why did you pick up the phone?" They will say, "I want to work at a Great Place to Work. I want to work in your culture. Well, now it is not a competition, but there is a little bit of competition at Accenture for who gets the resources to embed AI first. As you can imagine, with over 800,000 people, our talent supply chain, there is a lot of value. You have been one of the leaders in using AI to deliver business outcomes for Accenture. As a final question, why do not we just wrap up with a little bit about how we are our own best credential and you are leading the way. Well, thank you for that. We are our own best credential. What we are out doing with our clients, we have to experience ourselves, and oftentimes we are architecting it with our practitioners together. Julie is referring to what we have done in recruiting, where we have changed, we call it frictionless recruiting, which is really our agentic recruiting solution. It started from a place of we knew our recruiters needed to spend time with candidates, they needed to spend time sourcing, but where they were actually spending their time was scheduling interviews. Where they were actually spending their time was typing information into a system. We put in an agentic recruiting solution where agents now do all the interview scheduling. Agents can screen a resume. We have assessments that deeply understand the skills of the candidates to help that process move much faster. Now, a human always makes a hiring decision. A hiring manager always makes a hiring decision. But the agentic process has allowed us to reduce our time to fill by 28% and improve candidate quality by 30%. Now, those are real outcomes. It allows our recruiters to spend more time outsourcing. It allows them to spend more time helping candidates navigate this process. It has allowed us to increase our time to productivity. It used to take six months for an entry-level hire to become productive. Now it is six weeks, which is five more months revenue for you, Julie. Yes. Well, thank you, Kate. We are very fortunate to have you leading our leadership and HR function. We could spend a lot more time on this, but I know that people are anxious to have a break and to have lunch. Thank you for joining us today. We are now going to take a lunch break. At the back of your name tag, you will have an assigned table. Please be back in your seats at 1:00, and if you just go out the doors, there will be people to tell you where to go, but it is basically where you registered and the room next to it. Thanks so much. We will see you during lunch. Take care. Are you ready? Okay, great. All right. We are one set of ecosystem partners away from the main event, which is our Chief Financial Officer. We know that. We know that you really want to hear from her. But I am excited to share our last set of ecosystem partners that have joined us today. Let us roll the video, and then Angie will take it from there, and then we will have Q&A. The gap between where the AI model capabilities are and where organizations are today with AI has never been bigger. Why is that? Well, we believe at Databricks that the reason for this is that data and processes are tucked away and siloed over the last 20 years in many different systems, on-premise and in separate databases and in people's heads. If we could just get all of that and provide it as a context to the AI, the AI is plenty smart to solve those problems. That is why we built what we call Genie Ontology. It is an ontology layer that does this. But how can we get these organizations to actually succeed by getting all that data and give it to the agents? We need two things for that. One is you need a great partner, a global professional services partner that can come in and help actually look at all those processes, unlock all that data that is siloed away in these different systems, and get them into our ontology layer so we can feed it to these agents. Second, you need great technology, and at Databricks, we hope that our ontology layer is the secret sauce that actually unlocks that data. You need both of these things. That is why Accenture is an extremely important partner for us. 8 years now in a row, they have been selected Global Partner of the Year for us. That is why in March, Accenture launched the Databricks Business Group, and we have actually together combined trained 12,000 certified professionals inside Accenture who understand how to go through all these siloed systems and how to actually change the processes and actually gather all that context and feed it to the agents. That way, Accenture and Databricks can together get actually agents into production at these different enterprises. We can actually finally bridge this gap between the capabilities that the AI has and the actual what is happening on the ground at these companies, instead of just doing more and more POCs together. That is why Accenture is extremely important partner for us, and we are looking forward to partnering deeper over the next decade together. Accenture has been a strategic partner to Dell for more than a decade. With the formation of a dedicated Accenture Dell Business Group, our relationship gets even more focused. The demand that we are seeing today for private AI, sovereign AI, and neoclouds require full stack delivery, infrastructure, data, and AI agents designed and deployed together. We have delivered 6,500 AI factories in the enterprise, but the vast majority of customers really have not yet started. They need help with their business processes, with simplification, streamlining, and automation. Accenture is scaling and partnering with us to meet that need. They are helping clients move from AI interest to adoption, combining strategy, technology, and execution to deliver measurable results. Together, we are advancing enterprise customers on the Dell AI Factory with Nvidia, anchoring next-generation AI data center build-outs across the globe. It is my pleasure to recognize Accenture today, and the role our partnership plays in helping enterprises turn AI ambition into real business results and shape the future of the agentic enterprise. Accenture is the largest global systems integrator in the Snowflake ecosystem. They are also our Global Partner of the Year for Healthcare and Life Sciences Services, and the inaugural catalyst partner for CoCo, our cutting-edge AI coding agent. All in, Accenture now has more than 5,000 Snowflake certifications and a community of more than 10,000 AI practitioners. This impact is significant as our joint customers continue to sharpen their focus on how to apply AI to the hardest problems in their businesses and do so securely, responsibly, and at scale. Accenture brings together critical industry expertise, business process knowledge, and change leadership experience that enables enterprises to effectively move from pilot to production. It is this partnership that is enabling us to transform enterprise functions across supply chain, customer experience, clinical outcomes, and financial performance, and accelerate business impact. Accenture has built the skills, workflows, and governance to accelerate its own outcomes and bring those learnings directly to their clients so they can adopt AI with confidence. Snowflake brings together trusted data, enterprise governance, broad model choice, and an open partner ecosystem that directly complements Accenture's industry expertise and ability to reinvent companies. That is what this partnership represents. Moving AI from experimentation to measurable enterprise outcomes and defining what it means to be an agentic enterprise. We are proud to build that future together with Accenture. We are very honored and happy to be working with Accenture. Its international reach and its depth in the industry make it an ideal partner for us. We have strong industrial synergies because both of us are driving impact across financial services, across manufacturing, and across the energy sector, for instance. In all of these sectors, we see a growing demand for open-weight technology and for sovereign AI, as defined as AI systems that can be deployed very close to the most critical data of our customers, that can guarantee business continuity, that can guarantee affordability as well, and that can make our customers comfortable with using their IP and turning it into AI assets. With Accenture's reach and with its depth with those partners, we can continue to drive AI transformations for those industry, for those enterprises at scale. Both Accenture and Mistral are very well-positioned to address the sovereign AI demand, which we believe at Mistral to be driving most of the demand in the years to come when it comes to delivering value with artificial intelligence. Accenture is critical for the client adoption of AI. Together, our job is to help transform businesses and to help them transform their processes, their core processes, to go beyond the individual productivity that a conversational interface can bring. As a customer of Mistral, Accenture has invested in building a dedicated Mistral instance, and it has built a Mistral AI Studio that is embedding Mistral's technology into Accenture's operations so that they support client solutions. In February, we have announced a multi-year strategic collaboration designed to really help the organizations that we care about to rapidly move to secure and large-scale AI deployments. Accenture is therefore equipping its professionals with Mistral's models and products. We are very happy for this partnership to have started. We are really looking forward to scaling it further. Hi, everyone. Angie Park, CFO of Accenture. We are going to bring it home. Ready? It is a good day. All right. You have heard today about our strategy, where the growth is coming from, and how we have positioned Accenture for sustained long-term growth. My job is to show you the financial blueprint. I will walk you through three things today. What we have delivered. Second, where we are going. Third, how are we going to get there? Let me start with what we have delivered. In FY 2026, we achieved or exceeded every measure of our guidance that we provided at the beginning of the year. Revenue was $74.2 billion, up 5% in local currency, adding $4.5 billion of incremental revenue. Our adjusted operating margin expanded 20 basis points. Our EPS grew 8% to $13.97. Free cash flow was $11.6 billion, a 1.4 free cash flow to net income ratio. We returned $11.5 billion of cash to shareholders. At the same time, we deployed $4.9 billion across 17 acquisitions. We invested over $3 billion in operating investments, R&D, learning, and acquisition-related costs. Taking a step back, over the last four years, you heard Julie mention we added $12.6 billion of revenue. We expanded our operating margin 60 basis points. Our adjusted EPS grew at a 7% CAGR. We invested $13 billion in our business. We deployed approximately $19 billion in acquisitions, which includes the capital related to the cyber OT transactions that we closed in September. We returned $35 billion of cash to our shareholders. We grew the business, we expanded margins, we invested at scale, and we returned significant capital to our shareholders. This is the financial model that we have successfully executed over and over again. Turning to where we are going. As Julie mentioned, we have three financial ambitions. First is growth. Our ambition is to deliver at least mid-single-digit constant currency revenue growth in FY 2027 and in FY 2028, and to step up our growth trajectory to mid to high single digits beginning in FY 2029. Remember, this ambition takes into account that we will be absorbing AI efficiencies while delivering that growth. At the midpoint of the range for FY 2027, our implied organic constant currency growth is approximately 2%-2.5%. At the top end of the range, it is 3.5%-4%. Second, sustainable margin expansion. We expect to expand our operating margin 10 to 30 basis points per year in 2027, 2028, and in 2029, while absorbing significant investments in our business and our people. Over this time period, we will use our efficiencies from AI-enabled productivity in three ways, passing value to clients, reinvesting the majority of what we retain into growth, and continuing to expand operating margin every year. We believe that that is the right balance for long-term shareholder value creation. Third, disciplined capital allocation. Our business consistently generates strong cash flow. This matters because it gives us the ability to significantly invest in our business and our people, both organically and inorganically, and return cash to shareholders. So through FY 2029, what we expect to do is to maintain a free cash flow to net income ratio of at least 1.1, grow our dividend with a payout ratio in the mid to high 40s as a percentage of prior year net income. We are going to repurchase more shares than we issue, and of course, we will invest in our business organically and through acquisitions that are ultimately to fuel organic growth. Let us now talk about the financial model that gets us there. So our financial model has three components. You know it, revenue growth, margin expansion, disciplined investment and capital allocation. Let us start with revenue growth. So you have heard today how our strategy positions us to capture the significant opportunities that we see ahead and our path for stepping up growth in FY 2029. I do want to highlight one strength as you think about our financial resilience over decades. We have a broad and diverse business. We operate at scale across three geographic markets and in 13 industries, and we have a balanced business across consulting and managed services. You heard today about our new growth model, seven Reinvention Partners, our new network of businesses, and the expansion into the mid-market, all strategic moves that both position us for more growth and strengthen our base. This diversity has allowed us to perform through different market cycles and gives us the confidence in our long-term growth ambition. The next component is our financial model, and is margin expansion. So our model is designed to do two things, create investment capacity and expand margins at the same time. Four levers, four things that we look at. First, pricing and contract profitability. We define pricing as the contract profitability or the margin on the work that we sell. Our focus is to maintain and improve pricing, and it can fluctuate based upon several factors, the competitive intensity, the mix of work that we sell, and the size of our deals. Our FY 2027 operating margin expansion, it reflects continued competitive intensity, and we work to maintain attractive contract economics. Second, how we deliver. So of course, AI is making our delivery model more productive. In FY 2026, our revenue per person increased approximately 5%, which was in part due to the efficiencies in how we deliver our services. We measure this on a rolling four-quarter basis with revenue adjusted for FX using our average quarterly headcount, and it excludes some subcontractors whose contribution has been consistent. As Kate mentioned earlier, we do not expect to grow our revenue headcount at the same pace as we have historically. And our goal is for revenue per person to improve again in FY 2027, growing our revenue faster than our headcount. Third, how we run Accenture. So over the last four years, we have reduced the cost of our corporate functions as a percentage of revenue by more than 200 basis points, and we have reinvested those savings. We will continue to deploy AI across our enterprise, reducing costs so that we can reinvest in the business. So let me give you an example. Contract to cash. This process spans legal, sales, and finance, and it touches 9,000 clients, 60,000 contracts, 900,000 invoices. We are reinventing this process end-to-end using an agentic solution, from contract review to sales bookings to billings and ultimately to collections. We expect it is going to create significant value over time, including freeing up capacity. The financial point is simple. Productivity creates capacity funds growth. Fourth, supply and demand management. Julie and Kate talked about this earlier today, 93% utilization rates. It creates operating leverage. We are deploying advanced AI and reinventing processes to both better match our skills and capacity with demand, and to shorten recruiting times. Together, these four levers, they create the capacity to invest in our business and expand margins. Let me turn to the last component of our financial model, which is disciplined capital allocation. As you know, it begins with strong cash flow. For FY27, we expect our free cash flow of about $11 billion-$11.8 billion, representing a free cash flow to net income of 1.2 to 1.3. We expect to return $9.5 billion to our shareholders, which represents 75% of our operating cash flow. This includes a 5% increase in our dividend per share and $5.5 billion in share repurchases. We do expect that this will reduce our weighted average share count by approximately 3%, which is a meaningful driver of our EPS growth. We are evolving our mix towards share repurchases because they support EPS and they give us more flexibility in the context of the current valuation environment. We will also continue to operate within clear balance sheet guardrails. We intend to maintain strong investment-grade credit ratings and gross leverage below 2x. In addition to the roughly $3 billion for our cyber OT acquisitions, we do expect to deploy an additional $5 billion in acquisitions in FY27. At that level, we expect gross leverage to be about one turn, well within our guardrails. As always, if we see the opportunities to do more, we can. Our strong cash flow supports both parts of our capital allocation strategy: returning cash to shareholders and investing in future growth. I want to spend a moment on the second piece because acquisitions are an important part of accelerating our strategy. As Julie mentioned earlier, we do acquisitions for three reasons. Many of you know this: to scale in high-growth areas, to deepen our industry and functional expertise, and to expand into new growth areas. Our acquisition strategy is ultimately to fuel organic growth. We use our strong balance sheet and our acquisition experience as competitive advantages to accelerate our strategy. Because of our strong cash flow and our strong balance sheet, we can flex it up and we can flex it down based upon what we see. We apply consistent financial discipline against the targets that we evaluate. We recognize that different types of acquisitions can have different return profiles. For acquisitions that extend our core services capabilities, we require returns meaningfully above our cost of capital and a path to accretion over a relatively near term horizon. For investments that expand our addressable market into higher growth areas, which could be products, platforms, or solutions, the growth opportunity is higher, the return threshold, investment horizon can be longer. Where we pay a higher valuation, we expect a higher return over time. Our track record supports that discipline. Our current acquisition portfolio over the last three years is generating returns of more than 2 times our cost of capital. The discipline continues after the deals close. For the first three years, our capital committee reviews acquisitions semi-annually against the original business case, including both financial performance and talent retention. We apply this same discipline across our business, exiting businesses, offerings, countries, contracts that no longer meet our strategic or return thresholds. How are we tracking our progress, and how should you measure whether the strategy that you've heard today is working? Of course, we will measure ourselves against the financial ambitions that we've outlined today. In addition, I want to share some of the other key metrics that we're tracking as key indicators of our progress against our long-term growth ambition. We look at the number of clients with quarterly bookings over $100 million and the creation of new Diamond clients. These metrics reflect the depth and durability of our trusted relationships and our ability to grow with the largest organizations in the world. We also look at the performance of our key 18 ecosystem partners. This is a direct measure of the technology and AI leadership and our ability to capture growth with our ecosystems. Market share gains. Clearest indicator of our competitiveness and whether or not we're winning in the marketplace. Finally, our Great Place to Work ranking. Shout out, Kate. Our people remain fundamental to our success, and attracting and retaining top talent is a critical competitive advantage. Our goal is to remain in the top 5 globally, and today you heard we're number 4. There is one additional metric that I want to highlight because it reflects how our business model is evolving. Revenue per person, which we expect to increase over time. As AI creates productivity and our business mix continues to evolve, this is the metric where you will be able to see how we are creating even more value and increasingly decoupling revenue growth from headcount growth. It is one of the clearest indicators of how AI is changing our business and strengthening the scalability of our business. To wrap up, our financial model is designed to compound. The productivity we are driving is creating that investment capacity. As we invest, it's going to create new growth opportunities, and our strong cash flow and balance sheet allow us to invest and return cash to shareholders. We have demonstrated this model, and we will continue scaling it. This is what gives me confidence in what we've laid out today, and our commitment to you is that we will continue to create shareholder value. Thank you. Okay. I think now I'd like to invite, I think Julie, Manish, John, Mauro, and Alexia are going to join me on stage. Just give us a second while we get organized. Good afternoon. We are excited for 30 minutes of questions and answers here. Angie just told you who is on stage, but it is Julie, Mauro, Manish, John, Angie, and Alexia Quadrani, the Head of Investor Relations. I am going to call on you guys. Just raise your hand. Please wait for the mic to come over to you. Then if you do not mind just stating your name and your firm, that would just be helpful to us. Yeah, and just our other leaders are also in the room, so if you do have a question for someone else who was on a panel, please just let us know, and they have got a mic, and they will be able to answer as well. All right, great. Tinjun? Mic? Oh, thanks. Like an ice cream cone. Okay. Good day. Thank you for hosting. My question, Tinjun Huang from JPMorgan. I am just thinking, what is giving you all the confidence to go ahead and issue this to your outlook that is a little uncharacteristic of Accenture, but it does speak to the confidence in the business? What are the building blocks, do you think, to ultimately get to that acceleration in 2029? I have gotten some questions around just absorbing the AI efficiencies. That is a pretty common question I know in the sector, but can you maybe just give us a mental model of how that might play into the outlook and how you see it? Thanks. Sure. Why don't I take that, Alexia? I also got the same question. We wouldn't have given this guidance probably a year ago, and the reason for that is that we've been building this foundation, and as part of building the foundation, we've been doing more and more work with our clients. Our confidence comes really from three things. First, we are the leader in implementing AI, and over the last few years, we've started to see our clients be able to take them from pilot to production, and we have a much better view of both what that takes and what that pace is going to be. That's why we have such a clear view of how we're going to grow, and that visibility has come from both doing the projects, but also that we've been doing them long enough that we have enough examples to feel confident about how we're seeing that develop. The second is that we've also been testing our view of how we absorb efficiencies, and so we've been absorbing them in our business from day one, and so we have more confidence in what that's looking like. We see two places that we're absorbing efficiencies in how we deliver as well as the software we implement, and it has more and more AI. It does impact the amount of our efficiencies. At the same time, I just take you back to the beginning, our strategy is to put more AI into all of our delivery. We have to work through some of our existing contracts, but the way that we will win is by helping our clients have more efficiencies that they can reinvest for the enormous agenda they have ahead of them. Remember, we said that only 5% of organizations have the enterprise AI stack that would even allow them to have AI be repeatable. There's a lot of investment that has to happen, and so we build relationships by using the latest technologies, delivering efficiencies, and being the partner that has the breadth and the talent to be able to help them achieve their ambitions. In addition to that, we have been very quietly going after the new markets that we've seen. The network that we've built, which is now 6% of Accenture, also gives us a lot of confidence as we see our long-term growth. We have a clear strategy around how to grow the core. We have a lot of visibility into what our clients need, and we've now built a network that we can scale that also gives us confidence. Those are the building blocks that really allow us to feel comfortable laying out an ambition for the next three years. Jamie. Thank you. It is Jamie Friedman at Susquehanna. Great day today. Thanks for the additional disclosures, the detail, the thought process. This may be somewhat mundane, but I had an investor relations-related question. When I look at the KPIs that you have had over the years, okay? You had the strategic priorities, and you had that for many years, and then you reduced that disclosure. Prior to that under Pierre, you had the old and the new. It was pretty straightforward. You are introducing the revenue per headcount. I appreciate that. How do we measure how you are doing on the six and the 94 going forward? Great. Angie? Yeah. I think that we laid out today how we see the next few years. The measures that I gave you relative to the metrics that we are going to be looking at, it will include, of course, how we are on our way to doubling that over the next three years. That is our ambition. We would expect that to be an annual disclosure because, as you can imagine, these things are going to fluctuate up and down over a quarter. You should anchor it on our annual guidance. All right. Let's go to this side of the room over here. Say your name and company. Thank you, Stefan Slowinski from BNP Paribas. Thank you so much for doing this today. Really helpful and clearly see the opportunity that is ahead of you working with your customers to implement AI. Just wondering around the free cash flow implications of that. When we think about a move towards outcome-based pricing and the investment in the network of businesses, is there any change in your free cash flow conversion? I see the 2029 outlook has, I think, 1.1 for the net income to free cash flow. That is below the 1.2 to 1.3 you have guided for this year. Just wondering if that is just a cautious kind of look a couple of years out, or if there is anything changing in the business model that will impact the free cash flow conversion. Thank you. Angie? Okay. Hi, Stefan. For us, we think that a 1.1 free cash flow to net income is quite excellent. Really, we know what 2027 looks like. The level of investments, et cetera, that we make will fluctuate depending on what we see and where we believe we need to invest. But at a minimum, we look to deliver at least 1.1, and so nothing to read into that of like, ooh, is something changing here? It is more about we believe 1.1 is super strong and that is our ambition, and we will see how things flow from there. Great. Right here. Please say your name. Yeah. Hi, it is Bryan Keane at Citi. Thanks for doing this. Great day. I just want to ask about the AI efficiencies. I guess the fear in investors' minds is that as AI advancement continues, those efficiencies will get greater. How do you get comfortable that you are not going to have to give further efficiencies? Then kind of attached to that is thinking about competitive nature of the business. I guess another worry is that competitors will come with AI-led to price more aggressively than maybe Accenture has to try to win some business. They are kind of related, but how do you think about those two things? Sure. Why do not we first hear from Manish and he can give you a little color about what actually happens on the ground, then I will have one of our market CEOs talk a little bit as well. I think the stuff around efficiencies has been a topic for discussion for probably more than three decades, right? Because when we did offshoring, we did RPA and some of the other waves that we had. We always had this question coming up. I would say that there are two things on this. One is that every time something gets with lower cost, with faster, the demand always increases. It comes back to a very old and a boring paradox, which is the Jevons paradox, which was there, but it has been proven, and we kind of typically disregard that piece. But I have always seen, as I said, I have lived through these three waves, and I have always seen the demand kind of goes up. That is point one. Second point is, typically what happens is if the clients have 100 units of work, in 2001, they were giving us five units of work out of what they had. In 2010, they were giving us 20 parts. In 2021, they were giving us 25, and now we are seeing they are giving us increased amount of work because it has become cheaper and with lower cost. That is kind of the second point. The third point I think which we are seeing is just the emergence of the new services, which is kind of super exciting, right? We did not have AI-managed services. We did not have data-managed services. We did not have, you heard today, the OT-managed services. We did not have any of this. You are seeing new kind of services emerging in the AI era, which we were not even looking at earlier. We talked about the growth arenas earlier, but look at agentic commerce. Nobody talked about agentic commerce on this front. That is just the third point. The last point I will just say is As AI has come, I know we all love AI and the deployment of AI. Any organization before they deploy AI, the tech that they have, we talk about tech debt, which is the digital core in the enterprise AI stack. The process debt is much larger than even the tech debt, which it is very uncool, and nobody wants to focus on that. Then you have got the data debt because you got to get the data organized, and that is why the data managed services and the architecture. Then you have got the operating model and access to talent. These five things they continue to kind of ensure that there is so much work to be done post which you can deploy AI, actually. So that is just a bit of this thing, those four points. That was a very complete answer, so I will not have John and Mauro add to it. I will add one thing, however, which is you did ask about the AI-led, and that is actually what we are doing today. You heard every one of the clients talk about how we are using AI and embedding it. Manish talked about reinvention.ai, which is our proprietary platform that we are using to help lead. Because a lot of the reason why in managed services, for example, clients are turning to us is they do not want to build the platform that has the agents and all of that. We are already selling with an AI-first lens. You have to do that to compete now. Great. I think that is Jason back there. That is me. Jason Kupferberg from Wells Fargo. Thank you for everything today. I just had a two-part question about the 2028 and 2029 outlook. If we think about this current fiscal year, we are expecting about 2 to 2.5 points from M&A. Is that the right proxy to think about for the next couple of years? Then just if you can hone in on fiscal 2029 a little bit more, the acceleration you are obviously pointing to, assuming that that is organic, what is driving that? What is the most likely scenario for that acceleration? Thanks. Yeah. We have historically been in sort of the 2% from inorganic, and that is a good sort of model to go forward. Obviously, it flexes up and down depending on opportunities, but that is a good model going forward. Then when you think about the building blocks of the step-up, maybe I will have Mauro just give a little color as to how he sees that happening in his market. Well, first of all, it is linked a bit to the points that Manish was covering. We are really early in this cycle. We spend every week at clients, and we really understand where are those clients in the cycle. If I talk about Europe, and you saw the numbers globally, Europe, we are even much earlier in the cloud journey, for example. Many clients, I am not talking about global clients, but national champions are still discussing how to approach the journey to cloud, and cloud is a big enabler of AI. What I am saying is that, as Manish was saying, there is a lot of work to do to prepare and transition into real capturing value from AI. The point of which I was going to make on the tech debt, the data debt, the process debt is very visible. Clients really need to navigate in this moment, and they really need to navigate and understand how to make choices. One point that I see very valuable is they learn more and more how to deal with ecosystem partner. They need to play and make the right alliances, the right partnership with ecosystem partner. I think they find always in Accenture, the preferred partner, at least I can say in Europe, to help them find the right balance across a different ecosystem partner to try to have certainty of the future steps. Because many CEOs tell me, "I want to have certainty of future cost." Today, we need to make choices. We need to decide who to partner with and how fast you can afford to this transition, because then maybe we did not discuss a lot about change management. Change in organization takes time, and it's not a magic button of putting AI and then everything works perfectly. Our job is we need to navigate together with them in their transformation journey. The other building block is the network, right? It's 6% today, but it has the potential to be 12% in FY 2029, and it's growing double digit. You can start to see how that becomes a much more material contributor by FY 2029 in helping us achieve our ambition. Hi, Kevin. Thank you. Kevin McVeigh, UBS. Really helpful day for sure. As you think about the business mix consulting relative to managed services as clients start to scale their AI adoption, does that mix stay constant? With the efficiencies clients have on the managed services side, do they redeploy that more into the consulting or more on the managed services? I'll sort of keep this short. For about a decade, we've been approximately 50/50, and much of our managed services also now includes consulting type of work, and then the consulting type of work leads to managed services. We don't see right now some big change happening, and you can see that even in our guidance for FY 2027, where both are growing about the same. We don't see some big catalyst right now for a big mix shift. Great. Thank you. James. Thank you very much for everything today. James Faucette from Morgan Stanley. I wanted to ask about ventures and acquisitions. I feel like this is probably an underappreciated component of the strategy and how you're able to stay on technology cycles. I'm just wondering, how do you think about sustaining the growth rates of these businesses as you acquire them? How should we think about how that evolves over time, and then how that contributes to the expected acceleration, especially as we're seeing an uptick in acquisitions right now? How important of a driver in the expected acceleration is that? Thanks. Yeah. I'll have Manish comment, but one of the things just to reground everyone in is that the acquisitions are both in our core business and in the network. In all cases, the belief and the way that we look at the business cases are that they have to grow more because they're part of our family. That's our mental model in terms of as you think about maintaining and actually accelerating growth. Manish, can you give a little bit of color? Yeah. We have done, as you have seen, plenty of acquisitions. I think they are all in terms of where we believe there is a massive opportunity for growth. If you look each one by one, the reason why we turbocharge all our acquisitions is the availability of our client account lead network, the deep trusted relationships of being a complete trusted advisor, the biggest orchestration engine on this planet, which John and Mauro spoke about, is that access is why everybody and all the ecosystem partners and all the acquisitions, that is the biggest strength of Accenture. Massive strength. Can you just imagine at 4,000 clients, I've got people who are sitting there walking the corridors, talking to the client every single day and understanding what the key challenges are and deploying the available. That is what they are all doing. That is why we feel very confident to what Julie just said about rotating the business as we move, because 6%, they will come, they will get access to the world's biggest distribution channel, and then we just have explosion of growth around that. Go right here. Excuse me. Sorry. Thank you. Excellent. Rod Bourgeois here with Deep Dive. Manish, I have a question for you about managed services, given your background, particularly in that area. When you IPO'd your managed services business, I think it was 17% of revenues. It is now 50%, and it is on a very large base. All of the concerns about AI floating around impacting stocks, but it is growing 7%. Can you give us some color on where the growth is coming from and how much of that is in newer areas of managed services that we may not have grown up understanding from a historical perspective? Thanks. Thanks, Rod. I think this is the question which keeps on coming. Managed services, what is going to happen? Hair on fire on that managed services. As you rightly said, thanks for pointing that out, that we have grown this in a massive way. We are growing this in a consistent way over the years. I think there are two parts to this, which I said earlier. One is every time something gets at lower cost, the demand increases. This is where I always give the example. Automation will destroy all jobs in humankind. We think it is a new term that has come now. It was first stated in 1851 during the Industrial Revolution. That is the beauty of this, and people think about this. That is point one. So explosion, because it is becoming much more cheaper, AI is able to get, I think it has given us more higher value-added work to be done in the managed services. In fact, part of the reason you are seeing the revenue per headcount increasing is because we are doing the higher-end work which the clients are now trusting us with. That is point one. The second one, which is big, is all the new managed services. They are just at a great scale that they are increasing now, but that will become even bigger part of our service, which is the whether AI managed or the data managed services. I keep on coming and saying AI is beautiful, but let us first do the data cleanup and the process cleanup and the digital core cleanup. Maybe quickly I would add that at least I have seen visible with AI, the business cases of our clients have significantly improved compared to three, four years ago. The business case for the client on the value that they can capture is much bigger. Now they are much more ready because, okay, maybe the business case was so soft four or five years ago. Now the business case is probably sometimes even double. There is more openness to do managed services from many clients. Let us go back there. Thank you. This is Fani from HSBC. I want to extend on the previous question that was asked. The managed services was supposed to be the area where you would see a lot more pressure, but you said it was growing at 7%, but your total overall group revenue was at 5%. Which is the area that you are seeing some more pressure on? Because the other subsegments that you had mentioned were all growth areas. The second question that I had was on your delivery model, considering that more and more delivery is going to fixed or outcome-based, how do you see this evolving into your outlook? Thank you. Great. By the way, it was actually 7% in Q4 and 6% for the year. For the year. So a little bit less of a gap. What I would say, and maybe, John, you can comment a little bit on this in terms of where we see the squeezing of the legacy, while a rotation to the new, because of course, Americas is half our market, and you can comment a bit on the delivery model. So I think this is a little bit of the question that we've been talking about with managed services overall. We do see managed services continue to grow. But at the same time, there's different parts of managed services that are in there. There are some legacy managed services that we have in there that are under more pricing pressure, right? By being able to squeeze those, it's creating an opportunity for us to sell into some of those other areas that had not been outsourced previously. It's the balance between those things where we're driving the incremental growth. As a company over time, we've succeeded by leaning into innovations in the industry, like just the offshore that Julie talked about at the very beginning, or innovations in technology, which has created value, speed value, for any of our clients. That was true with offshoring, that was true with cloud, that was true with SaaS, and it's true with AI. With each one of these things, we're kind of leaning into it. Even in cases where it's reducing the total revenue that we would get on that contract, the savings that we create gets reinvested somewhere else. We're in a great position to help them figure out where they can apply that savings in order to create more growth or more differentiation elsewhere. So it's kind of this revolving circle as we go around. The legacy parts of the business that are getting squeezed create savings that gets reinvested into the parts of the business that are trying to grow. When we help them save, then we also are helping them grow or differentiate in another area. How it works for the client and how it works for us, these are relationships we've had, as we talked about, in cases for decades. We sort of know both sides of this equation or working with them on this transition, like partnering. That's why our delivery model is all about we want to use as much AI as we can in all types of work, because that's called putting the client's needs first, and then positioning to be able to do more. Our strategy, what's so important about it is we have been building the expertise to be relevant to all these other buyers for, in some cases, decades. Right? Those budgets are the ones that are now starting to expand in addition to the tech budget because of the opportunity. That's why we're so well-positioned, and the breadth of our business really matters. If we were a much more narrow company and absorbing AI efficiencies, that would be a challenge. But we really have a broad base of business that's super exciting. Let's go to Darren. Hey, thanks, guys. It's Darrin Peller from Wolfe Research. Let me just start quickly with Angie, and then a very quick one for Julie as well, but it's really first on margins. If you could just help us in the context of the environment we're in around some more interesting dynamics around pricing, how do you think through the building blocks for the conviction on the 10-30 bps, especially all the way out a few years? Then maybe just quickly, Julie, when we think about the areas of your business that the new data infrastructure and the core being advanced opens up for you that maybe you couldn't sell as much of three years ago, what are a few of the areas, I'm thinking about Song or areas like that maybe can accelerate now given the infrastructure of your customers today? Great. Let me start with- Thanks I'll start with the margin expansion and how we're thinking about it, because I do know there's been a lot of conversations around pricing throughout the day. There's the four levers that I went through earlier today. Pricing is absolutely one of those factors, which is the margin on the work that we sell. We work hard. Our goal is for it to be maintained or improving. That's the first. The second piece is how do we deliver our services? Julie, like everyone up here has talked about how we're leaned in in terms of how we deliver our services to our clients to be more productive in how we're delivering that. Second big lever. Third is how we run Accenture. Pretty significant, and you guys have seen that in our G&A, for example, in terms of the efficiencies that we're building in. All three of those things, along with our talent and supply management, all of those are in play that allow us while absorbing, by the way, while absorbing significant investments, and you saw our investments in our materials that we set and still throwing off 10 to 30 basis points. It's a formulaic piece that we think through, but those levers are in play for us to deliver the 10 to 30. Right. We're four years in now, right? Obviously things can change, but our confidence comes from we've been operating in this environment of more competitive intensity. We've been operating in the environment of giving more productivity, right? We've been taking out costs in our corporate functions and reinvesting it. Again, I would've said we wouldn't give this three-year guidance one or two years ago, but we are now four years into this big transformation, and so we have more confidence in how this develops. Then the other question was? Just trying to give a couple of examples of the offerings you have that maybe Sure have potential to accelerate given your customers. Yeah. I think that probably the biggest new area is the enterprise AI stack. You heard Manish talk about where in FY 2023 that we had four deals that were $50 million or more that were mostly AI and data as opposed to other deals, and last year we had 50. Now, we want a lot more than that, but that's where we're starting to see companies that have built enough of the digital core and they're willing to spend the money because you don't get immediate ROI when you're building out the enterprise AI stack, and that's part of the challenge, right? In terms of adoption, you really do need that full stack, and data is absolutely critical. But I would say that in building out the digital core, one of the things that we talked about earlier is that there are so many areas of the digital core that are actually new areas. So the mainframe is one of them. IBM z17 product is only a couple of years old now, and so now it has the ability to embed the AI, to make different choices about what goes to the cloud, what makes sense to stay there. That's a big growth area that isn't about something brand new, but the tech is there, and they absolutely want to use AI, and it's very important to be able to use more AI, that you modernize it. And so it's very important that the depth of our understanding of each of these aspects means that we're capturing new growth in each of the components. It's not all about. Again, it takes time. You have to have investment. Our clients, the spending environment's not changing. Some of that's just got to be worked through. All right, I think we have time just for one more. I know you've had your hand up for a while. Why don't we take two, and we'll take the woman next to her who's also had her hand up. Thank you. David Paige from RBC. I was curious if you could talk about some of the emerging growth opportunities, maybe in the mid-market or in emerging markets. How should we think about that over the next two to three years? Thank you. Sure. Do you want to start, John? The mid-market is one of your favorite topics, along with Morrow. I'll start. The mid-market, just to be clear, there's the mid-market, which is an area that historically Accenture, while we do work in the mid-market, isn't something that we've targeted in the way that we're intentionally targeting now. These are companies between, say, $300 million and $3 billion in size. We're going to market with our ecosystem partners, with packaged solutions, and a team that's been custom-built in order to serve that sector of the market. For us, I look at it in Americas like white space upside for us, and I think we will be able to grow there because we have a strong brand, we have super strong ecosystem relationships, and we obviously have a scaled delivery capability on and offshore that we can do this. That's upside. Then there's the emerging large segment. Which again, we've always worked in emerging large. This is the $3.5 billion to $7 billion size companies. We are intentionally targeting the highest performing companies in that sector, and we have a lot to bring to the table for them as well. We have very senior executives that have been working with the biggest companies in every one of these industry stacks. We're making some of those folks available to directly serve companies in that sector so that we can bring that 20 years of expertise, knowledge, network, understanding the industries, in addition to the rest of Accenture's capabilities that we do for the biggest companies in the world today. As I look at both of those, and Manish and I have been working on this for the better part of the last three years, we've seen these segments really grow. We're being more public about it now with all of you, but we have a lot of upside potential that we're looking at as we continue to lean in here. Let's take our last question now. Thank you, and thanks for your time today. This is Maggie Nolan with William Blair. I am curious on the guidance, what would happen or what would you expect to be the driver behind an increase in FY 2028 from mid-single digit to FY 2029 in high single digit, and your confidence in being able to reach the high end of that in 2029? Right. The big drivers are that both the core and the network are going to grow. We expect the network, our ambition is to double it by 2029 and to have the core continue to grow in the mid-single digits. And we feel that if we can achieve that with what we expect to start to happen in 2029 in terms of opportunities and where we expect AI to scale, that is when we feel like we can have this step up. Now, where we are going to be in the range in that step up, we will update you closer to then. But we feel like we are being very realistic about the opportunities, the realities that we need to work through over the next couple of years, and where we think that the opportunity to scale both the network and grow the core is. Thank you. I am sorry. I would love to spend more time, but I know it has been a long day. I just want to thank all of you on behalf of the entire management team and our board. You have invested a lot of time with us, and we appreciate it. Hopefully, you are walking away with a deeper understanding of how we have become a business reinvention and technology company, and why we have so much conviction in our growth and our shareholder value creation ahead. Thank you for your time and your trust, and we will see you at earnings. Thank you.

Data Source: Quartr Last updated: Oct 14, 2026

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