First of all, how amazing is this conference? Have you guys been day one, day two? Day three is the best. Day three is the best, right? Factually, it is, it is absolutely the best.
You can tell the energy is really high.
Well, that doesn't say anything because we have a fairly quiet audience. Even when this room is packed, there's no questions, et cetera, so... But, the quality of the company is the content has been just off the charts. Jeff, thank you so much for making it to the conference. Really appreciate it. You were here last year, and I asked you this question: What is the long-term vision of the company? And, you have a really—had a very compelling answer. I wonder if that answer has changed. So what is your—what are your goals for the company? What is the strategy? How you want this company to look like five years from now?
So the goal of the company is unchanged, right? We see the ability for technology to completely change the way companies go about building their relationships with their customers. And now, I'd say, if anything, that vision for what we can accomplish has been supercharged by all the progress we've seen in generative AI. So at our conference, just two weeks ago, we really unveiled our vision for how we think Gen AI plus the CDP. So taking all the understanding a company has about its customer, as told by all the data, pulled into profiles of customers and then audiences of similar customers. And now, Gen AI can take that and turn it into more powerful, more effective customer engagement and customer communications through every step of the customer journey.
The end result of combining customer data, communications, and AI, we believe, is going to be companies will be able to build 10x better customer relationships at one-tenth of the cost of today. You know, when you think about these use cases, right, how would that work? Well, is Gen AI able to take a really... Like, all the data about the customer base that a company has, and unlock a 10x more performant marketer? Absolutely. Easily. We laid out that vision. Like, AI can actually automatically create marketing journeys for the marketer. In fact, we launched a product called Generative Journeys.
You describe to the AI, you say, "Create a journey for customers who haven't bought anything in 30 days and, you know, have things in their shopping cart, and but have bought something at full price at some point in the last year, and, you know, their favorite color is purple, whatever. And then try to sell them what-" And you just describe it like that in English, and it will draw the whole journey, like all the boxes and all the, you know, do this, wait 3 days, do that. If they did this, do that. It will automatically select the customers that are the best candidates for that campaign, and you just click approve, and it starts. Oh, and it writes the emails, too. I mean, you know, this is all possible.
And then once you say, like, "Okay, that's possible," this is literally something we announced two weeks ago. Once it's that possible, once you go from, oh, it's, you know, takes a minute to do this journey, that before would have been probably weeks, you know, going around to the, "Okay, well, I gotta get the data people to give me the feed of customers. Then I gotta go to the, the creative writers, the copywriters, and then the design people, and all that." Now, you can just do it in, like, you know, a minute. Then you start to ask questions of like, okay, well, what's the limiter on how many of those you can have running, right? Because it used to be people's time was the limiter on how many campaigns you could be running at one time.
And now you're like, oh, by the way, we, we also announced a product called Generative Audiences, so or Predictive Audiences, where it would basically say... You know, you wake up in the morning, and it says, "Hey, we analyzed, you know, AI had analyzed your, all your customer data and realized that there's a propensity for these customers who bought this product, and this, and this, to go buy that product. They're, you know, 40% more likely to buy that product. Do you want me to create a journey around that?" "Yes." "Okay, on the Generative Journey created." Like, so you talk to me like, okay, AI can have the ideas for the campaigns. AI can actually execute the campaigns. AI can see the full end-to-end end of, like, is this campaign generating sales? And if you feed it gross profit data, is it generating profit?
And if yes, great, do more of it. If no, you know, slow down or stop it. Now, you're like, the limiter is if a company typically would have maybe 100 of these campaigns running at a time, because human beings had to go do all this work. In the future, companies are gonna have millions of these campaigns running simultaneously. Millions of simultaneous campaigns that are constantly coming up and, you know, being created and killed, and created, and killed, and AI measuring their effectiveness, and the human beings are gonna look at charts, and they're gonna test hypotheses. If I feed the AI this data source, does it get better or worse?
So it becomes data science back to the marketers, right? So when you ask the question, can the marketing team get 10x better? Minimally, like, 100x better is probably more likely. And can they do that at a tenth the cost before? Easily. Right, so that's the vision we put out there, and the same thing, by the way, goes for service and support and pre-sales, and a lot of other functions inside the company, where you're just gonna get these 10x outcomes at a tenth the cost. That's the power of combining the data that a company has about its customer with generative and predictive AI, and then all of the channels to go out and deliver on that promise to the end customer.
Got it. Two things that come to mind, Jeff. One is, doesn't this lower the barrier to be in AI-driven applications? Because you have data, Salesforce has data, you know, ZoomInfo has data, Adobe has data. All of a sudden, we've gone from these stovepipes of very domain-specific, you know, I do creative, I do sales, and you do CDP and, Flex really, really well to, oh, okay, so AI is helping us get into the data and draw these deep insights. So you, and you deliver your spiel. You sound like a marketing automation company, right? So, pros and cons, does it not lower the barrier for anybody to get in and do this?... and what is so unique about the data that Twilio has that-
Well, if you, if you think about like-
You're right to win here.
If you think about it, like, the core of that story is data and the channels. Like, everything else is, like, largely automation and a few dashboards. And so what it really comes down to is if every company has access to the same language models, and the language model space is, you know, commoditizing rapidly. So I think everyone will have access to language models, that's a no-brainer.
Yeah.
And so what it comes down to is, what proprietary data set does a company bring to bear that is better than, you know, say, their competition?
Correct, yeah.
There'll be a variety of answers to this question. You know, people have proprietary data set, it's about, you know, various things about product, or maybe I've got, you know, data about you know, some domain-specific thing. But every company has customers, and every company has customer data. So the question becomes, how well do you use that customer data to turn it into these AI outcomes? There isn't the thing. There's no one source of data. Right? 'Cause you take all those, I think, called them stovepipes. I haven't heard about, like, you know, the silos of data that exist among, you know, web data, mobile data, e-commerce data, marketing data, purchase data, returns data, I mean, everything you can imagine, but you have to bring it all together in order to unlock this outcome.
Just having a bunch of separate data streams sitting in different places does not allow humans or AI to have an insight about what would you do for Kash? What is Kash interested in? What's he all about? You need to take all that data together in order to draw the inferences and make predictions about each person, and then cohorts of customers, and things like that. That's what the CDP is needed for.
And so what the CDP allows companies to do is to tear down all those data silos that are essentially the blocker to getting these AI outcomes, and that's why Segment, as the leading CDP in the market, both in terms of its capabilities, but also in terms of its market share, according to IDC, you know, that gives us the edge of helping customers to create their proprietary data asset here, that allows them to unlock this outcome better than their customers. When you think about the incentive for companies to do this well. But if you can get 10x better outcomes at a tenth of the cost, which I think is directionally what you can get at a minimum, then there'll be so much incentive for customers to get this right.
Got it. That puts you in a new category in marketing automation and things that you've noted on before.
It's actually not about marketing automation. It's like, I actually think that all of this comes down to data, basically. But yes, we are in the marketing automation space with our Engage product which is built on top of Segment. We are in the contact center space with Flex, our contact center product. But those are all built around the core of communications and data, which is really the foundational assets that are most important in this story, I believe.
Got it. Before I turn it over to Matt, one other thing is, when you look at the synergies in this AI world, what are the synergies between the communications business and the applications business, and what are the things that you can, you talked about a data-centric view of building these new generative AI applications. What else can you leverage from the communications platform?
Well, you know, every customer that comes to us for communications is coming to us for communications for a use case. Right? Think about the text messages you might receive from a company, or the phone calls, or the emails you might get from a company, right? As the leading platform for voice calls or voice messaging and email we see customers come to us for contact center use cases, for sales and service, for marketing use cases, for security, like one-time password use cases, and for notification use cases. Like, those are the four most prevalent use cases that most companies come to us for.
So if you think about it, what we've been doing is aligning our stack to enable us to go deeper- or really, you know, vertical in those areas. You know, for all those contact center use cases that customers come to us for, well, obviously, we have Flex. For all those marketing use cases they come to us for, we have, we have Engage. For all the one-time password and notification use, like, we've got our Verify product. So if you think about it, the way we've built out our product portfolio is to say, if a customer comes in and says, "Hey, look, I'm trying to plug Twilio into this use case around verifications," then we say, "Okay, well, you know, you can do it yourself.
Here's, you know, the right APIs, or we've already have that built for you that you can plug in and you can choose." And so for us, the opportunity is to upsell customers into a solution that solves the problem they're going after, versus building it themselves, but still in a very technical way and still in a very API-driven way. And that's the basic interconnect between the raw communication capabilities that we have brought to market that is a $3.5 billion-dollar business for us and we're the leader into the next areas that we're taking the company.
Yeah. I have a macro question for you before I turn it over to Matt. Our Chief Economist, Jan Hatzius, has been calling for a soft landing, and it's been right so far. We've reached a point where inflation's come down just about enough, and rates seem to be stabilizing. You know, we've gone through a tumultuous 18-month period, and nobody anticipated that we'd have such a massive rate increase, and the economy has hung in there and done okay. Everybody's fears of a recession have proven to be, sadly, maybe for them, untrue. The industry has come out okay. So it's been-
Only thing said at banking conferences, you know, sadly.
Yeah, I know. Yeah, sadly. And for the people that made those negative announcements, happily for us, you know, we have a more, sanguine view. Where I'm going with this is, if things were to stabilize, and we do have a soft landing, we actually call it, we stole Jan's soft landing. We're calling it Software Landing. That's a Goldman Sachs proprietary thing, Software Landing. Let's say if you have a Software Landing and rates modestly come down second half of next year, whatnot. What does calendar 2024 look like in the event that we don't have this massive instability, and we just have a more normal, normal economy that where people are less concerned about? What do budgets look like? What, what does-
Yeah, I mean, you know, don't have a crystal ball. But what I would say is, you know, you've seen over the last 18 months, a lot of companies looking at their investments in a like with more scrutiny. You know, asking what's the ROI of the various software products that we've invested in? Trying to harmonize those investments, and say: Hey, do we have, you know, two or three of this category? Maybe we can consolidate down to one. Or saying: Hey, do we have, you know, someone bought this thing, are they even still here, and are we getting the value out of it? So you just have the, those things going on.
By the way, those are good things to go. Like, companies should be focusing on that in terms of efficiency, and I think that's what this side of the cycle is actually about. A lot of times, it's just to kind of clean up from the good times of the last, you know, cycle, and then, you know, the whole thing repeats again. So for software companies, though, I look at what most of the software companies that I think of. I think about the ones that we use, that we're buyers of. I mean, software fundamentally makes companies more efficient.
Like, that's the role that software plays. Now, you actually have to implement them correctly, right? You have to get use out of them, but ultimately, software has the ability to make companies better. Like, I believe that. I think what you get back to is more of the upside thinking of, "Hey, if we have this piece of software, is it going to help us drive more market penetration, more, competitive, wins, and put us in a better stance for a longer period of time? Because right now, companies are in that retrenching mode. They're thinking about short-term outcomes. How do I save some money now?
Right? Whereas you start to get back to thinking about long -term, "Oh, if I invest in this, I will see an ROI. And so to me, that's what the Software Landing probably looks like. As conversations with customers start to turn back to, "Hey, what's the opportunity to build a really strong competitive stance for the company because you're investing in software, and now especially because you're investing in AI, how is this going to evolve the competitive dynamics in your market, customer? How can we help you to go win in that world? I think that's what normalcy will look like again.
Yeah. Okay. So Jeff, just pivoting back to Generative AI for a moment, we talked about the implications of Generative AI on CDP, on marketing campaigns, etc., but if we bring that to kind of the Flex contact center product, right? Contact center seems like an area that's ripe for disruption with generative AI.
Yes, absolutely.
So can you talk about some of the announcements coming out of SIGNAL, whether it's Flex Unify or Agent Assist, and maybe how that may catalyze, you know, broader adoption of that product?
Yeah. So one of the things that we are preparing for is for the contact center to pretty aggressively turn into a, an automation platform. Today, contact centers are largely, you know, human workflow products, right? So human beings log in and, you know, take calls and have to browse all sorts of myriad internal systems to help customers. I think the contact center of the future will be much more about managing the automation than it is around actually having human beings have those conversations. You know, we were talking to some industry analysts recently, and, you know, I asked the question, I said: "How many seats are there globally for the contact center?" And the answer was, you know, directionally, about 20 million. And I said, "How many folks..." These are the experts. These are the industry analysts.
How many folks here believe that number is gonna be more five years from now? How many hands do you think went up?" Zero. Okay, how many of you think it's gonna be less?" All the hands go up, right? So then the question becomes, okay, so we all agree, how much... The question is now, how, how, how much less?
How much, sure, yeah.
Half as much? A quarter as much? I won't spoil what the hands did in that part of the of the conversation. But this is an area where I actually think the fact that Flex is a more nascent business for us is actually a benefit. 'Cause if Flex were a substantial part of our revenue today, we'd probably have a lot of conflict. And I think a lot of SaaS companies have a lot of conflict, will have a lot of conflict around AI. Because if you're a SaaS company that's monetizing per seat, and you're gonna tell your customers, "Hey, I think, you know, we're gonna make your people that buy our seats, like, we're gonna make them 10% more productive, and the world, the future is gonna be glorious."
When in fact, the reality is, a lot of AI will make it so you need fewer of those people. Maybe 10% fewer, maybe 50% fewer, right? That's the contact center. That's every SaaS category, basically, with seat license. And so the question is, if companies have built their business model on seats, they're gonna get disrupted because they will be hesitant to deploy that, technology that requires you to have half as many seats. But that's what the technology will enable. And so disruptors are gonna be able to come in and say, "Guess what? I can offer you technology that means you need half as many seats," in a way that the incumbents will be hesitant to do. And so I think that'll be true in the contact center as well. And so we are very focused on automation.
We are very focused on bringing together the customer data together with those communications channels, because, again, I think this largely becomes much more of a data and a data science problem versus a how do I manage a thousand, you know, people sitting in cubicles problem, and then, bringing the data together with, of course, knowledge about the company and its policies and all that, those are the foundations of that automation.
And you can see, we launched this vision two weeks ago with CustomerAI, which basically said, "Look, if you're trying to build AI that is gonna serve customers, whether it's in a pre-sales context, whether it is in a support context, whether it's in any of these contexts-" The key ingredients here are going to be, one, you know, an LLM that has the ability to reason, and that is the amazing thing about the language models that we see today. Like, that's the thing that changed in the last give or take year, is you now have computers that can reason their way through hard problems. That's why I think this is not hype. This is truly going to be an innovation that is, roughly the scale of the internet in terms of impact on humanity.
Because for the first time ever, we've built a machine that can reason, and when you look at some of the problems people have asked LLMs to solve, and you watch it work its way through how to solve this problem, you're like, "That is reasoning." We don't know how it works, but we also don't know how these work either. So it's the same, it's the same mystery to us, but nonetheless, the outcome is pretty darn similar.
Yeah. So, Jeff, I think the common thread in this discussion has been just the massive productivity unlock across a ll these different categories that Twilio plays in. So I guess, how do you think about pricing for this productivity improvement?
I think what you're going to do is, like, clearly move away from per seat pricing. The only product that we have that does have the option of per seat pricing is Flex, and I think that's just a pricing model for us and for anyone who's smart will go away. And you'll price it more on, probably on a conversation basis. Like, think about Segment. The way we price it today is on monthly tracked users. It scales to how big a customer is your customer base. That's roughly speaking, how much work we're going to do on your behalf.
It's also roughly equivalent to how much value you're going to get out of our solution, and I think you end up with models that look more like that, which is like, the more conversations you have, the more you're going to pay us. Right? The more data that's involved in those conversations, perhaps the more you'll pay us, 'cause there's more compute going on to, to infer things about that customer, to do some smarter things. So maybe there's levers that you turn on and off to make that conversation smarter, and those are features essentially, you pay more or less for, but it's not going to be a per -seat kind of basis.
That's very interesting, and maybe we take it back to fundamentals for a moment. You guys initiated revenue growth targets for 15%-25% from fiscal 2025 to 2027. Right now, the company, I think, is expected to grow less than 10% this year, right? So can you help, you know, bridge for the audience, kind of how you expect to get back to that kind of 20% midpoint over the next couple of years.
So there's two ways of... Not two ways, two facets of the answer. One of the things that we're doing, and then the other is, like, more macro, right?
So I'll start with the things that we're doing. What we are very focused on, number one, is scaling and getting the go-to-market machine for Flex and Segment to a scale that is like a humming machine. As you know, we've told everyone in the past, we combined our sales teams in early 2022, which was a mistake, and so we've kind of had to unwind that decision and reconstitute the independent selling machines for Flex and for Segment. So that's been a painful mistake, but I think largely the work is behind us in terms of the foundational work of hiring the sales team, getting butts in seats, enabling them, and now we've got a largely enabled sales team, and now it's a matter of building pipe and closing deals.
For Comms, what we are focused on is going out there, winning design wins, so that's when a customer decides to use Twilio and is going to bake us into a product, as well as taking share from other competitors. In terms of Twilio having leveraged the last, you know, the last era of growth to go have the largest customer base, the best balance sheet, the best products, and the most revenue, like, that puts us in a great position that now we're on the other side of, like, you know, the cycle to go win market share because we're the strongest company in our competitive set. We grow our customer base there, we grow our customer base on both sides. Those are the things that we're working on now in terms of our go-to-market.
The flip side is the macro economy, because as we've talked about, a usage-based model has a great tailwind during a growth period, but unfortunately, has a headwind during the, you know, the economic not growth period that we're in, I guess. It's not a recession it's a, the slowdown, whatever the flip side is that's between, like, awesome times and a recession. And so it's a headwind for us now. For communications, a usage-based model means that, like, if our customers are just doing less business, less transactions in their businesses, that typically would mean, like, less communications. I told the story on one of our earnings calls of I bought the new Zelda video game from Best Buy.
I got a text message that said, "Hey, you know, your, your order is ready to come pick it up. Right? So as an example, if fewer people are buying things because they have less disposable income, then there will just be fewer text messages sent because there's fewer things bought. In the same way that people are taking less vacations or, you know, whatever, less consumer activity equals less communications. In Segment, there's also a little bit of that dynamic, too, 'cause we monetize it in monthly tracked users, MTUs. And so customer- and that includes, by the way, anonymous users.
So people who land on the website and are clicking around, right, that's interesting data for a company, 'cause, one, at some point, that might turn into a tracked user, and you want to know all the activity they did. But if marketers are spending less on, say, SEM to drive people to that website, and we know a lot of marketing budgets have been pulled back during last year, well, then there's less users to track, and so at renewals, companies have right-sized those contracts to the now monthly tracked users that they're seeing. So that's the headwind we face.
So on the macro side, the tailwind is as economic activity picks up w e don't have to do much, and you start to see the growth kick in again as more economic activity happens, as marketers spend more, more people on the website, or just more transactions are occurring, you see more in the communication side. And the thing that we are well -positioned for is to capitalize on that growth without having to spend more. Because we have reduced the size of the company during this cycle pretty substantially, about 27% o verall from our height, through two rounds of reductions in force. We've got a really great cost structure, a cost structure in place now, and we can deliver on that growth without having to invest much at all, if anything, into the foundation of the company.
And so what you'll see is, as that growth kicks in from a macro standpoint, we can drop a lot of gross profit to the bottom line, and that's what's really exciting about the what the future holds in terms of things that are in our control, and then a little bit of the macro side. And so, look, I think that if we hit a, a really horrible recession, I think that could be a, an impediment to us reaching those medium-term targets, but I don't think anyone's calling for that, a nd so I feel confident that we can hit those medium-term targets.
So from your perspective, like, where are we in terms of usage trends? Are you starting to see stability kinda coming out of Q2 relative to where we were in Q1 or even, you know, a couple of quarters back? You know, can you share some context around where you think we are in terms of-
Yeah, you know, in, in the early stages of this side of the economic cycle, you know, we saw the usage patterns just deviate from where they had been historically. So our predictions about, hey, what do we think our usage is gonna be, they weren't materializing because there were fewer transactions going on, fewer like, all the macro stuff going on. And when we talked earlier this year about stabilization of volumes, what that meant is that we weren't seeing degradations. In fact, our models were accurately predicting the usage trends that we were seeing, and so that was the stabilization. And I think that now what we are seeing is both the effect of, you know, some.
You know, I wouldn't say the, like, macro is, like, changing, you know, materially day to day, but, yeah, I think generally speaking, you know, you're probably seeing the economists say, like, "Yeah, there is a stabilization. " You know, it's not like a lot of things are up for question like they were maybe a year ago. So there's a stabilization going, and then you say, our go-to-market efforts of winning market share, winning new customers, et cetera, has the ability to grow our usage volumes and the revenue as a result.
I want to jump in one thing. So on that very topic, Jeff, are you calling for at least you expressed optimism that bookings can accelerate in the second half of the year? Is that based on the stability, the economy stability? What are the leading indicators you're seeing in your business that give you confidence that we can show exit on a strong note this year?
Yeah, and just, just for clarity, I'm not trying to make any, guidance around bookings 'cause I don't think that's something we've ever guided to. But what I will say is, like, I think we're seeing some of the buying hesitation early in the year is, like, those dynamics are changing a little bit. I wouldn't say it's, like, a wildly different market.
Yeah, yeah.
I think we're seeing some more positive signals in terms of, like, early signs of pipe generation and things like that. I think Generative AI is certainly a tailwind to this whole thing. Because , despite the fact that customers are still rightly focused on ROI and, you know, being good stewards of their capital, t hey all know that AI is going to change their industries and change their companies. Now, exactly how and when, everyone's trying to figure it out. Everyone's trying to say, "What are the things I should be investing in that are gonna bear fruit?
Which are the things that maybe are too early or, you know, there's probably gonna be hucksters, like, in this in the AI world, just like there were in, you know, Bitcoin and everything else." Like, every trend brings that, and so they're trying to sort through, okay, what's real and what is, you know, maybe speculative? They know gen AI is gonna change, and so that is the nature of every conversation I'm having with customers now. And the way we are positioning. What we do is, look, it is very early in the buying cycles for AI, no doubt about it. I don't think... I think there's some exceptions, but I think largely speaking, AI is not turning into revenue for software companies yet.
Do you think it will?
Oh, absolutely.
Okay.
'Cause I think the incentive to invest in these use cases is going to be so high. I'll tell you a story. Like, we just made it through our migration in our communication server business, the 10DLC migration, which is an obscure thing that, sadly, investors in Twilio had to understand. But it's like we are migrating from, basically, a world where every sender on the network was kind of unknown and anonymous, to a world where everybody is known. Which is actually really good for all of us as consumers, in reducing spam and fraud, and all sorts of bad things that can happen on the network.
It was a painful process 'cause everyone had to register their campaigns to be able to keep sending text messages, so it was a very painful effort. We deployed AI in some of the later stages of getting these campaigns approved that did the work of hundreds of people that were spending months working on it, did that work in, like, minutes. Right? I mean, that's probably a 1,000x productivity increase for Twilio. And when you look at these outcomes, you're like, "Wow!" Like, it is astounding. And so now you start to think about rolling ahead to other situations that our customers are in where they are just throwing manual work at problems that could be automated to get a 1000% increase in productivity. That is, those use cases, you can't ignore that.
Does that lead to contraction in employment, or just makes us more productive and do things faster, quicker, and enjoy better quality of life?
I mean, look, the comparison that I typically make, rightly or wrongly, is to, you know, the Industrial Revolution, when you suddenly got an abundance of physical labor. Right? And, you know, a lot of people said, "Well, what's gonna happen if you need, you know, 100 people to run the farm today a nd now there's a thing called a tractor? Like, what's gonna happen?" Well, clearly, farms are run in a much more efficient way. We're able to feed billions of people that we couldn't feed prior to the Industrial Revolution, and people have moved on to other professions, and so the farming industry is much more efficient now, you would say, and as well as able to fulfill the needs of humanity much better. And so I think there'll be similar transitions that go on.
I don't know exactly where, and I'm not gonna pretend to have the answers about exactly how it's gonna work out, although I suspect that there's a lot of parallels from history that will be analogous. In the similar way that you look at how computers made people more productive in their work, and productivity led to stronger economy , just more economic output from humanity I think you'll see the same thing here.
Bill McDermott was here yesterday. He's always bullish, but, you know, he's been for the right reasons, right? He believes that IT spending next year will be faster growth rate than what we saw this year. Because, you know, for everything that we've gone through. I mean, do you have any thought on that? I mean, it seems like this whole stability theme, especially with rates starting to come down... We're not economists. You're not, I'm not either. But if things start to stabilize, maybe we unfreeze some of the budgets that have come under so much scrutiny. Do you think there's a possibility that next year could be a better year overall for software?
Well, you know what's interesting is this. Somebody actually asked me in a session just before I came down here, they said, "If, you know, people are gonna invest in AI, where's that budget gonna come from? Like, who's gonna be the loser in that story? You know, I thought about it for a second, because that actually wasn't something I'd necessarily thought about in the past. But I... You know, it did strike me that I don't think there needs to be a loser in that story, because if you get as much efficiency gain as I think companies can get with AI, the ROI and the speed of that ROI pays for itself. And so you don't have to have a loser. You know, there's some amount of upfront investment, but it's just gonna pay back so quickly that- and that's where you get that notion of, like, efficiency gain and the software industry can return to growth if we're able, and that's the big if ... if we're able to deliver on that efficiency gain. I think that there will be certain areas where we'll be able to deliver on that pretty quickly. Other areas will probably take more time.
Yeah. So with that, I think 19 seconds away. Thank you so much, Jeff, for coming to our conference. Really appreciate it, and I hope you have a productive day. Thank you for our clients for your participation as well.
Thank you. Thanks, have a nice day.
Best day. Yeah, let's, let's finish it up on-
Thanks, everybody
... a very high note. Thank you so much.