Transcripts
Accenture plc's management answers for the business every quarter. These are the exchanges that explain it best — verbatim, from the call transcripts preserved in Sources. Each link opens the full transcript at that page in a new tab.
Q3 FY2026 Earnings Call — Q3 FY2026
The most recent call, and the one where the pivot toward platform and non-FTE revenue gets its clearest articulation. · Open the full transcript →
Management sizes the quarter's two shortfalls: a $100m Middle East revenue hit and large managed-services deals slipping to FY27.
Julie Sweet (Chair and CEO): I also want to give you context on two factors that impacted our results this quarter. First, we were impacted by the conflict in the Middle East. We saw a revenue impact of approximately $100 million compared to our expectations, which was all consulting type of work – split evenly between the direct impact on our Middle East business and indirect effects outside of the region. In the last few weeks of the quarter, we saw this indirect impact globally in Products, and to a lesser degree, in Resources, mostly in discretionary spend. In addition, Sales in the Middle East were impacted by approximately $400 million and also in EMEA due to longer decision-making. Second, a couple of our large Managed Services opportunities moved into FY27 for company specific reasons.
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Cybersecurity compounded from roughly $700m in FY16 to $10bn; the OT platform deal aims to more than triple that addressable market.
Julie Sweet (Chair and CEO): Our expansion into the OT cyber platform business builds on our strong foundation of cybersecurity services, including OT. We have grown our services organically and inorganically over the last decade from roughly $700 million in FY16 to $10 billion in fiscal 2025, a 35% CAGR over the period, 4 times that of Accenture’s over the same period. This investment more than triples our total addressable market in OT Security, which is growing double digit.
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The mid-market defined and sized — clients with $300m to $3bn of revenue, a $240bn TAM — and the new business built to serve it.
Julie Sweet (Chair and CEO): We are also expanding our total addressable market by going after a new, exciting customer segment: the mid-market. We estimate that the mid-market, which we look at as companies with between $300 million and $3 billion of revenue, is a $240 billion addressable market for us, growing high single-digits. That is why we are launching a new business next week called Accenture Edge. This business will embed Accenture’s large enterprise expertise and ecosystem relationships in business solutions designed specifically for the mid-market. We see that companies in this segment face many of the same technology, data, AI, cybersecurity and productivity challenges as large enterprises, but they often need solutions that are faster to deploy, more repeatable and right sized for their scale.
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The stitching-risk question answered: why OT security, why now, and why three assets become one contract for the client on day one.
Tien-Tsin Huang (JPMorgan); Julie Sweet (Chair and CEO): And then finally, just why prioritize security as an enabler for AI versus other areas to win in AI? We obviously trust what you guys have done in the past. We're just trying to better understand, because this seems more strategic than about adding revenue per se. […] Exactly, this is about long-term growth and really a massive market when you start to think about how it's not even about assets. Everything's going to the physical world, right? Physical AI is coming, everything's going to be connected. And so you can't have an AI revolution unless you have critical infrastructure, and unless you secure when you start moving into physical AI, and you can't have that without OT security. 95% of spend in the past has been about IT security, and OT security is a much bigger market and critical need. And we're starting from a $10 billion cybersecurity services business that we've built over the last 10 years organically and inorganically, a 35% CAGR, and we've been in OT security all along. And so one of the things that we do really well is to understand where the technology is going to create demand in our clients. In terms of the platform itself, Dragos has an excellent platform. The addition of NetRise and runZero is just enhancing an already strong program platform. And what companies today do is they have a bunch of fragments, they have to like contract here and they have to contract here and they have to stitch it together. So day one, just the first thing is it's one contract, right? And then we'll enhance the platform, which Dragos has a ton of experience because they've been building that platform. So we don't see risk at all in terms of stitching it. And day one, we're already making companies a lot happier because they can have one buy, not three.
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The four moving parts of the FY27 exit rate, given early: inorganic just under 2%, federal back to growth, deal timing, the conflict.
Angie Park (CFO): Yes. And I think, for us, we did because of the uncertainty that we experienced, particularly in the last three, the last few weeks of the quarter, we did want to make sure that you understood that more of the range is in play. And, Tien-Tsin, I think one of the things that you're trying to get underneath is really around our exit rate and what that looks like going forward, right? So, and I know that that's top of mind for you guys because you use Q4 as that basis, but I want to make sure that I get a few points out for you to consider because this is what we're thinking about as well. So if you think about the acquisitions that we have announced today and the expected closing, we do expect to enter FY27 slightly below 2% of inorganic growth. Secondly is our AFS headwind will sunset this quarter, and we expect that it will return to growth this quarter. The third is related to the managed services opportunities that Julie mentioned and when those actually, when they close in '27. And then, of course, the conflict that Julie already mentioned in discussing with Bryan, that's a variable and we'll see how that evolves. But at the same time, we are executing in new areas, including demand in AI and expanding our TAM.
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Why the commercial-model shift runs through M&A: changing how clients buy long-standing services is slow, new categories start non-FTE.
Julie Sweet (Chair and CEO): And Kevin, in terms of just the profile of that revenue, what you're seeing is that we are moving into higher growth areas. So, we're really excited about the cybersecurity acquisitions that we just announced. That's $208 million ARR growing at 53% [sic 48%]. So that's just an example of how we're using the acquisitions to move into higher growth areas. And they have a different profile in terms of their commercial model. So one of the things that I've said consistently is that in things that our clients have been buying in services for a long time, it's going to take a while to like change the buying patterns, which is why we're making, but it's much easier to go into new categories or to provide new kinds of value and switch to non-FTE models. And so you've seen that with what we just did with cybersecurity. You saw that with Ookla. We announced Alphahealth this week in Italy. That's also a services and platform combination. And so we're going to continue to move ourselves into non-FTE, in part by these acquisitions that will then drive organic growth.
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Token spend gets the cloud-FinOps treatment — a new optimization practice — and so far no material crowd-out of services budgets.
Jim Schneider (Goldman Sachs); Julie Sweet (Chair and CEO): I was wondering if you'd maybe comment broadly on the client budgetary impact that you're seeing from AI infrastructure spending and token spending specifically in terms of upward pressure on their budgets and what impact are you seeing on sort of what you view as to be your addressable TAM in terms of services and even software and are you seeing any kind of change that would kind of drive some moderation in that infrastructure spending to benefit you in the coming quarters? […] So Jim, one of the things we're clearly seeing, in fact, we have a whole practice that we're starting to grow now is on how to help clients optimize their use of tokens. It feels a lot like the cloud scenarios that we remember when people were moving to the cloud and then they were like, “oh, wait a minute, we're spending a lot more on the cloud than we thought” and we built a whole FinOps practice on helping optimize cloud. So we definitely think that we're seeing that with the clients and they're coming to us because we're doing a really good job ourselves of being able to know how you use the tokens, which models you use for which problems and that's something we've been focused on since the very beginning. It's also helping because we have delivered real ROI and our clients are seeing the spend but they're struggling with the ROI and so it's helping us there. And at the same time, there's a certain amount of spending that's going to happen and so we're not seeing it be material to impact the spend on services today.
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Fixed-price work is over 60% and still rising, with no margin difference by type of work — the risk sits inside the guided expansion.
Jamie Friedman (Susquehanna); Angie Park (CFO): And then for my follow-up, last quarter Q2, you had a disclosure about 2025 fixed-price at 60% of work. Can you talk about the evolution of fixed-price? Is that type of work in particular demand and how the margin characteristics of fixedprice may compare to the other dimensions of the company? […] We continue to see our fixed price work be over 60% and continuing to increase. There's no real difference as we look at it by type of work. It's in the similar zone for both consulting as well as managed services. And obviously you see that play out in our margins overall as well. So margins, not a big difference that I would call out relative to fixed-price versus the other commercial constructs, but it is embedded in our 20 basis points of expansion for the year.
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Q2 FY2026 Earnings Call — Q2 FY2026
The best single call on why management believes AI is a tailwind, and the toughest questioning of that claim. · Open the full transcript →
The fixed-price disclosure in full: over 60% of work, driven by proprietary platforms and clients buying cost and delivery certainty.
Angie Park (CFO): Within bookings, the percentage of our work which is fixed price continues to increase over 60% in FY25. This reflects the rising importance of our proprietary platforms and clients’ need for cost and delivery certainty—where our scale, experience, and financial strength matter.
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The cleanest statement of where Accenture sits in the AI stack: models supply the intelligence, Accenture supplies everything around it.
Julie Sweet (Chair and CEO): We play a critical role in the AI-ecosystem. Foundation models provide the “intelligence”; and our role is helping clients understand what to deploy and when, how to integrate it into their systems, reimagine their processes, modernize their data and digital core, help redesign their operating models and do effective change management, and help build the capabilities and talent needed to scale AI across the enterprise. As the technology changes even more quickly, our clients are turning to us to help them navigate. They also want us to help them go faster—sometimes by building their capabilities and other times by leveraging ours.
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The long funnel argued from installed base: hundreds of modern ERP estates were built before advanced AI existed and now have to be redone.
Julie Sweet (Chair and CEO): Let’s look at ERP. We have been the number one partner to all the major ERP ecosystem partners for years, and over the last several years, we deployed modern ERP systems across hundreds of clients. When those systems were implemented, advanced AI did not yet exist. Now those clients want to embed the new AI and data capabilities and transform their end-to-end processes. For example, with one of our largest Oil and Gas clients, we are seeing a clear pattern. First, they modernized their digital core. Over several years, we partnered on a major ERP transformation to implement a cloud-based platform that simplifies operations, standardizes processes, and creates a single source of data across the enterprise. It was a significant, multi-year investment. Now, with that foundation in place, they are investing again—embedding AI directly into the systems that run the business. This is not a separate layer of technology: it is intelligence built into core workflows— across finance, supply chain, asset maintenance, and field operations. These capabilities analyze large volumes of data, initiate routine actions, and support better decisions in real time. The impact is tangible: faster cycle times, fewer manual steps, lower operating costs, and stronger operational resilience. We are beginning to see this same sequence more broadly—modernization of the core, followed by AI-driven enhancement. Enterprise systems are becoming the platform that allows AI to deliver value at scale.
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Asked for hard evidence that Accenture is a net AI winner, management concedes there is no clean metric and names what it does watch.
Jason Kupferberg (Wells Fargo); Julie Sweet (Chair and CEO): What kind of quantitative evidence should investors be looking at to help substantiate the view that Accenture is a net beneficiary of AI. […] Thanks, Jason. I would just start with that at this point in our business, AI is permeating everything we do because it either is driving why clients are actually doing things like moving to the cloud. But when we're doing something that isn't specific AI, they're looking at our AI credentials because everything is aimed to get to AI. And then of course, we have direct AI and then our managed services business is being evaluated by how good our platforms are and their expectations of building AI. And so like to start with, like your first kind of way of looking at is, how is our business performing relative to everyone else and are we taking market share, right? That is the – because at this point, it's not isolated, right? It really is why we're winning and it's – you have to have it to win – you have to be leader to win at the levels we're winning of like $22 billion. And then we're going to give you metrics, Jason, over time that will change to kind of tell you. And so today, we look at market share, we look at our overall growth. And then the metrics we're giving you are the ones we're using, which is because everything is so tied to the big ecosystem, is our growth with that ecosystem outpacing overall growth? And then how are we doing with the emerging players? And then we are looking at how many companies are initiating AI with us among our client base, which are the metrics we gave you today. So the metrics will change, right, but they'll reflect what we're looking at as we drive our business.
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Why a better frontier model does not translate into bookings: the model is the engine, the wheels and transmission are the work.
Tien-Tsin Huang (JPMorgan); Julie Sweet (Chair and CEO): Julie, appreciate your comments there on why it's a tailwind. But I was just thinking with these frontier models that are improving so quickly, it's driving a lot of news flow and a lot of debate. And are you seeing any correlation? Are you tracking this how these models and how they're improving and their capabilities improving and how that might impact your bookings growth and conversion to revenue? I'm just trying to understand if there's some kind of correlation or pattern and how that might impact your numbers here going forward as the frontier models improve. […] It's a great question and I think it goes to the heart of kind of what's diferent with models versus when you release functionality in a packaged solution as we've seen in the past, right, is the models are basically just a super powerful engine. So if you think about the car, right, you've got this great engine, only if it's connected to everything, if it has wheels, so you can actually make it run and the transmission to guard it. And so, when the models come out, there isn't a direct correlation to bookings or new work. But what it does is create the next opportunity for us to look at what are the solutions that it's going to now create. And so if you think about in earlier days, a lot of the work was focused on things like summarization and content creation, the better the models are, it's able to fuel things like moving into agentic – where you – and we're starting to see that. So we're starting to see more experimentation and use of agents really basic workflows as the models get better. So think of the release of the models as the beginning of creating new opportunities for us to take to our clients, even as a lot of work that we're doing based on everything that has already happened.
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The honest split on AI demand: 78% of the C-suite now says growth matters most, but efficiency use cases are still what gets bought.
Julie Sweet (Chair and CEO): But with respect to AI, how would you characterize the mix of advanced AI work between growth or revenuegenerating use cases against the eficiency-led use cases? We hear a little bit of a pickup on the growth side, but love to hear what you're seeing on-the-ground there on the mix shift. […] So I think the first shift that's happening is the focus. It is not yet in the mix. So, our latest survey that we do every quarter of the C-suite and how their view of AI, the latest survey had 78% now saying we think growth is going to be the biggest value. That's not yet translating on-the-ground to being the biggest driver, mostly because of where the technology is. If you think about kind of the early days, a lot of it is about content, summarization, et cetera, that is really an eficiency play. And as the capabilities improve, you start to see more ability to take it into the core business and to do more complex work. So we are absolutely seeing an uptick in growth –growth-focused AI programs, but eficiency is still leading the way. I will tell you that the most exciting area right now on growth is conversational and agentic commerce. Demand is surging there. And I think as that – and that's where we're investing a lot, I think as that takes of, you're going to start to see real results from on the growth side from these new developments and that's a whole new market and it's a whole new opportunity for us that we're super well positioned, of course, because of Song.
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The capital-allocation doctrine: buy into higher-growth adjacencies to fuel organic growth, now with data and IP that break the FTE link.
Jonathan Lee (Guggenheim Partners); Julie Sweet (Chair and CEO): Can you help us understand what's driving the step-up in deployment and whether this reflects a shift in acquisition strategy toward larger or earlier-stage assets, higher multiples in the market or perhaps a pivot toward IP-led deals? […] So, our strategy that we've executed over the last decade or so has been to use V&A often to go into new areas that are higher growth. So, we did that with Accenture Song. We've done that with Industry X, you saw us do that with capital projects over the last few years. And that is all to fuel organic growth, right? So, it's increasing our total addressable market by going into new higher growth areas. And that's again what you're seeing us do that. And we're doing that in key AI enablers. And so those are things like data centers, energy infrastructure. We're doing that in big secular trends like defense. You've seen those acquisitions over the last couple of years and public sector is another one. Education is another one. So, higher growth areas, increasing our TAM. And then increasingly, we see an opportunity to meet unmet demand in the market where you don't have solutions where we can build products either organically or by purchasing them. So, our Faculty acquisition, for example, has a really unique decision intelligence product. And then in addition, there are new commercial models where data is one of the key enablers of AI. And so you saw our Ookla acquisition, which is really about an incredible data set. And the way that then gets into our business is in the network is really core to both communications and all enterprises and to use AI, having this kind of a dataset is incredibly powerful and it's a completely diferent commercial model, a licensing and subscription base.
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What the pivot costs: higher multiples and a smaller immediate earnings uplift, accepted for higher growth and margin later.
Angie Park (CFO): Yeah. And so, in some cases, we are paying higher multiples than in the past. So the immediate uplift is lower in those instances than prior acquisitions. So that said, we are intentionally shifting towards higher growth, higher margin assets that are going to fuel organic growth and strengthen our capabilities, and it's really to position us for long-term growth and returns.
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The compression question head-on: if AI collapses an ERP migration to two weeks, why is that not a smaller TAM for integration work?
Jonathan Lee (Guggenheim Partners); Julie Sweet (Chair and CEO): As a follow-up, one of your partners recently highlighted the ability to reduce SAP ERP migration workloads to as little as two weeks using AI, how do you respond to concerns that AI tools are compressing project timelines, relative rate cards, and reducing the TAM for systems integration work? And are you seeing similar compression in your own engagements? And if so, how are you ofsetting this through volume or new service oferings? […] So, in general, you should think about our strategy is always that the more that we can use technology to bring more value to clients faster, the better it is for our business. And that's the strategy you've seen us execute ever since RPA really burst on the scene in 2015, because when you can actually make, especially the technical piece of it go faster, there's so much work, all the process change, all the change management, et cetera, that like the SAP deals are multi-year and those often become gating items that they're not investing in other parts of the technology landscape or other parts of the business because they are these huge projects. And so, we see this as whether it's in ERP or mainframe, it helps, because the actual technical piece is a small piece compared to the rest of the work and it leads to more work. And so, for example, just last week, we were at AIPCon Palantir's conference with SAP, Palantir and Accenture on stage saying we're going to develop those products. They're really not developed yet at scale in any way. But we're working together because it will be a net benefit to our clients, which means it will be a net benefit to us. That's how we think about it.
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Q4 and Full Year FY2025 Earnings Call — Q4 FY2025
The annual call: FY25 in full, the guidance convention, the talent rotation and the reorganization into Reinvention Services. · Open the full transcript →
What the AI figures do and do not include — the disclosure boundary behind $2.7bn of revenue and $5.9bn of bookings in FY25.
Julie Sweet (Chair and CEO): Our early and decisive decision in FY23 to invest significantly to become the leader in Gen AI with a $3 billion multi-year investment is clearly paying-of as we capture this new area of spend for our clients. In FY25, we tripled our revenue over FY24 from Gen AI and increasingly agentic AI to $2.7 billion. And we nearly doubled our Gen AI bookings to $5.9 billion. And as a reminder, these numbers only reflect revenue and bookings specifically related to advanced AI, which is Gen AI, agentic AI and physical AI and do not include data, classical AI or AI used in delivery of our services. We're now going to use the term advanced AI as it encompasses the latest developments that are starting to gain traction.
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The talent rotation stated plainly — upskill first, exit fast where reskilling will not work — alongside the single-unit growth model.
Julie Sweet (Chair and CEO): In addition to continuing to hire world-class talent, in FY25, we developed and are implementing a refreshed robust three-pronged talent strategy to rotate our workforce. We are investing in upskilling our reinventors, which is our primary strategy. We are exiting on a compressed timeline, people where reskilling, based on our experience, is not a viable path for the skills we need. And, we're continuously identifying areas of how we operate Accenture to drive more eficiencies, including through AI in order to create more investment capacity. […] Finally, our growth model. On September 1, we launched reinvention services, which brings all of Accenture's capabilities into a single unit. Nearly 80% of our large deals are multi-service. The model as we fully roll it out will make it faster and simpler to sell and deliver everything Accenture ofers and to rotate our oferings to embed more AI and data and equip our people.
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The roughly $865m charge decomposed: compressed severance for the talent rotation plus divestiture of two off-strategy acquisitions.
Angie Park (CFO): Before I move on to the details of the quarter, I want to spend a moment on the six- month business optimization program we initiated in Q4, for which we recorded a charge of $615 million and expect to record an additional approximately $250 million in Q1, for a total of approximately $865 million over the period. The business optimization program has two parts. One related to rapid talent rotation that Julie mentioned, which reflects severance associated with headcount reductions that we are making in a compressed timeline, and second, related to the divestiture of two acquisitions that are no longer aligned with our strategic priorities. These actions will result in cost-savings, which will be reinvested in our people and our business.
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Why enterprise adoption lags the mindshare — and why management treats that gap as its demand pool rather than a threat.
Julie Sweet (Chair and CEO): It is well recognized that advanced AI has taken the mindshare of CEOs, the C-suite and boards faster than any technology development we've seen in the past two decades. At the same time, as reported widely, value realization has been underwhelming for many and enterprise adoption at scale is slow other than with digital natives. This is why our clients are turning to us. We know that the gap between mind share and faster actual adoption is because the enterprise reinvention required to truly unlock the value of advanced AI is hard and has significant costs. There is a huge diference between how we're all using AI in our individual lives that is incredibly easy and what it takes to use it in an enterprise. The opportunity for AI is at the intersection of business strategy and tech and org readiness. For most companies, the biggest gap between mind share and adoption is tech and org readiness. We're still in the thick of cloud, ERP and security modernization. Data preparedness is nascent and many companies grapple with fragmented processes and siloed organizations. Generations of leaders need new skills to understand how AI should inform their business strategy. The workforce needs new skills to use AI and new talent strategies and related competencies must be developed.
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The guidance convention that recurs every quarter: the top of the range assumes no change in discretionary spend, the bottom allows decay.
Tien-Tsin Huang (JPMorgan); Angie Park (CFO): I wanted to – my first question I'll ask on visibility on revenue growth, if that's okay. Just love to hear your thoughts on visibility compared to the last couple of years given the backlog, which is quite big with large deals, you have the pipeline, of course, and then what you're seeing on discretionary spending given the economic backdrop as you see it? […] As we look at FY26, we feel really good about our positioning. And so as you said, you saw our strong bookings of $80.6 billion in FY25 that positions us for FY26. We can see our backlog from the large deals. And if you look at our pipeline and looking at our pipeline, it's solid overall and we see strong demand for our large transformation deals. From a discretionary perspective, what we've assumed is at the top-end of the range, there's no change in discretionary spend, while at the bottom of the range, it allows for deterioration. And by the way, as you think about our guidance of 2% to 5% excluding AFS, we're at 3% to 6% for the year.
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The core bull case in management's own words: client AI savings are not lost, they fund the next item on an effectively unlimited list.
Tien-Tsin Huang (JPMorgan); Julie Sweet (Chair and CEO): Just give us your latest thoughts on AI driven productivity and those gains and how they might unfold. I get that question quite a bit from investors. Do you see potential deflationary efects and how might that impact Accenture services both positively and negatively? […] Great. Thanks, Tien-Tsin. So we don't see AI as deflationary. We do see and are seeing it as expansionary similar to every tech evolution we've been through. The move from an analog to digital, from on-prem to cloud and SaaS, and is many of you who have been with us over the course of the years have known, in every successive tech evolution, we've become stronger. And so if you look at AI, we see the same thing. Yes, AI absolutely boosts eficiency in areas like coding or operations, but those savings don't disappear. They're being reinvested into new priorities. The list of what our clients want to do with technology is truly virtually unlimited. And so when we can save them money by delivering our services with advanced AI, that frees up their budget to do the next things on their list and that's what they're doing. They're always going to those next priorities and we're best-positioned then to help them. That is how we delivered our 7% growth last year. I mean, two years in, we're seeing the pattern for how that journey to advanced AI is expanding our business. And by the way, I will add that one of the most consistent things that I'm telling CEOs today is that their AI strategy has to focus on both growth and productivity. And almost every CEO that I've talked to says they pivoted way too far toward productivity and not enough to growth, which of course, we are helping them with, with things like Song. And we give that advice really from our own experience in how we have successfully grown through every tech evolution, embracing the productivity on one-side and then capturing the opportunity it creates on the other side by helping our clients.
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A disclosure question answered candidly: data is kept out of the advanced-AI figure so the new-spend number stays clean.
Jamie Friedman (Susquehanna); Julie Sweet (Chair and CEO): I wanted to ask, Julie, about the way you're defining advanced AI. And I think if the transcript is right, you say Gen AI, agentic AI and physical AI. I'm actually asking about why you're saying you won't – you're not including data because we've sort of been trained that data is foundational. So why is the data component not in the definition of advanced AI? […] Because what we're trying to help share with you is how we're taking spend in a new market. And by the way, data is absolutely critical. In fact, one out of every two projects in Gen AI, agentic AI, physical AI now has significant data pull-through. So our data business is on fire, right? Like this is an absolutely critical area. Companies are just getting started. It's nascent in many places. It's part of the digital core that we're building. It's just that to date, we've wanted to share with all of you transparently the really new areas.
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Where the savings go: over $1bn from the optimization program is reinvested, leaving only modest margin expansion on the table.
Bryan Bergin (TD Cowen); Angie Park (CFO): Can you talk about, maybe assumed savings you expect to achieve from this optimization plan and how it may help you evolve your operations? I'm specifically curious if you see that kind of combined with Gen AI adoption internally, allowing you to operate at a sustainably higher utilization as that did tick-up this quarter. […] I think that for overall, we expect savings of over $1 billion from our business optimization program, which we expect that we will reinvest in our business and in our people because it's so important for our future growth. And so we expect to reinvest that while still delivering modest margin expansion.
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Q2 FY2025 Earnings Call — Q2 FY2025
The shock call: the GSA federal contract review disclosed live, and the thesis tested on how much revenue was really at risk. · Open the full transcript →
The disclosure that reset the stock: GSA told agencies to review contracts with the top 10 consultancies and terminate the non-critical.
Julie Sweet (Chair and CEO): First, Accenture Federal Services. Federal represented approximately 8% of our global revenue and 16% of our Americas revenue in FY ‘24. As you know, the new administration has a clear goal to run the Federal government more efficiently. During this process, many new procurement actions have slowed, which is negatively impacting our sales and revenue. In addition, recently, the General Service Administration has instructed all federal agencies to review their contracts with the top 10 highest paid consulting firms contracting with the U.S. government, which includes Accenture Federal Services. The GSA's guidance was to terminate contracts that are not deemed mission critical by the relevant federal agencies. While we continue to believe our work for federal clients is mission critical, we anticipate ongoing uncertainty as the government's priorities evolve and these assessments unfold. Based on our significant experience across federal and commercial clients, we see major opportunities over time for us to help consolidate, modernize, and reinvent the federal government to drive a whole new level of efficiency.
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How management framed the March 2025 shift: uncertainty sharply elevated since December, industry fundamentals asserted to be unchanged.
Julie Sweet (Chair and CEO): Second, in recent weeks, we are seeing an elevated level of what was already significant uncertainty in the global economic and geopolitical environment, marking a shift from our first quarter FY ‘25 earnings report in December. At the same time, we believe the fundamentals of our industry remain strong and we are very well positioned with our clients because all strategies continue to lead to reinvention through new ways of working, tech, data, and AI. We are confident in executing our strategy to help clients reinvest. As you would expect, we are laser focused on bringing tremendous value to our clients. Our strengths lie in our agility as the market we operate in changes, utilizing our deep client and ecosystem relationships and our leading position in Gen AI and technology more broadly. We are also well diversified across markets, industries, and types of work, which enables us to continue to lead in a changing market context as we have done before.
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Pressed to quantify federal exposure, management declines to split it: 8% of the business, the range is the disclosure.
Tien-Tsin Huang (JPMorgan); Julie Sweet (Chair and CEO): Is there – maybe to ask it differently, just is there a way to frame the real revenue at risk? I know mission-critical is, maybe hard to define it here on the call, but is there anything that you can share in terms of what's really at risk or not at risk thinking about duration or is it really more of an issue of replenishing work, etc.? Just trying to get a better understanding of visibility there. […] Sure. And so, Tien-Tsin, what I would say is, and what we've been clear about is the guided range we're giving for the quarter and for the year reflects our best view of the impact that's coming from both the slowing of new procurement actions and the assessments of the work that we're doing, and so we don't get into different pieces of it, but – those two things, the range of outcomes and that's reflected in the range. I mean, it is 8% of our business. We have lots of other parts of our business that are about that size that we are always looking at estimates and assumptions. And so this is our best view of it today and the range reflects it.
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A precise correction of the premise: uncertainty rose in recent weeks, but management says no slowdown had shown up in the business.
James Faucette (Morgan Stanley); Julie Sweet (Chair and CEO): As we talk about the little bit of the slowdown that you've seen in recent weeks, how would you characterize it geographically or industry vertical? Just trying to get a little more color there. And what do you think those customers are looking for in terms of their, proceed or continue to pause or hesitate, type of decision making? […] Thanks, James. I want to be clear, we haven't seen a slowdown in the last few weeks. What we commented on, which I think is kind of everyone is well aware of is in the last few weeks, there's been an elevated level of what was already significant uncertainty and there's a couple of big themes around that, obviously tariffs, and that's a global discussion. That is not just an Americas discussion. And also consumer sentiment, which is a little bit more of an Americas discussion. And so we're really just commenting on what I think we're all seeing and that's only been in the last few weeks, and so we're already, of course, in the heart of the discussions of clients globally who are talking about it.
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Do clients claw back the AI savings? Managed-services contracts already assume technology-driven productivity, so the model is unchanged.
Keith Bachman (BMO Capital Markets); Julie Sweet (Chair and CEO): But are you seeing any changes in the nature of your economic relationship with your customers? In other words, are customers asking for some of the savings or is there any change in that narrative on how the supply side and economic relationship broadly speaking with your customers may unfold as Gen AI matures a little bit? […] So I think in the first question, what we've been seeing with Gen AI is what we've seen in the past when we have new technologies, like, I take you back to 2015 when we first announced MyWizard, which we now call GenWizard, as we've introduced Gen AI and that was that major shift that occurred with respect to automation, which by the way is still relevant, right? And so that – we are not seeing a different change. We've been continuously – remember like, particularly, on the managed services side, our contracts assume that there's going to be more efficiency driven from technology. Gen AI is allowing that to kind of go up over time. But like the way that the model is working is just very similar to what we've seen with prior waves of big efficiencies from technology. So we're not seeing new patterns evolve there.
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What management says holds the business together through shocks: decade-long client relationships, diversification and ecosystem position.
Julie Sweet (Chair and CEO): And then again, what I would say on the – how things might layer in. CEOs are actually focused on: how do I succeed regardless of the level of uncertainty? So the conversations we're having are not, hey, what happens if the tariffs that – this gets resolved, etc., it's okay. We have a higher level of uncertainty than we did 90 days ago, and so how do we then reinvent faster, right? What do we need to shift to? CEOs, and this is not from – this has been going on for now for a few years, right? They're embracing that their responsibility is to grow regardless of what has been, in my tenure as CEO, in the last six years, a series of a lot of different events. And that's why as we think about our own business, right, we continue to anchor on the characteristics that have allowed us to be the leader over these different cycles, that's the deep client relationships. Our top 100 clients we've been with for over 10 years, the diversification of geographies, industries, I do want to give a shout out to all my industry teams. The industry groups all – we had broad based growth, but it allows us for that diversification as well as types of work and then the all-important ecosystem relationships and our leadership in Gen AI and technology. Those are the building blocks of our resilient business and we all, our CEOs and ourselves have to be agile to succeed in whatever market and that is what our range reflects. The fact that we took the bottom off of the range reflects our belief in our resilient model as we continue to navigate.
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Q3 FY2023 Earnings Call — Q3 FY2023
The origin of the AI strategy: the $3bn investment explained, with a candid read on cost, ROI and how long it would take. · Open the full transcript →
The commitment that set the next three years in motion: $3bn into AI and a doubling of the data and AI workforce to 80,000.
Julie Sweet (Chair and CEO): Our approach to AI is clear. Just as we have successfully done with cloud, we are investing to take an early lead, and position for the opportunity ahead. Last week, we announced a $3 billion investment in AI, a big step to accelerate our clients' reinvention journey, which includes us doubling our data and AI workforce from 40,000 to 80,000 strong, including the expansion of our center for advanced AI that today has over 1,600 generative AI experts bringing new assets such as our AI Navigator for Enterprise to life, and developing new GenAI-powered industry solutions. And across this all, we are leading with responsible AI to be the most trusted source in helping our clients mitigate the risks as they drive value.
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The bifurcation that has shaped demand ever since: small discretionary projects falling away while large transformations hold up.
Lisa Ellis (MoffettNathanson); Julie Sweet (Chair and CEO): Let's dive in on the Strategy & Consulting. I know it was a high single-digit decline this quarter. That – just looking back at your comments from last quarter, I think that came in a little bit softer than you expected. But then you also called out many new projects coming in related to GenAI and other technologies. Can you just talk a little bit about kind of what's changed, what that evolution looks like and kind of what's your confidence level in the time horizon that we'll see Strategy & Consulting improve over the next couple of quarters? […] So the big difference in our expectations from last quarter and where we ended up, really was all in the small deals. And we saw further – they came in lower than we expected, and we saw that extend to Europe and the Growth Markets. Now that was both in S&C and systems integration. But that's the big reason that we have a difference in sort of where we thought where we would be this quarter. Now, our job is to continue to pivot to higher – where there is higher-growth, and we're working on that in digital manufacturing, supply chain, data and AI. But that will take a little time. And what we're seeing is that there's a lot of extensions going on in small deals, but it's the newer, small projects, while at the same time, we continue to have very strong bookings and interest and huge opportunity in transformations.
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The clearest statement of the managed-services model anywhere in the set: at least 10% productivity every year, and how it gets found.
Lisa Ellis (MoffettNathanson); Julie Sweet (Chair and CEO): But can you give your view on how you see GenAI impacting the IT services industry overall? Like, a lot of people make an analogy to sort of the impact of offshoring on the industry and sort of other big sort of step function changes to the operations and the kind of composition and the way IT services is done. Can you kind of give your latest perspective on that, how you see it affecting Accenture and your industry more broadly? […] So think about it first in context of Managed Services. Every year, right, we have to find at least 10% of productivity. So we talk a lot about our platform, things like myWizard and that. That's all AI-enabled. Just year-to-date in operations, not using GenAI, right, we have automated 13,000 jobs and then we've reskilled those people and redeployed them. Our business model requires us to get at least 10% productivity year in and year out. As we're getting to the maturity of automation and AI before generative AI, we see generative AI as our ability to continue to give at least that 10% productivity year in and year out. So in the Managed Services area, we see that more as the ability to continue doing what we have to do as kind of the next generation of technology. Where we're super excited is in software development that is more around our systems integration and our big transformations around platforms because while we do automate there, we think GenAI may provide a real opportunity to do even more. And remember, our strategy is to deliver compressed transformations. So the more that we can find ways to deliver faster and less costly, that's going to be a big differentiator. So we're leaning in hard.
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Unusual candor at the peak of the hype: GenAI is expensive, the ROI is unproven, and the $3bn is a bet on being early anyway.
Julie Sweet (Chair and CEO): At the same time, these technologies are really early. And so for example, we're doing a lot of experimentation now. It's really good for things like documentation, but complex integrations, being able to use them for highly architectured systems, which is what our large enterprises do – GenAI isn't there yet, right? So we think it's going to take some time. We also don't yet know the cost. And one of the things we are really – a lot of clients are looking at us for is to help them with the business case because most of the studies, including our own, are all about what’s potentially [the] uses of it. But because these products aren't out yet, we know that – it's much more expensive to use GenAI, it's much more energy [intensive] [corrected]. And so the actual ROI – so there's the art of the possible, but what's actually the return – it's still really early days. So we're very excited that we can get new kinds of productivity, particularly on things like consulting and systems integration but it's early days yet. And we are leaning in because we think it's a big opportunity for us to differentiate. And that's why we are investing $3 billion over the next three years because we think this is like another Cloud First moment where we were out early, we invested at scale.
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Asked to underwrite the $3bn against the Cloud First precedent, management declines to quantify — a record of what was not promised.
Tien-Tsin Huang (JPMorgan); Julie Sweet (Chair and CEO): So on the AI front, you did mention, I think, the Cloud First. Do you draw that parallel when you guys – I think that was three years ago, you did a $3 billion Cloud First investment. That's paid off very well for you. So I'm curious, do you expect a similar return here on the $3 billion you're putting into AI? How should we measure that? Or is it going to perhaps convert differently in terms of the returns? […] Tien-Tsin, that's a great, clever way to try to get us to talk about more of the future. But what I would say is we've got a great track record of investing and getting a great return. And so we think that it's going to pay off well.
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Where the money was expected to come from: not pure GenAI but the data and digital-core work that has to happen before it.
Bryan Keane (Deutsche Bank); Julie Sweet (Chair and CEO): I get that it's early, but the big question everybody is asking is how long will it take before it moves the needle in bookings and revenue. Is that a couple of years out still? Or is that the time frame and the rapidness of the use of the technology should push it earlier than a normal technology wave? […] Well, Bryan, I think in general, we think GenAI is going to go faster than, say, cloud, right, which took more like a decade. I would focus on – so first of all, we're being very rigorous when we talk about GenAI because we're really saying like what are the actual GenAI. The big growth, we think, is going to be in all the companies that then have to get their data done faster. And we're not lumping that together. And so I don't know what others are going to do, but we're really being very pure in saying like, "Hey, this is pure GenAI." And if you think about where companies are, our research shows like only 5% to 10% of companies are mature right now with data and AI, and they're the ones that are really going to be able to use GenAI at scale. We just had this research done that came in last week that hasn't been published yet. About 50% of companies have not started on their data or AI journey, and everything in between – some are good in data but not AI. They're having a hard time to scale. So where we think growth is going to come particularly next year, the bigger growth is going to be not in like the pure GenAI, but it's going to be in helping companies finish getting their end-of-life data migrated to the cloud. Because you need your data in the cloud, right? It's going to come in the data strategy and the – all the governance and getting it architected while some of the stuff around GenAI gets sorted out. So for example, cost is not there yet. And how do you take data from one cloud and there's cost to take it and put it another cloud. All of that, we're going to be working with our clients and our technology partners – to really create the right business cases. But the growth we think in the near term is going to be from accelerating the digital core. And that's why we feel really good about the bigger transformational deals continuing next year because there's so much work to do.
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More calls
Q1 FY2026 Earnings Call — Q1 FY2026 · 23 pages · Go here for the data-center services thesis: the DLB Associates majority stake and the roughly $12bn addressable market management expects to double by 2030. · Open →
Q3 FY2025 Earnings Call — Q3 FY2025 · 21 pages · The call that announced Reinvention Services, folding Strategy, Consulting, Song, Technology and Operations into one unit from September 1, 2025. · Open →
Q4 and Full Year FY2024 Earnings Call — Q4 FY2024 · 22 pages · The trough year in management's own words: 2% local-currency growth on $81bn of bookings, the completed cost programme, and the CFO handover to Angie Park. · Open →
Q2 FY2024 Earnings Call — Q2 FY2024 · 23 pages · The sharpest description of the discretionary squeeze — “another turn of the dial on constraining spending” — and how it changed the shape of bookings. · Open →
Q4 and Full Year FY2023 Earnings Call — Q4 FY2023 · 24 pages · Useful for the runway sizing management uses (share of workloads still off the cloud) and for how badly the CMT industry group dragged on FY23. · Open →
Q4 and Full Year FY2021 Earnings Call — Q4 FY2021 · 19 pages · The Cloud First precedent that every AI answer is measured against: a dedicated unit taking the cloud business from $12bn to $18bn in a year. · Open →