Good morning, and welcome to HubSpot's Spring 2026 Spotlight Investor Webinar. I'm Chuck MacGlashing, and I'm here with Yamini Rangan, our Chief Executive Officer, and Duncan Lennox, our Chief Product and Technology Officer. Today, we'll walk through HubSpot's 2026 strategy and how the new products and innovations we released at Spring Spotlight yesterday are making AI work for growth companies. We'll also share an update on how HubSpot is transforming how it builds, grows, and operates with AI. Before we start, I'd like to draw your attention to our safe harbor statement. Statements made during this webinar that are not historical facts may be considered forward-looking within the meaning of the federal securities laws. These statements reflect our views only as of today, involve risks and uncertainties, and we undertake no obligation to update them.
Please refer to our most recent SEC filings for a discussion of the relevant risk factors. Now, it's my pleasure to turn it over to HubSpot's Chief Executive Officer, Yamini Rangan. Yamini?
Thank you so much, Chuck. Welcome. Hello, everybody, and thanks so much for taking the time today to join us in this investor webinar. Look, the pace of innovation is just accelerating. There is a lot happening in the industry in just a matter of weeks, and there's a lot happening at HubSpot. We just had our Spring Spotlight yesterday and a lot of exciting updates. We wanted to provide a product and strategy update. There's just too much happening within the industry and HubSpot that we didn't want to wait until Analyst Day, which happens later in the fall. Just as a reminder, we're still within our quiet period, so all of the financial updates will be part of our earnings call in early May. With that, here is the agenda for today.
I'm going to start by setting the stage with our 2026 strategy and the progress that we are making within that strategy. We are going to spend the bulk of time with Duncan Lennox. He's our Chief Product and Technology Officer, and he's going to walk through our agentic customer platform and the agent updates from Spring Spotlight. You're going to see a lot of the product demos, and you're going to see how context shows up as a distinct advantage in all of those demos. I'm going to close out by sharing how we are transforming how we build, grow, and operate as an AI-first company. Okay. With that, let's jump straight in. Our strategy is clear and it is focused. Make AI work for growth companies.
Reimagine marketing with a new playbook as well as products, and accelerate up-market growth with a platform that delivers both power and simplicity. Let's start with AI. Look, there is no shortage of tools in the market for AI, but there's a huge gap between AI output and AI outcomes, and that is exactly the gap that we are focused on. We're focused on democratizing AI for companies with two-2,000 employees in order to drive growth for them. Now, small and mid-market companies, they don't have the time, and they don't have the expertise to keep up with the blistering pace of AI improvements that we see every week. We do it for them. We are their growth partner in AI transformation, and our AI strategy is really clear and focused.
We want to deliver a platform that has all of the Growth Context, which will help both agents as well as the humans using our software to drive outcomes. Today, we're going to share the progress that we're making in both a set of first-party agents that we just updated, as well as the Growth Context that drives that outcome. Okay. Let's talk about marketing. The pace here is accelerating really, really quickly. Now, discovery of brands as well as products is shifting pretty dramatically to a diversified set of new channels, including LLMs. That is why I'm really excited to announce HubSpot AEO, HubSpot's Answer Engine Optimization solution that we just launched yesterday. Now, this solution provides AI visibility so that you can see the share of voice. It provides prompt recommendations as well as content recommendations.
HubSpot customers can now buy this and use this in two ways. First of all, as a stand-alone solution. That means there is a new front door for HubSpot's marketing solution. Start just with AEO. Second, they can use all of these advanced capabilities with Marketing Hub Pro as well as Enterprise. I'm really excited about this launch and the value it's going to deliver for our customers. Up-market, look, we continue to have strong product-market fit in this segment of the market. Customers are looking to lower total cost of ownership, consolidate their stack, and drive AI innovation. With the updates that we are delivering this week, we are bringing more powerful agent capabilities as well as platform capabilities to help them grow and drive AI transformation.
Very exciting updates, and you're going to see us accelerate innovation throughout this year in these three key priorities. At the same time, we're completely transforming the company. How we build, how we grow, how we operate as a company is changing, and the pace of change there is accelerating internally. I'm going to share more about the progress that we're making here in a few minutes. This is our 2026 strategy.
Now, let's jump straight in to the highlights from Spring Spotlight. In order to do that, it is my absolute pleasure to welcome Duncan Lennox, our Chief Product and Technology Officer. Now Duncan is responsible for product, engineering, and UX, and he's setting this pace of innovation within the company. Before HubSpot, Duncan spent time at Google to head their applied AI, and prior to that, Amazon. He's seen scale and significant scale. He was also the Co-Founder and CEO of two companies in the sales and e-learning space for more than two decades. Duncan, welcome and take it away.
Thanks, Yamini. It's really great to be here with you all today. Yamini just laid out our strategy for 2026, and at the heart of it is AI that doesn't just deliver output but actually drives outcomes for go-to-market teams. I want to dig into what we believe is key to making that happen, which is context. I'm going to walk you through how we think about context at HubSpot, why it's so important, and demo products that we featured at our Spring Spotlight this week that uniquely use context to deliver real value and outcomes for customers. At HubSpot, we're building the agentic customer platform, and that means we capture all your customer context in one place, then make it available to both your team and AI, embedded AI and agents, so they can work together to market, sell, and service your customers.
You might have seen this visual of the agentic customer platform before and even heard others talk about the importance of context. We've thought deeply about the role that context will play specifically for go-to-market teams, and I want to walk you through how that thinking has refined and shaped what we've built. First and foremost, not all context is created equal. Personal AI tools are building personal context, your preferences, your conversation history, your communication style. We've got enterprise tools that are building organizational context, so documents, wikis, and institutional knowledge. Go-to-market teams need something different, and that's why we're focused on building Growth Context, the specific dynamic understanding AI needs to drive outcomes across marketing, sales, and customer success. This isn't just a concept. We've built real infrastructure that will help customers capture and maintain their Growth Context.
We see Growth Context as having five dimensions. Firstly, we've got business context, everything that makes your company yours, your unique positioning and voice, your pricing, your differentiation. We've got team context, how your best people actually work, the judgment, the methods, the instincts that live in calls and deal notes, not in your onboarding docs. Process context then is really the nuts and bolts of your workflows, what triggers a handoff, what makes a deal urgent, what your companies are actually built to do. Customer context, of course, is the full history of every relationship with every customer you have, what they bought, why they bought it, where friction happened, and what comes next.
Finally, network context is the collective intelligence of HubSpot based on 18 years of working with hundreds of thousands of go-to-market teams, pattern recognition at a scale no single business could ever build on its own. Let's walk through how all this comes together in the life of a customer. We're going to follow one company through the full journey, and that company is Sonder, an employee wellness platform. They work with businesses to give employees access to mental health support, wellbeing coaching, and preventive care programs. They're a real HubSpot customer and a great example of how shared context across the go-to-market team leads to growth. Let's start where every business has to start, getting found. For Sonder, their target buyers are HR leaders and people on culture teams inside mid to large enterprises.
These are people who are actively looking for wellness solutions, but the way they're finding those solutions has changed a lot. The search bar is no longer the first stop. Buyers are going to ChatGPT, they're going to Perplexity, they're asking LLMs who to buy from before they ever click a link. If Sonder isn't showing up in these answers, they're invisible at the most important moment. Most marketing teams have no idea how their brand is represented in this new world of discovery. The campaigns they're running are often built on assumptions rather than their actual customer data. This is where HubSpot gives Sonder's marketing team an advantage with HubSpot AEO. It shows marketers how their brand and content appear in AI-generated answers, how they compare to competitors, and what to do to fill that gap. Let's use it to track Sonder's AI visibility.
To get started with AEO, the first thing Sonder will do is set up their brand profile. HubSpot pulls from Sonder's brand kit that they've already configured, pre-fills their name, domain, and any brand variations an LLM might use to refer to them. Sonder reviews a list of key competitors generated by HubSpot based on their unique customer and business context. Sonder can also add anything that might be missing. Lastly, we confirm a set of tracking prompts. These are the suggested questions buyers might use to search for businesses like Sonder that HubSpot generates based on customer context.
Things like, what employee wellness platforms are recommended for mid-size companies in Australia. If Sonder notices a prompt is missing, they can add their own, like, what should I budget for a global employee wellness platform. With all the prompts set, they can do a quick review to make sure nothing is missing and start tracking. Okay. Now that we've got that set up, let's take a look at Sonder's AEO dashboard. Here's where they can see things like their brand visibility, what percentage of those tracked prompts actually mention Sonder. They can also see their competitive share of voice, how they stack up against each competitor. We have the prompt dashboard, where Sonder can manage the prompts that they're tracking, and if they want to go deep on any single prompt, they can click to see the actual responses that models are using.
We get to the citations view. This tells Sonder which websites are driving the AI answers. Finally, recommendations. This is key. Based on areas of low visibility, HubSpot AEO recommends actions Sonder can take to increase how often they appear for that search. That's exactly the kind of insight that informs their content strategy and lets them know where to invest. Here's the thing about these prompts. Get them right and you optimize how you show up in LLMs. Get them wrong and you're spending resources trying to show up for questions no buyer is actually asking. Growth Context makes the difference here. We pull from Brand Kit for your positioning, your value props, the foundations of your business. As your customers engage through forms, emails, and calls, their questions and areas of interest become critical customer context that informs the prompt suggestions.
That's what makes HubSpot AEO more valuable over time. It's learning from your real customer conversations, not just your marketing copy. Six months ago, Sonder had no idea whether they were showing up in AI answers at all, and now they do. More importantly, they know exactly what to do about it. Now that Sonder has a better understanding of their AI visibility, let's use Breeze Assistant and Loop Marketing to build an awareness campaign to close that gap between them and their competitors. Breeze Assistant is now a Loop Marketing expert. It's built on the playbook we launched at INBOUND last year for marketing in the age of AI.
As a quick refresher, Loop has four stages, Express, where you define your brand and ICP, Tailor, where you use AI to personalize content, Amplify, where you diversify your campaign across channels, and Evolve, where you learn and iterate with the help of AI. Sonder has already an established brand and ICP. It's mid-to-large enterprise companies in Australia who've recently expanded. Yamini talked about helping customers navigate marketing with the new playbook, and now Breeze Assistant can help them do it. We know from HubSpot AEO that peer-reviewed sites and listicles are strong-performing citations for Sonder. Breeze pulls those citations, and we ask it to draft a marketing brief so we can double down on the content that's working. Based on Sonder's brand and the customer data stored in HubSpot, Breeze Assistant builds a comprehensive brief targeted at increasing the quality and volume of their citations in AI answers.
Now, Sonder uses Marketing Studio to build out a full campaign. They pull in the content HubSpot AEO told them is working and use the remix functionality to create new assets like blog posts, social content, and even a podcast. Now, the marketing team collaborates live in the studio, and within days, they have the new campaign in market. Now, here's how HubSpot's context advantage makes Breeze Assistant different from other AI tools. Without context, the most AI can do is quote from a generic marketing playbook. Breeze Assistant knows your business, your brand identity, your ICP, your product catalog, even customer feedback.
HubSpot doesn't just store thousands of contacts. It understands how you organize your market and the value proposition you're bringing to them. When Breeze Assistant gives you Loop Marketing guidance, it's not generic best practices. It's grounded in your actual business. It also knows where you are in HubSpot and what you're trying to do. If you're looking at a contact record, it understands you need information about that specific contact. If you're building a campaign, it suggests next steps based on your actual customer data. It knows your role, so marketers get campaign strategy, sales reps get deal guidance. The recommendations aren't just helpful, they're specific to your job. New content is live, and it's working. A Sydney tech company, about 400 people, recently expanded, found Sonder through one of those peer review citations we just optimized for.
The Head of People visited the pricing page, spent time on the case studies, and is now in the CRM as a high-intent lead. This is exactly the moment where most sales organizations lose ground, not because the product isn't right, but because what happens next is too slow and too manual. It's not a rep problem, it's a context problem. The rep gets the lead notification, but they still need to figure out who else is in the buying committee, what the company is going through right now, and what's going to land. This research takes hours, if not days, and we all know time kills deals. That's what the rebuilt p rospecting agent is designed to solve.
Now, instead of researching the companies that you enroll, the agent prospects for new leads based on your ICP and monitors those leads for new buying signals that tell the rep when it's a good time to reach out. When the rep opens the agent, they already see a prioritized list of companies showing intent right now. The rep can see each signal and exactly what triggered it and click through to the source. Every company also comes with a reason to reach out, already written. The rep clicks in. One contact is already in the CRM who came through the campaign, but the agent also identified two others, a CPO and a CFO, so the rep adds them to the CRM. The agent has already drafted personalized outreach, pulling in the rep's signature, referencing the buying signals, and using Sonder's value proposition specifically for the role.
It even knows the campaign content, because that's all on HubSpot. Context is what makes Prospecting Agent actually useful. It's pulling from your full CRM history, every interaction, every conversion, to understand which accounts close for your business, not just which ones look promising. The outreach isn't generic. It's grounded in your product positioning, a rep's role and priorities, what triggered the contact in the first place, past conversations, and similar feedback from other customers. It learns. The more your team uses it, the smarter it gets at finding accounts that actually convert. That's the through line here. The content Sonder created to improve their AEO citations brought this buyer in. The same customer context that informed the campaign is now informing the outreach. Okay, fantastic. The outreach worked. The Chief People Officer responded, Sonder's rep had a discovery call, and it went great.
The budget is confirmed, requirements are clear, and the next steps are agreed. Now, here's what normally happens. The rep tells themselves they'll update the CRM after the next meeting. They're busy. By the next morning, they've already forgotten some of what was said. The deal stalls, not because the customer wasn't interested, but because the rep ran out of bandwidth. Smart Deal Progression closes that gap. The moment the call ends, instead of reps patching notes together manually, HubSpot preps next steps for them. It isn't just a to-do list. Smart Deal Progression knows more than just this call. It operates like a rep's second brain with the same deal and customer context. That means in the post-meeting recap, the rep can see a clean summary and action items, each one cited back to the transcript. The rep isn't guessing.
They can hear it for themselves and approve with confidence. Action items are attributed to the right person, editable, and can be saved as tasks in one click. The follow-up email is also written. It summarizes the call, captures what was agreed, and the rep can refine the tone right there with Breeze, and after the tweaks, they hit send. This is where things get really interesting. Smart Deal Progression then makes suggestions for CRM updates like deal stage, amount, next steps. All suggested, all accurate, all pulled from deal context. The rep reviews and approves in seconds. The CRM is updated. Nothing was left to memory. Look, I've said it already, I'll say it again, I genuinely think this capability is underappreciated. Smart Deal Progression is like giving every rep a second brain. It sees past emails, notes, and deal activity, everything.
When it suggests next steps or follow-ups, it's reflecting the whole relationship, not what just happened on the last call. It knows how your team actually sells. It understands your pipeline definitions, your deal stages, the way your team executes. When it suggests CRM updates or flags risks, those recommendations reflect where the opportunity actually stands, not some generic sales framework. Context turns a transcription tool into something that actually moves deals forward. Okay, the deal Sonder was working just closed. Fantastic. 400 employees at that Sydney tech company now have access to Sonder's platform. This can often be where the relationship is made or lost. Employee well-being is a sensitive category. When an employee reaches out about accessing mental health support, they expect a response that knows them, their plan, their history, their situation.
A generic automated reply in that moment doesn't just miss the mark. It does real damage to the relationship and trust. Sonder's support team can't personally handle every query at that level. That's the tension. It's exactly why context here matters more, perhaps more than anywhere else. Let me show you how Sonder sets up Customer Agent for email, their highest volume support channel. The first thing they do is set their expressions, the specific instructions that tell the agent how to behave, how it greets employees, closes conversations, when to apologize, and which topics it should never answer autonomously, like anything involving clinical escalation, which Sonder always routes to a human. HubSpot provides out-of-the-box templates to make this fast, but Sonder can refine the instructions if needed. Okay, great.
Now, before going live, Sonder's team tests the agent with email, simulating real customer queries without putting anything in front of actual customers. They can see exactly how it would respond and build confidence before they commit. Okay, deployment. Sonder starts with working hours only. The agent handles email after hours and on weekends when the team isn't available. They also use a workflow to route by customer tier. Free plan users go to the agent, enterprise accounts go straight to a human. Billing and clinical questions are excluded entirely. Here's what it looks like on the receiving end. An employee emails in asking about booking a wellness coaching session and whether her plan covers it.
The agent reads the email, pulls her record from the CRM, her plan tier, her session history, what she's accessed before, and replies with exactly what she can book, how to do it, and a direct link, formatted clearly, signed off professionally, thanks to our agent expressions, and answered in seconds. She got an answer that felt like someone actually knew her because the agent did, and that's what context in support looks like. Customer Agent responds based on the complete context. It's pulling from your knowledge base, your product data, and that individual customer's full history. Every response is tailored to the person and their situation, not just the ticket in front of them. When a human needs to step in, the handoff actually makes sense because Customer Agent lives inside of HubSpot, so it sees the entire relationship. Your service rep isn't starting from scratch.
They're starting with full context, what the customer tried, what the agent recommended, and how to make the agent better based on your customer context with smart QA. What you saw wasn't five separate product demos. It was one story. Sonder building awareness in a world where discovery has moved to AI answer engines, converting that awareness into pipeline by reaching the right people at the right moment, using the right context, and closing that deal because nothing slipped, cementing the customer relationship through support that actually knows who it's talking to. We're already seeing real customer outcomes thanks to HubSpot's context advantage. With Breeze Assistant, we're seeing 4x more leads created. Without business and market context, AI can only use generic marketing advice to create generic plans. With it gives you one that's actually targeted to your customers.
That's the difference between campaigns that resonate and ones that don't. With Prospecting Agents, we're seeing a 19% increase in email send rate. The increase in send rate is important, but the real measure here isn't volume. HubSpot is focused on high-value outreach that reps want to sign their name to. Send rate went up, but we also went from reps rewriting 2/3 of the drafts that we produced to approving 2/3 of the drafts without edits. That shift happened because the outreach is grounded in the Growth Context they needed, real buying signals, and emails written in the rep's own voice. It feels authentic because it is. Smart Deal Progression, we're seeing 10x improvements in CRM update accuracy. Anybody can build a CRM updating agent. What's hard is earning your sales team's trust.
Reps hate filling out CRM data, but they're held accountable for it, so the bar is high. With Growth Context, not using just the current call, our suggestions are 10 times more likely to be accepted, and that's what it means to actually save a rep time. With Customer Agent, we're seeing 70% of tickets on average resolved. We can achieve average rates this high because Growth Context means we surface the full customer history. If the agent fails, we can tell you exactly why, whether it's a gap in your knowledge base or missing customer data. That's the flywheel here. Every escalation makes the agent smarter for next time. For HubSpot AEO, we're excited to have it in market, and we've seen incredible early results from customers who've been early testers.
For example, in a matter of weeks, Sandler drove 8,000 new website visitors and moved their brand visibility score two points. AEO didn't just tell them the problem, it told them what to do about it. Docebo went from guessing at their AI visibility to leading their category, with nearly 15% of leads now coming from AI sources, and that number is growing. For Fresha, the question was simple, are we showing up? Now they know the answer, and their traffic growth reflects that. The thread running through all of these results is Growth Context. That rich set of information that go-to-market teams to actually deliver outcomes. That is only possible on HubSpot. That's because Growth Context isn't one thing. It's business, team, process, customer, and network context all working together. Almost every meaningful AI action in the go-to-market process needs all of them.
Point solutions might have one slice, but that's why they hit a ceiling. Let's say you're preparing a prospecting email. A point solution providing customer context might help you get their attention with a personal hook, but it won't match your voice or product positioning without business and team context. A support tool that's great at surfacing your knowledge base can answer some questions, but it won't know why the customer bought your product in the first place and be able to use that context to the team's advantage. Even platforms that tout being unified have found it incredibly challenging to solve this. Many may have the data, but they aren't and haven't been opinionated about the structure, so they cannot understand how the pieces relate. HubSpot has always been deeply opinionated about what it takes to grow.
Opinions that were formed very early on about what a contact is, how a deal works, what a campaign does, these are the foundations that allow us to organize disparate data into rich, complex infrastructure of Growth Context. That's what the agentic customer platform is built on, and that's what HubSpot's context advantage makes possible. I'm going to hand it back to Yamini to close us out by discussing how we transform how we build, grow, and operate at HubSpot.
Well, thank you so much, Duncan, for that really comprehensive walkthrough of agents as well as the context layer. I hope that was very informative in terms of what we launched and how Growth Context shows up. Look, I'm super excited about the outcomes that we can drive for customers with our agentic customer platform, and that is exactly what everything is about, driving outcomes. We've always taken sophisticated technology and democratized it for small and mid-market customers to drive outcomes, and that is exactly what we are doing with AI. Let me actually walk you through a few examples of what customers are adopting and how that is driving outcomes for those customers.
Okay, let me start with Metrie. Now, Metrie is a North American building materials company. They have about 400 HubSpot users across multiple regions. Now they had a completely manual process to triage incoming emails. They created a workflow and used Customer Agent to read every incoming email, route that email to the right queue, and then respond to that request specifically with the Growth Context. Now they used up their 5,000 included credits in two days, and then they bought 100,000 more to keep that agent running. Now they are well on the way to leverage nearly 300,000 credits. In Q1 2026 alone, Customer Agent handled over 16,000 customer conversations for Metrie. Quote turnaround time is down by 33%, and order turnaround time is down by 35%. Clear example of a customer scaling with Customer Agent.
Let's talk about ISSA. Now, they are in edtech, and they run one of the largest fitness certification programs in the world, which means you can imagine that they get a constant stream of customer questions across chat, across email, as well as phone. Now they came to HubSpot to consolidate their entire fragmented support stack, and they went all in on AI from the start. They started leveraging Customer Agent as well as all of the AI features within Service Hub. Now Customer Agent handles 100% of their chat volume. That means they have freed up all of their human agents to be able to handle more complex questions that comes in phone. That means the phone abandon rate has dropped by nearly 70%. Clear example of leveraging platform capabilities as well as leveraging Customer Agent.
I'll finish up with an example on Prospecting Agent, and this is with Eventus. They are a fast-growing fintech company. They wanted to scale prospecting, but within their CRM, they had nearly 10,000 dormant contacts and inaccurate data, which means that every outreach email they were sending, they were just getting a huge bounce rate back. They wanted to fix that problem and drive growth. They started with adopting Data Agent. Data Agent helps enrich the company data, helps enrich the contact data, and provides a very clear prospect score. From there, they started using Prospecting Agent to personalize the outreach across multiple channels, and that is working. Because of this, they've been able to replace point agents and other solutions and data that they were using.
In Q1, 50% of all of the engaged prospects interacted with Prospecting Agent, and that is driving more pipeline for Eventus. You can see that they have continued to scale credit consumption based on this. I hope you can see the clear momentum in both our product innovation as well as customer adoption and the kinds of use cases that we are seeing traction in. With that, I want to shift gears, and I want to talk about the internal transformation at HubSpot. We're transforming how we build, how we grow, how we operate, and the pace and progress here is exciting. We have fundamentally changed how we build products at HubSpot. Now, we started with Copilots, like everybody did. We scaled very quickly from there with coding agents, and now we have a HubSpot-specific agentic execution platform that is compounding our advantage and driving the pace of innovation.
I'll walk through each of these phases. Now, in phase I, it was all about Copilots. We proved that AI could make every engineer go faster while maintaining the reliability of the product. That gave us organizational confidence as well as the data to move into agentic AI, and that was our phase II. In phase I, if it was about making engineers go faster, phase II was about using coding agents to do the work. We moved from AI-assisted coding to fully autonomous agentic coding. Here's the thing that we found. We found that off-the-shelf coding agents that we were using were okay. At our scale, which is 1 million builds a day across tens of thousands of microservices, it's just not optimized for HubSpot. We needed an agent harness that was optimized specifically for our environment.
We moved into phase III pretty quickly, and we built that infrastructure ourselves, a Kubernetes-based agent execution platform where every single coding agent runs in an isolated container that replicates a real HubSpot developer environment, complete with internal build tools, the test suites, and the service access that is needed. What does this mean? Well, this means that instead of building every agent from scratch, we have built a foundation once. How agents access data, what actions they can take, how they connect to the rest of the Growth Context within HubSpot, everything. Now, that decision has compounded really fast. Many of you know that we've always taken a platform-centric approach to development, and that has helped us maintain the pace of innovation and built that pace. You've seen that with reporting, automation, messaging, things that are platform primitives that helped us ship more capabilities across every hub.
That is exactly what we are doing with agentic execution. We now have the unified tools, the unified skills, and all of our agents are interoperable. That means they speak the same language, they share the same tool sets, the same skills, and they draw from that same Growth Context. That means our customers, they get a consistent experience regardless of which agent they are using, because underneath it is a platform that is scaling. That is a massive advantage. For our customers, it's an advantage, but for HubSpot, this is what enables the pace of innovation with AI. Really exciting. Okay, let's talk about how we grow. Now, over the last two years, we've systematically rebuilt how we attract, engage, and delight with AI agents as well as assistants.
The result is an agent-first go-to-market, a flywheel where agents are doing the work and humans are operating with higher leverage, but much deeper connections with our customers. Of course, the value is really clear in why we do this. When we are in the bleeding edge of go-to-market, we learn faster. We provide that feedback to product, and we also educate our customers in terms of best practices. What exactly is this agent-first go-to-market? Let me talk exactly about the agents that we are now using. In terms of how we are attracting, the top of funnel is nothing as it looked like three years ago. We once had a bunch of content leads and inbound chat teams to be able to do it. Now, top of funnel is an AI-powered demand generation engine. It actually starts with a demand agent.
Demand agent builds up our TAM. It identifies our ideal customer profiles. It enriches the company and contact information through a variety of HubSpot as well as third-party sources, and it scores every single account so we know what to prioritize. We use an inbound agent that handles roughly 82% of all of our website chats with no human involvement. It qualifies visitors, it handles competitive questions, it identifies real buying intent from who is on that, and it's now even beginning to start closing starter deals. Pretty exciting. We also have a AEO agent. We've been proponents of this. We've been experimenting, iterating, and working on AEO for the past couple of years, and that is why we are the number one CRM with visibility across all of the LLMs. Our qualified leads are up significantly, and those leads convert 3x better.
That's the transformation in the top of the funnel. Let us talk about how we engage our customers. We have built agents at every stage of the sales motion, and we have provided assistance to our reps using AI. Our Prospecting Agent does exactly that. It tracks the intent of our prospects. It then generates personalized messages that our BDR teams as well as our reps can use in terms of outreach, and that has improved the productivity. At the same time, for active deals, reps have now a conversational assistant that sits on top of everything that they do. It provides risk scores. It provides similar won deals as they're having the conversation. When reps and managers use it together to work a deal, the win rates go up.
Finally, we've also built pre-sales agent that handles technical questions and a demo agent that spins up a tailored demo environment on the spot for a specific prospect. Lots of innovation going on there. Finally, let's talk about the delight stage. Here's where we have seen two clear patterns emerge. The first is in support. We found product market fit here almost immediately. Customers got faster answers here, our team got capacity back, and obviously, AI has added to productivity. We've not hired a single tier one support rep since 2024. Clear value that we are driving there.
In the case of customer success, the story is more interesting because that actually is providing an assistant for all Customer Success Managers to understand the usage of a customer by specific use case, where they're using HubSpot, where they're not, and how they can have deeper conversations with customers. It is really exciting to see this transformation within our go-to-market. I'll kind of finish off with this. HubSpot is going through a process of massive AI transformation and metamorphosis. Over the last couple of years, we have inspired HubSpotters to leverage AI, provide access to tools. We have transformed the culture to be one of experimentation, and we have changed the organizational clock speed to go from annual planning to now operating in just six-week sprints. The result is an organization that is genuinely AI-first, with 95% of HubSpotters using AI weekly. We're just getting started.
What we've also recognized is that employees becoming 10x more efficient with AI tools does not automatically mean the company is 10x more productive. There is a gap between AI driving individual productivity to AI driving institutional productivity, and that is what we're focused on. We're investing in the infrastructure to provide context across all of the teams. We are reimagining workflows within specific teams and identifying pods that can actually drive this type of institutional productivity. That is the transformation that we're building towards. Let me close this out. I hope you found this very useful. I hope you take away a few things. One is that we have a very clear and focused strategy. We want to make AI work for SMBs. We're reimagining marketing, and we're accelerating up-market progress.
We have a clear advantage, Growth Context. It shows up across the platform. It shows up in every single agentic use case that you saw in the product demos today. Our pace of product innovation is accelerating. We remain laser-focused on delivering great outcomes for our customers. We know that is a massive opportunity for us. Thank you so much for taking the time to join us for this update. I look forward to speaking to many of you in early May.