Accenture plc (ACN) Earnings Call Transcript & Summary

Let me remind you that some of the matters we will discuss in today's conference, including our business outlook, are forward-looking and as such, are subject to known and unknown risks and uncertainties, including, but not limited to, those factors set forth in our most recent annual report on Form 10-K, quarterly reports on Form 10-Q and other documents filed with or furnished to the SEC. These risks and uncertainties may cause our actual results to differ materially from those expressed or implied during our presentation and are not a guarantee of our future performance. As always, Accenture assumes no obligation to update any statements made in these presentations. During today's presentation, we will reference certain non-GAAP financial measures, which we believe provide useful information for our investors and our analysts. You'll be able to find materials from today's session, including reconciliation of non-GAAP to GAAP measures posted to the Investor Relations section of our website.

Hello, and welcome. We have many of you in the room and online. So thank you for joining us. And thank you to the people who actually make today possible. That's our reinventors and our clients around the world, the incredible technology companies that make up our ecosystem and of course, our production team who's with us today. We're also joined by some of our Board and many of our senior leaders. And for those of you here today in person, you're going to be able to meet some of those senior leaders. We are really excited because you're 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're going to cover three things. First, why is AI making Accenture more essential than ever; second, our new foundation for growth that we've been building for the last 4 years; and finally, third, our growth trajectory, how we're going to use that foundation to drive significant durable growth and shareholder value creation. So let me start with some context. Twice in the last 20 years, there's 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. And you saw for the first time, software starting to replace some services. Now 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. And 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. And in both cases, Accenture had significant growth and took significant market share. How did we do that? Well, first of all, we embrace 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 organize to what we sold. And we invested each time in new sources of revenue that were being created by the technology wave. So we're now 4 years into the next economic reset of our industry, the age of AI. We think the opportunity is bigger than ever before. And 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's being replaced. Now across both of these areas, clients, the ecosystem and trust have been at the center of our strategy, and they remain so. And we have confidence in our future because we've had a great track record in prior technology waves, we're running -- a playbook that is informed by the past but accelerated. And now we can see it in the opportunities that we've created already and the new foundation. So I'm with clients almost daily. It's the best part of my job because it's 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's 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 enterprise and many more are just getting started. Wherever they are starting, there's 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. And this is what matters to Accenture. Our clients turn to us in times of change. The bigger the change, the more they need us. And reinvention is fundamental change. And our clients over the years have turned to us over and over again because we've 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. Now you're going to hear a lot about of our strengths over the course of the day. But I want to highlight a few that we've built over decades, who we serve, who we build with, what we know and what we've done. So 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. And we have an incredible ability to build trusted relationships sometimes built over decades because we have a cadre of client account leaders who wake up every day thinking about how to help their clients be successful and what we can do to be a part of that. This means that we have unmatched insight and experience. And there's 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. And 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. And 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 #4 on the Great Place to Work global ranking. This is cross industry, and that ranking is by far the highest in our industry. And when you take all of these factors together, that is why decade after decade, we have been the #1 partner to the ecosystem that matters to our clients. And 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. So 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. And 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're 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've 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. And 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. And when you think of each of these strengths, who we serve, who we build with, what we know, and what we've done, they're the reason why Accenture is a force multiplier for our clients. We help them do more than they can do alone. And 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. And underpinning that trust is our commitment to live every day our core values and our leadership essentials. Whenever I'm 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. Now before I take you to where we're going, I want to spend a few minutes on our starting position. Over the last 4 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 4 years, we've increased our addressable market from $1.5 trillion to $3 trillion. And in the age of AI, we have built the largest AI and data workforce in our industry. And while we've done that, we've 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 4 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, and 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. And we've been incredibly successful. We use our $100 million bookings a quarter as a proxy for reinventions. In FY '22, that was $100 million. Today, it's $141 million in the year that we just completed, which means over 500, 501 to be precise that we have done over the last 4 years, not only is that driving our growth, but it positions us for the next rounds of growth. And the way that works is well illustrated by a meeting I had this week. So just a couple of days ago, I met with the CEO of a new client, a $20 billion client -- 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 will be over $100 million. Now 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. And you can see that with our Diamond client relationships, which are our largest relationships, in FY '22, we had 267. We now have 317. Now over the course of the 4 years, as we focused on reinventions, we also learned a lot. In 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 7 units. We call them reinvention Partners. Each of them is organized around how our clients operate, invest and buy. And 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 '22, when generative AI emerged, we moved quickly. Within months, we had announced a $3 billion 3-year investment specific to AI. The best way to evaluate our achievement is to look at the numbers. So 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 the statistic. This is over 18,000 around the globe in multiple industries, from a starting standstill point of 5, right? 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's climbing every day. We also went from 40,000 AI and data professionals to nearly 110,000. We created 9 new business groups with the emerging companies that mattered in AI and data following our playbook that we build relationships with the technology company that matter to our clients. And 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's only a month now. We also announced the creation of our new AI safety business using faculty, our AI specialized business that we launched that we bought earlier this year, and you're going to hear from Marc Warner, the CEO, a little bit later. So when you think about why is it important? We took early leadership, mostly, it's because this is where the demand is going to grow and it's where our clients want to spend their money. But that early leadership also gave us another advantage. It helped us understand what the new growth would be. And 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. And over the years, we've used that to accelerate growth. And when we look at our business today, we have a multibillion-dollar businesses that were built initially through a lot of inorganic cloud, cybersecurity, song, supply chain and engineering. So 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 4 years, including the acquisitions that slipped into September $19 billion. We've done so for the three reasons we make acquisitions. The first is to scale markets where we're already in but have higher growth. So 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. So we've done a lot of supply chain acquisitions. Those tend to be smaller and more niche. And then the third reason is to expand into new markets. And 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. And so 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're 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 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 4 years, they've been about building, reinventing, expanding. The next chapter will be about scaling reinvention for our clients and for us. Our 3-year financial ambition is to achieve at least mid-single digit revenue growth in constant currency in FY '27 and FY '28 and then a step up in the range of growth from mid-single digit to high single digit starting in FY '29, 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. And we will continue to invest organically and inorganically in both the core and the network. So let's start with the core. The core was 94% of our business in FY '26, 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 technical debt and creating the technology foundation needed for AI. For others, it will 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. And 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 technology 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, and 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 use before -- do before. Some of that's going to be about running the enterprise, but there's a lot of net new opportunities like agenetic commerce. And 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. And 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. So we have two engines, the core and the network. But we also grow by who we sell to. And so 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. And we'll grow with them by leveraging our reinvention partners to grow our market share within a client and 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 growing -- is a $240 billion market growing high single digits. Now 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 bought mid-market focused companies to test our strategy. And starting in FY '27, 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. And the mid-market will be part of our core and part of our network. So before we go to the next section today, I just want to take a moment to summarize the big picture. We have invested for 4 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 FY '29. 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 a challenging spending environment. And 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 3 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 that -- the new areas that we've identified. And our ambition is to grow on a very, very large base, mid-single digits while absorbing AI efficiencies. And with respect to our network, we believe that we have the potential to double the size, it's currently 6%, by FY '29. So we're excited to now be able to dive deeper into those growth opportunities. And in a few moments, Manish Sharma, our Chief Strategy and Reinvention Services Officer, is going to come on stage to do so. But before we do that, we're going to talk about -- we're going to hear directly from some of our ecosystem partners. And 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, and then Angie will take us home this afternoon. So that's the day. Thanks again for investing the time. And now you'll hear directly from 5 of our ecosystem partners, all of whom we both use at Accenture and we help our clients use and then Manish will join us. Thank you.

Accenture is one of our largest and most strategic global systems integrator partners. At Reinvent 2025, they won 12 AWS partner awards, including GenAI Consulting Partner of the Year, GenAI 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. And through a 5-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. And Accenture ranks #1 globally in active Google Cloud certifications with nearly 50,000 Google Cloud skilled professionals. Deploying Agentic AI is a top priority for enterprises today. But 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 agenting solutions tailored to how specific industries operate, including marketing, cybersecurity, AI and data, contact centers and solved programs. Together, we're helping enterprises move past pilot phases and delivering transmission 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 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. But what really sets center apart is that they are not simply advising clients on becoming Frontier, they're 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 Getco Pilot. That first-hand 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, Nestle, Repsol -- and so many more, helping them move from AI ambitions to meaningful business outcomes. I'm 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 advisers 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 read team our models, study their alignment and test our safeguards. Both companies expect to invest at least $1 billion over the next 5 years in this -- This is money well spent because getting this right will both manage risk 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. 4 years ago, it could barely write a line of code. Today, more than 80% of all code committed to when tropics 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 to 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 entropic safeguards to detect mixed use. EFS has been a significant unlock for companies looking to deploy frontier models in high-value sensitive context. Internally, Accenture also watched the walk 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 9 industries in 18 markets. Cyber.ai launched in March with Claude as its reasoning engine. -- is putting Frontier capability to work in helping organizations defend against cyber attacks. 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 here. 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 opening, our mission is to ensure that AGI or artificial general intelligence, benefits fallout 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 is OpenAI's AI Transformation Partner of the Year. Together, we're helping clients move from AI that finds information to AI that gets worked on. asking 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, create, to solve problems. Building on its $3 billion commitment to data and AI, Accenture is training 100,000 people on ChatGPT work and Thank you. Our teams worked through a technical center of excellence with 700 Accenture forward deployed experts specializing in GenAI, open clients realize value faster. -- of course, requires detected 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. So I think just seeing these videos and everything else, I get very excited. And as I get excited, I'll speak even faster. So Rod, you got to kind of just say if I'm speeding too much. So I thought it will be good to kind of get that out first. But I think thanks, Julie. It's 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. And here is the math to kind of explain what we are saying here. You got the base, which was about $1.5 trillion. We added with 20 new 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 a $3 trillion addressable market. Now let me talk about how do we think about executing our strategy. And I'm 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'll take a pause and kind of now go into the -- how do we serve the enterprise. We serve the key buyers and budget holders through our seven reinvention partners. Want my friend, who is the CEO of Americas, we were chatting and he said, "Manish, like nobody understands what a reinvention partner means." And I say, "Reinvention partners is just think about them as the key budget holders, the key decision-makers in any enterprise." It's as simple as that, just focused on the budget holders. And -- as I look across the patch, it's 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. And 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. And 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 us Julie referenced earlier. I always like to think about tying AI to APS. Go away for the hype and the frenzy, it's 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 financed. They all have HR. They have a digital core. They have customer, cybersecurity and most have supply chain. And 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. And for example, I'll give you a few of them, right? 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 "the budget holders" who we are very 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 exchange. 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 this reinvention 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 multiyear journey and all will need to respond to the new tech evolution. And some of the stats which you will see here, right, modernizing ERP is only 41% complete. Moving to the cloud, where only 28% of workloads have actually moved. So we're an AI, 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 at $215 billion market. On modernizing the legacy technology, the hardest parts of technology estates are only starting to modernize. And 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. And 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, 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 run the payments and core banking that cannot fail. Much of it runs on IBM Z. 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 off-line. IBM Bob, our AI development partner makes Accenture's consultants more productive at this. We have also published a joint road map for clients modernizing an IBM Z. And Accenture has built IBM Apptio into the tools it uses to assess cost and value. So clients can see what the workloads on Z actually cost and what they're worth. Same is true in AI. Clients want AI inside the systems they already run with governance, the regulators accept, Watson X 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's 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 the 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's 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'm still in the core. So that is my second section of the core, which we are talking about. I've been with the firm for -- my 32nd year, and I've 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. And I said, greater efficiencies have always, always created more demand. And I've seen this through my -- whether it was -- whether we came RPA, the cloud wave and all the things that came out, I've always seen that like 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 business function and achieve their desired business outcomes. This means they get better, faster and lower cost solution while getting expertise and talent. And we are at the helm of delivering business outcomes for our clients in a tangible and a sustained way. Managed Services consists of multiyear contracts creating some of our largest, our most enduring relationship 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? And I will say AI is creating more demand. In FY '26, 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. I remember our first one was in July of 2001, right? And we were doing all the Managed Services in different we got approval for doing 40 people that time and to remember even today that day. In tech, agents are now embedded to run and modernize apps, that is a tech-managed services. In business processes, we have gone from key strokes and all the stuff that we used to do of transaction processing to delivering tangible sustained business outcomes for our clients. And we have new areas, new areas, which I think are still -- and I think they're 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 a 110 addressable market growing at 15%. It encompasses enterprises, re-platforming for AI, monitoring agents in production, managing the data polls that are out there and addressing rising cost governance and the compliance pressure that we always have to kind of think about. Finally, another massive thing for exciting thing for me, right, underneath all we have invention. AI. I just us seeing a report where it is kind of mentioned as the best, which is there on this planet, right. An integrated platform for identification and automation, where we have invested almost $1 billion over the last 4 years, reinvention.ai. Now, to be to life, I think I want to kind of starter companies is a great example of large-scale cross-functional reinvention looks like. Julie recently sat down with Stephane, the CEO of Steel Auto companies to talk about the reinvention, he is driving across the enterprise. Let's hear from them now.

Well, Stephane, 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, and you're going to be there again during our Investor and Analyst Day. So with your leadership team, so I really appreciate you building this in advance so that you could join us for Investor and Analyst Day.

No. And thank you so much, Julie, for being here. I'm so excited. I still remember this visit that we had together in India like it was yesterday and the leadership team and I had this view of like the scale, but more importantly, see the talent that you have like at our disposal today like in India. And I'm looking forward to be in your office, again, like in a couple of days.

Well, thanks. Very excited to welcome you back. And maybe we go back for a moment to actually the beginning because as we -- I know we're going to talk about the partnership. But at the very beginning, when you and I first had like -- 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've seen at lot of companies in the past, but in across industries, like really fast, you want it to move, but also the scope. I mean you basically said to me, Julie, I'm looking at everything. I want your best views. I want to reinvent how we're working, and there's nothing that is out of scope. I want to just really think about differently. And so maybe like as we get started, you can talk a little bit about just who Estee Lauder companies is, 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.

First of all, thank you for giving me the opportunity to speak a little bit about the Estero company. As you know, we are celebrating our 80th anniversary today. So it's a special moment for us. And we have like more than 20 beauty prestige luxury brands around the world. Among some of them with 6 of them that are $1 billion brand, Lauder, Clinique, MAC, Jo Malone, Tom Ford and even La Mer... And when I became CEO now approximately 18 months ago, when you and I had this discussion, we introduced our new vision, called Beauty ReMagine. And this vision was really to fundamentally transform the company at every level. We were looking at like our partners on how we were not going to do it, but we knew we needed it to do it fast. And that's where Accenture came into play. You and I had like a discussion at the beginning was like a simple guidance that you were giving me like on the way that the world is evolving clearly, what I appreciate it's very early on understanding how we could transform and we can transform absolutely every level. And I'm happy to just like 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. And I'm very proud of where we are today, looking fast forward at the end of fiscal '26. We just finished 3 months ago, we are back to organic sales growth. Our adjusted margin has increased by 300 basis points. And as an example, we have like 1/3 of our business online that is growing and gaining market share. So we are doing this transformation with speed. But this transformation needed more than just like 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. And today, this partnership is allowing us to just simplify, to create efficiency, to create speed, but more importantly, to also get access to AI, an agentic strategy that is -- is giving us the opportunity to not only see today but also the future efficiency that we can bring to the company.

And Stephane, maybe give our investors a bit of a view of just how broad it is. And why you wanted to go so broad in terms of like how do you think about -- you talk about this being a platform for growth. So maybe we can just talk a little bit about the scope.

Beauty ReImagine for us is a broad vision in the center. We simply but boldly want to become the best consumer-centric beauty, prestige company in the world. And for that, we needed to be fast, we needed to be agile, and we needed to just like 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, and we were doing it in a very fragmented way with like a thousand of vendors and partners around the world. So the way we were operating our brand and our regions and our functions was very disconnected and then you need to find a set of partners we will allow us to just change again, from a simplification and efficacy and, at the same time, also like speed. Today, when you look at the scope of what we had discussed at the beginning is there's not one area of the business that we are not looking into. Today, we are deploying our transformation, our simplification through like multiple transformation in finance, in supply chain, in technology, in people, in consumer care, but also in many marketing like pillars. So really, the fundamental transformation is allowing us to leverage our scale. Because ultimately, we are a large -- 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, invasion and also consumer experience at scale and leverage the power of the scale of the companies.

And you mentioned earlier, AI and Agentic AI, and that's an area that we are always talking about because it's so exciting. How do you about the technology and the AI component as you approached our partnership?

Very early on, on February 4, 2025, when we put the beauty margin, I've made it very clear that AI will be hardwired in absolutely everything we do. So I needed to find like 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 didn't have in the company. But also the right AI and agentic strategy that will allow us to just like create the ongoing efficacy because I want to be very clear. What we are not 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. I mean, I -- this is something you and I have done together, which has been really exciting, but also your entire leadership team is involved because it is so broad. So maybe as we wrap up, it would be great in sort of just your terms, kind of your words is, why did you pick Accenture?

First of all, you are very convincing, actually. -- is very, very good. But I think I really enjoyed like this partnership like 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 it's an operational transformation. So we needed a set of partners that we're going to be able to just operate at the speed that you've described at the beginning, but also allows us to just 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. And 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 transferred, every single area of business is going to be transferred very, very soon. And so 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. So 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 like consumer insights, how we are operating -- meaning like operationalizing all our processes internal with like AI, how we are deploying in supply chain, how we're deploying it in consumer care, to ultimately do what we do best. And I think this is one of the things that was very important. But I think there's 2 other things that becomes more apparent as we are developing this partnership. It is also the tech infrastructure. I have been very clear, we are hardwiring AI through everything that we are doing. And Accenture, like other partners is really helping us to really transform the company in so many that allows us to just improve our consumer insights, improve our supply chain, improve our financial processes and governance like across basically all like the pillars that we've discussed that we are deploying. And that's really key for us for ongoing and future benefit that we will create an efficiency for the company. And the last point is, I know it is dear to your heart and to my how to is also the talent. And I think I saw that like the 2 of us since the beginning, having had this relationship. But the second thing is also the talent that you deploy and the talent that we have in our organization. And I don't think with this talent, we would have been able to just prepare with the speed at which we are operating, not only it is fast in estate company standard, but it is also fast in industry standards. And I think I'm really proud of what we are doing, and it's really thanks to the talent. So I don't tenets really helping us to develop and to really get the business outcome that we are looking at. We are entering fiscal '27 in a very different company than we were in the past. We're much more agile. We simplified the organization. We are growing again, which was the objective that we give ourselves. And I know there's a share 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. So I couldn't be more happy about the partnership that we are developing together.

Thank you, Stephan. Well, we feel really proud and privileged to be a part of it. Thank you for allowing us to partner. And it's great to see where you guys are going, your results and excited to see this next chapter. So -- take care.

Thank you.

What I described is exactly what Julie and I have been talking about what it takes to deliver reinvention at scale. At that means transforming how the company operates across finance, supply chain, technology, marketing and consumer care across 150 countries, 150. And I don't think there's any company on the planet that can kind of 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 Stephan described about. I think Stephan also mentioned one important point. It's not about just reducing costs because sometimes we kind of get caught up about that. 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. So that's kind of just our partnership with Now I want to go on -- I'm still in the core. I'm going to now enterprise AI stack. This is the third example in our last scale reinventions that we're 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 kind of now help our clients with. The enterprise AI stack has an addressable market of $500 billion. Is that like, wow, this market was just not there earlier. And simply put, it's not about putting a model on top of the building and the building gets automated and AI, right? And this is where there is 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, that is the kind of 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 partners to evaluate and let the models conduct alignment assessments and test model safeguards. And security is not just IT. It is also operational technology as well, and we will hear from CEO of Dragos, Rob, as more systems and assets are connected, will need more of this. The enterprise AI stack requires continuous care within an organization, and we see this market scaling. And I'll give you one stat because you're always looking for stats and proofs on this. In FY '23, we had only four deals that were data and AI led, four. Today, we have just a data point. Now for bringing this to life, I recently had a chance to sit down with my clients and my friend, Kim Krogh Andersen from Telstra, a leading telco in Australia. In 2025, we launched a 7-year JV to reinvent work, customer experience and the ways of working, building the full enterprise stack from top to bottom. Let's roll the video to kind of hear from Kim.

Manish, thank you so much, and thanks for having me. The reason for us coming up with these untraditional partnership, the joint venture, the data and AI avenue that was really to accelerate our data and AI journey, take the 5-year road map and cut that down to 2 years, get the foundation in place and deliver on our ambition, which is to be an AI-first company.

If you look at all the stuff that we are doing, right? I think a strong foundation matters. What measurable returns are you seeing so far from accelerating the data potation 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. And this foundation for us was really to clean up our data estate. We are now down to [ 17 ] data platform. Years back, we were close to 100 data platforms. So that means now we can scale using less tokens, but we can also scale use cases because we have built any use case we do in a repeatable basis. On top of that, we are not just plumbing AI on top of existing processes. Together with Accenture, we have identified 8 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 systems, old products to new products, there we have really used AI to scale that in a very effective way. Reinvented the way we do sales and sales proposition in our enterprise business a way to generate these offers in days instead of ways, we have massive value pools in our network part of the operation. And we, of course, also have massive value pools when it comes to AI in the HR finance, corporate functions inside Helmand 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 took an economics help telcos still 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 plan. the control plane, we have developed together with Accenture, a plane where we get control of each use cases from a sustainability, responsibility point of view. So we monitor any single use case and see if it's behaved as intended. We want to ensure that all the value we get from AI on most of that value is captured to Telstar. Telstar's customer, Australia.

Can you talk about the approaches you are taking at Telstar to enable people and help drive the adoption of AI?

Yes, we have been on a journey when it's come to adoption. The Telstar AI Academy is really a way to systematically give our employees specific AI expertise in a holistic manner. And actually, last year, we have more than 15,000 that all took a cause in that AI academy. We need to ensure that people understand AI because if you understand, you can also -- you know how to use AI in a more secure and responsible way. So that has been -- really 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? Like can you share a couple of examples of [indiscernible]

Energy consumer because we run a lot of infrastructure. So there we have used AI early on. I will say I think the network and the network operation 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. And Accenture were the partner we looked at that had the most aligned ambition and we're most aggressive also because AI is about pace. We need to ensure we're in front of the pack. So we needed a partner that has access to all the new knowledge and always on top of what's coming next. We also needed a partner that we 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 the industry.

Thank you, Kim. Thank you for your time.

Welcome. It was a pleasure. Thank you, as always, Manish.

So I think you heard from Kim described 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 '23, four 50 million-plus deals, four 50 million-plus deals. And today, we are talking about 50 -- 50 million-plus deals. Because I might have lost in my speed that I forgot to mention because there are large-scale reinventions driven by data and AI, 50 million-plus. Now I want to now move to the fourth area. I'm still in the core and still trying to tell you how we are going to grow the core. And I'd like to highlight the real big -- and I think one of the most exciting things is about AI growth arenas. Now AI growth arenas are entirely new categories of demand created by AI. They did not exist 1 year back. AI is opening new possibilities and new budgets at almost every part of enterprise and with the new bias 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 don't want to kill you guys, only two of the arenas. One is agentic commerce and the second one is software-defined vehicles. Now 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 0. We didn't have the service. Today, it is $1 billion, and we have already won $125 million as we speak. Today, it is $1 billion, and we have already won $125 million 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 the ship. My friend, Daisy, and you meet her in a short time. She says, think of this as iPhone on wheels. -- is a simple explanation about that. Again, very small at the beginning of this year, on Jan 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 now how we organize for growth. And 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 40 million to 50 million-plus deals and the AI group arena. There's 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're 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 this, 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's talk few of them. I want to talk about Accenture construct, DLB and Learn Vantage. So before we get into Accenture construct, I would like to share a little history first, really show how we build a network of businesses. In FY '22, we had a capital business of about $300 million. We saw the opportunity early, AI is digital, but it needs physical infrastructure. We move fast marrying existing capabilities and adding targeted acquisitions like Answer in August '23. And then we got DLB in July '26. 4 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's 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 Europe -- in EMEA. 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 reengineering reinvention partner, we can now bring the full range of capabilities for which our clients need. Think '19 and '20, we couldn't serve them earlier. Now we are there ready to serve with a pretty new capability. Next, DLB. Data centers are one of the clearest examples of AI driving capital investments. DLB associates bring 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, Learn Vantage. As I said, we have got nine. I'm talking about period, we will dig into slightly even deeper in the panel. Learn Vantage is an AI-native learning platform serving a $110 billion market. As workforce capability is becoming a constraint on AI adoption, Learn Vantage 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, right, we will selectively expand our network into new markets. And I'm really looking forward to our next launch where we will bring to market products built using our deep industry and functional domain expertise. So I think the 9 will become 10, and it will continue to grow. So 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. And when I say the power of Accenture. We have got the world's largest client account lead who serve who are a trusted adviser who had orchestrate us in more than 4,000 clients across the world. Largest, I think, the intelligence as a trusted adviser, which is what we kind of bring. Now 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 last year 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. And I want to bring back to this chart, which is we have expanded our addressable market by 1.5 trillion to roughly $3 trillion. That is the math, and I kind of -- I was giving you a lot of times, but I wanted to summarize this again for you. And 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's a reinvention partner lead for supply chain and reengineering; Rob Lee, he is the CEO of Dragos. Our network of businesses function focused on OT security; Marc Warner, CEO of Faculty.ai, another network of businesses and now also the Chief Technology Officer for Accenture.

So I will try to moderate the panel, but these guys are a bit unruly. So sometimes a 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 3 decades is just the incredible talent we have. And for me, when I just there's four leaders walking and I get these pumps like wow, we see who can -- who in the planet can have this kind of leaders. So I'm going to start with Lan. I'm 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 be in kitchen English? Well, otherwise, and I talked about it being the new systems integration work, but just explain to our investors and analysts. So what we are talking about in this

Sure. By the way, you did great. So 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. So Accenture builds an enterprise AI stack, and you can think of that as the industrial kitchen to scale AI. So since ChatGPT launched, we have done -- our team has done 18,000 projects. So we know where companies stand. Most of them have baked the cake in their grandma's kitchen, so to speak. So now it's time for them to get industrial kitchen. So that is equipment, repeatable processes, quality controls so that all of them can make the cake consistently and safely for millions of times. So that's what we mean by enterprise AI stack. So this is not a quiz. Manish showed a 7-layer cake earlier. I -- this is what I do every day. 7-layer cake has data knowledge, models, agentic core, governance, security and safety, scale AI operations and then user front end, all of these need to be built on top of robust AI infrastructure. So my point here is made is only 1 ingredient. You need everything else in the kitchen to bake the cake. So 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 services before. The stack needs to be run all the time. Why? Because model would drift, data will get out of shape over time. Also, we believe that redness drive demand. Because Manish, I hope you agree with me, the industrial kitchen cannot be filled on top of some kind of a crumbling foundation. So you talk about companies who 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 the 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 stack, and that is why I got Lan to -- Lan, one client example where you can illustrate where you're seeing the -- how we are deploying this?

Yes, 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 AI travel companion for a large airline. So Manish, I don't know about you, but to me, when I think about personal tree planning is what I -- is full of what I call moments of anxiety. There just in the air. So 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 now your customer of your airline. I think I have $500 credit from the past cancel 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? So this is an everyday question, but we have to build a stack to actually get the work done. So just 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 you have to give model the contact that is very, very important. We integrated a lot of data from airline. We also leverage a lot of airlines knowledge documents, lots of them are standard operating procedures, policy document, very long, very messy. So I have to do a lot of work to clean them and actually bring them into AI. And 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, a great hotel. Because great hotel means different things to different people. So this is the kind of work that we do behind the scene and then we build agents. Think about agents 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. And while we're building agents also is very critical for us to make sure that we do governance and safety and security, right, 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 funding, another layer that I talked about earlier, it's 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 get not get locked in. And then agent interface also needs to be highly operational. And then we need to put all this together is almost like the industrial kitchen needs to have a command center that everything is running smoothly. And all of this need to be built on top of a very robust infrastructure. So I think the key takeaway I want you all to have from this example is enterprise AI stack is the link shipping to scale AI. Back to you.

I think you just -- and for me, like whenever I go for any discussion and people say, can you just quickly do some AI and get things out very quickly because it's like a really hard work, right? On this --

I mean -- we see this if you look back at history, always is the technology change to get the value goes hand-in-hand with the process change, whether that's like steam to electricity or containerization or computers -- original computers into enterprise, it's just bringing both together is the only way you ever get the value.

That's why I love this -- Let me go to Rob. New in Accenture is like -- 6 months, you are like 3 weeks -- so happy to see you here. For all of us. Yes, first of all, like IT, everybody is like grinding will go away OT. For you, you develop every night, you are worried about, oh my God, what's going to happen of us like really think about this. And it's going to become a $59 billion market. Tell us, Rob, more about this.

I mean, OT is the physical world. And no one notices it until someone hits the light switch or and talk and the lights go up and down, you go, oh, something is going on. And that's OT. It's the physical aspect of data centers, water, electricity grids, pipelines. It's our world. And all of the money has been spent on the enterprise IT side to secure it. and that's not effective in OT at all. And no CEO is confused about where they generate revenue. It's not the website, it's the operations side of the house. And so for governments and others to figure out that it's not protected, they're free cut out. And we see it happening. We see 700 supermarkets across France in the last week, refrigeration units, turning up to heat, spoiling food, fires and supermarkets, people are scared. They're looking for partners. They're looking for answers. They're looking for solutions. So for Dragos to have the technology for Accenture to have the reach, it's hitting a time in place that everybody is taking this seriously and needs an answer and it simply hasn't been done before. And you can't have an AI revolution or space revolution without energy and infrastructure. And you can't keep it very long without OT security. So I think it's just wonderful that we're doing it today.

I first met Rob in Dragos. It is pretty quick. Actually, it looks like it was yesterday, right? And it was -- I had a good tutorial on OT from Rob. He came to meet and was and I we together and we were really having a time. But it's just -- I think just shows again a massive opportunity that we have and how we are going to build on this. And with that, I'm going to go to Tracey. Now that every time he gives me this example and I start wondering, getting worried. But -- you are right in the middle of all the factories and all the plants and the maintenance and everything else going on. How has AI and security got to be designed as you are building this stuff?

So first of all, I am so glad you're with this. Because my best friend in what I do and what our teams do. So we are seeing AI in supply chain engineering across the patch, right? So it is early days. But if you think about it, R&D and engineering, right, core part of our clients' business, we're deploying AI with clients now to figure out new discoveries, formulations, new products. I mean an engineer spends 40% to 70% of his time depending on industry, looking for data, doing documentation, redoing engineering drawings and then trying to get it certified out the door, right? So agentic is brilliant for that space. Second, once we've designed a product, we have to make with the source the product and the materials. So we're seeing AI and how we look at alternative materials and sourcing. We're seeing how we can leverage it for optimizing spend and used to be we just cover the top categories of spend. Now we can cover all the categories of spend, thank you, AI, right? Then once we have the materials and we've designed this product, we got to make it. manufacturing right, in facilities. I couldn't agree more. It is the heart of the client's business. It's literally the crown jewels. And we're seeing AI being deployed with our clients, with our help and driving optimization, production, yield, quality, energy usage, right? Almost every client is looking at this on how they can save money but also create growth. And then 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 customers' demand and the signals tie-up together to drive more resiliency. But we can't scale any of this without what Lan said, which is we got to have our OT data modernization in order. We've got to have the data foundations available. We got to have it secure. And we got to bring our workforce, our engineering and operations workforce and supply chain along in this journey, right, to be able to do this. Let me give you an example of -- from a leading industry. So 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 7 years working on data foundations. So the core data foundations. And what does that mean? Well, it's across 20 plants. It's connecting 25,000 machines, 25,000. And I love the example of the billions of data for airline, but this is 5 billion data points a day, right? That's real-time operations and production, right, so that we can have cars. Now that's interesting for the visibility and how that all comes together. But they've already saved by doing that and being able to look at what's happening in the lines, they've been on to save EUR 120 million a year, and they've been able to improve by 50% the ramp-up time for new cars, okay? So that's growth. Now that they have this amazing data foundation, they're figuring out how do they do an agenetic layer on top to create an entirely new operating system for factories, right? 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, right? That's unbelievable. But the reality is what Julie said earlier, and that is, most of our clients are not there yet, right, on this journey on how they can bring that data set together, right? 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, right? So 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, very beginning. So to answer the second part of your question about OT security and body over here, it's absolutely imperative. It's not a nice to have. We cannot do the dial in the AI in these critical parts of our clients' business without OT security.

Rob?

I mean I love hearing this. I think it's the critical part of critical infrastructure. And again, people understand that outside these rooms and in the field. And no CEO wants to have a loss of human life, right? No national security leader wants to have velocity of life. And that's what we're talking about when we talk about cyber attacks on OT. It's catastrophic, it's power grid failures. We've already seen people try to kill people through cyber attacks. Nobody wants to talk efficiency in comparison to loss of life. And everybody wants to secure those facilities. So 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. And 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. And the combination of those two things is a good mission -- but of course, it's a huge market. And 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 with the doom and gloom guy at the panel. Yes.

And the thing which Rob was talking about not many people really understand the implications. And that is why I said I got my first tutorial from him in January in Davos. But then let me move to my next tutorial that I got, which was with Marc. So I met Marc in London when we were in the first discussion. We were near the white board, and we were fighting with each other who will take the pen on this. But Marc, we first met you and what I really liked about Marc 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. And they talked about safety 10 years back when it was not very cool. Now everybody is suddenly looking up about safety, safety, oh my God, oh my God. But like these guys were talking about it 10 years back, but Marc, tell us about what does safe mean in the world of models?

Yes, 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 that it would also just be more impactful. But I think sort of similar to what Rob and Tracey 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. Safety, 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 -- imagine a car you have your brakes, which are sort of fundamentally a safety system. But if you want to do the fastest times growing around the track, you don't throw away your brakes. It's getting the safety systems, the brakes and the gas working together effectively to get us the fastest times. We think AI will be basically identical to that. And we're seeing it in practice. So in the U.K., we did one of the first agentic system builds in the finance sector for new bank called Tai, a growing business bank. And actually spotting the fraud there is to help them do for detection. Spotting the fraud was quite easy it was building all the systems around that, many of the things that Lam was talking about actually that really took the time to get it right. And then once you do that, the -- like the value is just obvious and the organization can adopt it much, much more effectively.

No, like, again, -- this is where I tell you, like you can get anything away from the discussion, but just see the talent and the wisdom that these people have. So talk to us about applied AI. We talk about this, but you are not only safety, you are at the forefronts of Apply solving large business problems for life sciences clients and others. Talk to us about the launch of this new lab that we are talking about.

Yes. So I mean we think of ourselves as an applied AI company. So we started in 2014, back when there was only really people doing sort of 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 a meaningful way. So whether it was making education better or health care or products cheaper, all these kind of things. So we actually coined the term applied AI to sort of illustrate what we wanted to specialize in. And right now, there is basically a sort of open problem which is AI is this extremely dynamic technology. Every day and week, months, certainly, there are new releases and the capabilities are just increasing and increasing. And organizations don't know how to bring that into their businesses. And so together with Accenture, we are going to invest in something that we're calling faculty lab, which is an organization that's going to sit at the intersection of from problems and real enterprise context, so that you can act like organizations can actually start to understand how to bring this into their businesses. So think about something like software development. If you want to use coding agents as an individual, there's a ton of different blocks 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. And that's a disaster when it's about 3x the number of software engineers that operate in enterprise as compared to start-ups. And so we're just not able to get the value out of the technology at the moment. But soon, we will be able to. I mean our -- 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're going to have 10 or 100x that budget in the lab and a much broader remit. So I think we'll be able to see some equivalently exciting things come out.

you got what excited as usual. Now Rob, I'm going to come to you. You are running a very, 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, right?

Yes. I mean for first, like Accenture has already been doing this. When I started this company 10 years ago, nobody was really doing a lot of OT security. It wasn't really a market. Investors weren't looking at it. They thought it was crazy. I remembered getting laughed at plenty of time in Silicon Valley. And now it's the biggest market 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 flooded with the idea, but they didn't stick with it. And nobody in manufacturing, nobody in oil and gas, wants to see somebody whose first OT environment is their OT market. That's just not going to work. So 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. We don't 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 there are things that people haven't done before. Every CISO knows how to evaluate the next security technology in an IT market, they just need help. But not if they've 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 is going on. It's not anything that you've been through before. You need somebody to turn to. And so for Accenture and Dragos to combine that credibility, that authenticity, the expertise the technology stack, it's just something that everybody has been waiting for. And 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 #1 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. And 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 like focus and everybody is kind of talking about IT for a long time, OT is going to be one of the biggest, I think, expense 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 the printer. Nobody has never said like, "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. And all of that is just OT.

Yes. My answer is firing. Now I'll go to Tracey, back to you. Tracey, I think for the investors, I think they see us as an IT and we're doing all the functions and everything else. People with hard hats running around pace, right? Give us a window into like AI doing into this world of yours?

I love that hard hat. And steel...

I want to be the picture there.

Yes, a bit. Multiple things. So 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, right? So one. That's kind of the R&D example around manufacturing, a 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, right? 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 Manas. You'll be happy to know that you get really good, consistent manage as well using a digital twin. I use those examples a little bit jokingly to bring it home. But the reality is we're 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. And then the last example is then the hottest topic, sizes OT of core and besides AI and all these other things that it's really physical AI, right? One of the latest things and we're helping our clients figure out how they move things with robots and other capabilities. And one of the challenges with doing physical AI is that often to deploy it, you have to stop production, right? We don't like to stop production. If you go into a warehouse, we're talking millions of packages that are running 24/7 to go out the doors, right? So we partnered 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's going to work with humans on a shop floor. And then once we have the right layout, the right setting and the right design, then we go deploy it, right, facilities. That is the future of physical AI and where things are going, doing things before they physically get put in. So those are just some examples. Our clients, frankly, need help, right? This is messy, it's complex, it's mission-critical for sure. And now they're looking and saying, how do we help people, 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 would just link what Tracey just mentioned to the graphics we're showing earlier, $300 million grown to $1.9 billion, 55% compounding rate of growth. That is why it is so exciting. Thanks for sharing. Now Lan, I'm going to end this conversation with you. Everyone here, we get new models coming out. There's open bet 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 model selection and the open-bid model, what does the clients need?

SP-6 Absolutely. So it's really hard for me to follow the race car example, airplane example. I don't know what I'm doing here. But to me, Manish, this is pretty straightforward. I think the logic is this model are super powerful, but they are not easy to use. So what we are seeing is companies not getting value and they pull back. So 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. So Manish, you and I see this in the earlier days with cloud. Companies were signing a very large significant consumption commit, but buying capacity is only the beginning. So we were the ones who actually help them move the application, connect the data, change the way they operate it so that those spend come in actually turn into productive use. So we're 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. So that is the dilemma. How do we get them on stock? Three things: First, we may model work. We work with a lot of 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 5 people here, what are your favorite models? I will likely get 50 different answers because there are 100 of models and new models are coming out every week. So in fact, Manish, the tokenomics research that you and I did a couple of months ago, actually prove that there's only 10% to 20% of the enterprise workflow justify the use of the frontier model capabilities. So many companies just started realizing that not every model, every workflow deserves the most expensive model. So that is a 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 wave models so that they can have better control over their data. Also, as you know, we -- just a few weeks ago, we launched our full life cycle services of helping companies onboard, manage and run open wave models in their secure environment. Yes, you heard it right, full life cycle services. So 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 health care and banking because they cannot lead their data and also the cost of managing their model is extremely critical. And regulatory compliance is nonnegotiable. So we got -- too excited about talking about models here, but as a veteran in this business, I've been doing this for 20-something years, I cannot have thought and thrilled to be leading this business. And 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. And when she says we did the economics, paper, you did it. We see an incredible team. I think they kind of did it. I think just wanted to kind of end this with kind of saying that we see a massive opportunity. We see a lot of white space in everything that we do. We see millions of hours of work, that work that needs to be done in deploying some of the technologies that we have just been talking about. I think the -- again, the model for us is the same, right, which is identify the opportunities early, invest, build organically, acquire and kind of scale with the Accenture's power. But that's kind of what you kind of got from the team here. But thank you for listening, and thank you for the discussion. I think we will continue the discussion over lunch. But now it's back to Julie.

Thanks, everyone. Great job. We now have a short break. So can join us and be back in your seat at 10:45. 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. Thank you. [Break]

Before that, we're 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. And so first, we're going to roll that video, and then we'll go directly into John and Mauro, and then we're going to have a client join live from London. Let's 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's that both companies share a fundamental belief. We know that real value is created when enterprises use innovation to reimagine the way they want and core. 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. And 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, essence and accelerate decision-making. Accenture and SAP helping clients to do exactly that. batting SAP business AI across their core operations to create the autonomous enter points. 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 blood to support our customers on this journey with change management and help them unlock the maximum value out of AI for their business. And as we do this, our partnership will only grow stronger. Accenture doesn't just advise clients on SAP transformation. They live it. They won many of their own mission-critical systems on SAP Technologies. And 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 adviser 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's what SAP and Accenture deliver together, 50 years of partnership. And this is just the beginning.

For nearly 5 decades, Oracle's help organizations run their most critical operations. We understand their data, their industries, and what it takes to deliver results. Today, we're 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've already built more than 300 custom agents in Oracle's AI agent studio, including agents for finance and procurement. And with our advanced intelligence engine for Oracle, they have delivered sovereign AI solutions across the globe. That work has helped make Accenture our #1 partner globally for Oracle ARR 1 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'm excited about what we'll deliver together next.

I'd like to say a few words about Workday's partnership with Accenture. It's 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 to their toughest transformations. What sets Accenture a part is simple. They understand Workday for 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 scale, expertise and reinvention mindset to help make that happen. Better don't talk about it, they live it. Accenture is one of our most advanced and for leading 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 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 higher score before we bring them to market. And that co-innovation translates directly into real impact for joint customers like GE, Venova, Salesforce and Question 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 built together, and even more excited about what is ahead.

It takes an ecosystem to change an industry, and that's 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're living through the greatest technology shift of our lifetime. CEOs don't need to know the pilot. They're 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 9 months, and Accenture has been instrumental in helping our customers turn innovation into impact. We're only just getting started. Accenture became the first partner in our joint forward deployed engineer program to really drive exceptional results. We're bringing our engineers closer to customers while unlocking over 300 prebuilt 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 #1 part 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 over the last two decades, what we've done together, customer success, innovation, incredible. And I would just have to say that it's all built on the foundation of trust that both of our companies value so highly. 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 AI Force platform. Well, the results were incredible. So 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 cannot 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 5 regions. And Accenture has been our Customer Experience orchestration Partner of the Year for 6 years now, and we're really proud to partner with them with hundreds of clients -- joint clients across the world. When you think about the work that we have delivered for clients helping them deliver personalized experiences at scale to all of their customers, millions of customers around the world, over 1 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. And as we go into the world of AI, what's really important is helping our clients get the value of AI faster, more cost efficiently, securely and accurately. And that's 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 8 of our specializations. So they really cover the entire range of Adobe technologies across these 3 critical areas of creativity, productivity and customer experience orchestration. And 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. And with me, I'm 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'm always wishing America does just a little bit better.