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You can’t cut yourself to growth: Phil Fersht with Julie Sweet
510 Plays17 days ago
In the latest episode of From the Horse’s Mouth, Phil Fersht is joined by Julie Sweet, Chair and CEO of Accenture, to discuss what leadership looks like when macro volatility collides with technology advancement. In particular, they explored why cost cutting alone won’t drive enterprise growth.
As organizations race to scale AI, Julie made one thing very clear: ‘You do not cut your way to growth”. The conversation pushes beyond experimentation into accountability, how enterprises scale adoption across the enterprise, and the importance of nurturing the next generation of talent.
This episode tackles the real questions facing enterprise leaders: How do you drive growth, protect talent pipelines, and reinvent yourself at scale? And how do they do it all at once?
What you’ll hear in 30 minutes:
- Why “you do not cut your way to growth” in the AI era
- What it means to commit AI initiatives to the P&L
- The core differences between proof-of-concepts and enterprise scale
- Why volatility is forcing significant reinvention
- How AI is reshaping entry level jobs, and why preserving them matters
Guest Snapshot
Julie Sweet is the Chair and CEO of Accenture, responsible for 800,000 employees across approximately 120 different countries. After 15 years at the firm, she became the CEO in 2019 and has guided them through a global pandemic and the rapid advancement of AI.
Explore More
Phil Fersht on LinkedIn: https://www.linkedin.com/in/pfersht/
HFS Research Website: https://www.hfsresearch.com/
Julie Sweet on LinkedIn: https://www.linkedin.com/in/julie-sweet/
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Transcript
Introduction and Julie Sweet's Role
00:00:00
Speaker
Hello, welcome to the latest edition of From the Horse's Mouth podcast. I'm your host, Phil First. And today I'm very excited to be joined by the one and only Julie Sweet, who's the CEO of Accenture. Hi, Julie, are you doing?
00:00:15
Speaker
Hi, Phil. Thanks for having me today. Well, i know we haven't caught up in a while, but it's great to see you. You're looking well. And what's it like running a company of over 800,000 people? Just you give us a little glimpse into what you do on a day-to-day
AI in Leadership and Client Understanding
00:00:29
Speaker
basis. Sure. Well, I have to tell you, and i I know we're going to jump into AI at some point, but a big part of what I do every day is work on AI. So, you know, one of the things that people talk to me a lot about is you know, how do you keep up and and, you know, thinking about all the different developments. And, you know, for me and my entire leadership team, you know, AI, learning about AI, thinking about how it works for clients is a part of the daily job.
00:01:00
Speaker
And then second part of the daily job is clients, right? So, you know, one of the things I think people find sometimes surprising, i mean, I spend approximately 50% of my time working with clients. And I don't mean just meeting a bunch of new clients, but really sponsoring programs myself, diving deep with clients when we're doing new things, And then the third element is, of course, around our people and thinking about, you know, how, especially right now, we're continuing to rotate our people. But those are three. I mean, I've got all the other stuff you have to do as a public company, but those are kind of the three ways I think about my day. So how much has changed in the
Industry Changes and Volatility with AI
00:01:42
Speaker
last...
00:01:42
Speaker
two years in the industry. I mean, what's you're very connected to CEOs right across the Fortune 100, etc. How much is changing for them, do you feel? you know I'd say that the thing that's changing the most for CEOs to begin with is actually the macro.
00:01:59
Speaker
And so while AI is this incredible new powerful tool that every CEO is spending a lot of time on to figure out, you know, is it can it be the solution they believe, you know, in its power?
00:02:15
Speaker
What's changed in the last couple of years, though, is kind of the increased in ongoing volatility Yeah.
00:02:28
Speaker
you know if you take the u s a lot of the gdp growth here is tied to the tech companies right underneath that growth is not so attractive and companies are really struggling And so managing the macro is really the huge thing because in the last two years, it has become more uncertain, more volatile.
00:02:51
Speaker
And then you add to that that at the same time, there's and this incredibly powerful new tool that leaders five years ago didn't have. And so thinking about at the same time is there some way to address and be more successful by harnessing it, requires a very different level of energy and understanding at the CEO and the C-suite level, because this is not plumbing.
00:03:18
Speaker
The AI's real value is in the core of the business, And you're not touching your core with the new technology unless you deeply understand it. There's a lot of challenges today.
00:03:29
Speaker
It's super exciting. I wouldn't trade this moment. And I talk to CEOs all the time. None of us would trade this moment. It is a incredibly exciting time. You feel a huge sense of responsibility and an opportunity to make an impact. But it's definitely not the same as it was even just a few years ago for CEOs. Wow. So how has this changed the world of
Growth and Challenges in AI Capabilities
00:03:53
Speaker
Accenture? What challenges have you encountered and how are you dealing with that? well Well, first, maybe before we start with the challenge, i you know I'm really proud of, and it's also a like a representative, like just how fast we're changing. I mean, Phil, you know as well, let's go back to November 2022 when ChatGPT emerged. We had 30 people working on Gen.AI, right? We had 40,000 data and AI professionals.
00:04:18
Speaker
In a really short amount of time, you're looking at Accenture where we have 80,000 AI and data professionals, right? We've done 11,000 projects, right? we were We were at a handful just, you know, three years ago, not even three years ago. So it's tremendous to see how a company, you know, we've always embraced change. When I interviewed at Accenture in 2009, that's what the CEO said to me, that the company you're, you know, you're joining is not going to be the same company in three years. But even in that history,
00:04:51
Speaker
the way we have built this business is enormous. Now, what are the challenges? The challenges are that our clients actually have an opportunity to use this powerful new tool in every part of their business, and they're looking to us to rapidly figure that out for them, right? To come in with that point of view. And so keeping up with the pace of the demand, you know, is something where we have to educate people faster, right? We luckily have all of the the ecosystem partnerships that help us understand and get ahead. But the demand for reinvention from our clients is enormous. And that's where we spend a lot of time on how do we invest and how do we move our own people to be there faster? Because that's what our clients want. Yeah. I mean, people talk reinvention.
Client Readiness for AI
00:05:40
Speaker
And I know you guys, you know, you talk about it a lot.
00:05:43
Speaker
But do you think clients are truly ready to reinvent themselves or they know they have to and they're just struggling to figure out where to even start? Phil, I would look at it from two perspectives. From an industry perspective, in every industry, there are clients who are ready and who are executing. And mostly that's because in every industry, and I mean every industry, even like sort of industries that would typically lag, like a chemicals industry, right?
00:06:11
Speaker
And that's because over the last decade in every industry, you have leaders who've invested in their technology and their data because as a threshold matter, before you even get to leadership and mindset, if you don't have the right data foundation, if you're not mostly in the cloud, if you you know haven't really changed your architecture over the last decade, it's very hard to scale.
00:06:35
Speaker
right So every proof of concept can work because you force data into it. right Actually taking it across the the company is a big challenge. The second bigger challenge, though, is having more than the CEO, like actually having the CEO and the C-suite really committed to actually changing. We talk about changing the way you work, changing your workforce and changing your workbench, like how you use AI.
00:07:02
Speaker
And one of the biggest challenges is the CEO may be ready, but what a company has to do is to commit and put the outcomes in their P&L and create plans around that. Like when Accenture did a few years ago, we said we're going to we we weren't using all of our own services and we... We wanted to get to and a minimum of $1.5 billion dollars in savings in our back office. That was built into the plan that was underneath the guidance I gave, right? There was no, like, these were the KPIs that I measure the company with.
00:07:35
Speaker
And what we're often seeing is that, like in particular, AI and reinvention tend to be projects that we're not signing up for in the P&L, right? And until that happens, it's very difficult to
Leader-led Learning and AI Transformation
00:07:52
Speaker
scale. So what does it take, in your opinion, to drive commitment and accountability for AI adoption? You talk about business plans and performance objectives and feedback loops, but what do you think it really takes to drive this commitment from the client side? Well, the first thing it takes is leader-led learning, right? Because, you know, actually lots of people coming in from the workforce in entry-level jobs are a are already AI, you know, native, right? But for for leaders, you have to understand the technology, and the technology is not what we're all using every day to, you know, have better search, right? It is actually what does this technology do? What are its limits? You know, where is the technology? And that requires an in-depth understanding that is not like the old, you know, digital of yesteryear where you could go on a digital safari to, you know, Silicon Valley and you knew enough to say, OK, let's go, you know, move to the cloud. Right. And so one of the things we did is we started ah a business unit called Learn Vantage around training. But we're doing a lot of work with leadership teams around actually the in-depth learning because it's it's not one session. Right. Because until you understand the actual power of the technology.
00:09:06
Speaker
It's hard to commit and it's hard to understand why, you know, Accenture comes in you know, and and we're saying, here's your process today. Here's what the process needs to look like with advanced AI. And it's not just advanced AI because, you know, that's. sort of another question, but all of these solutions are using all site sorts of AI, right? Because advanced AI isn't accurate enough in all parts of a process. But regardless, it's if we come in and say, here is what you do today, here is how you radically need to change it
00:09:41
Speaker
That's hard to commit to with all the people, the change management. We've done things, especially in the core of the business, you know, for decades, unless you truly understand the power of the technology. So how's that changed Accenture yourselves
Accenture's Internal AI Strategy
00:09:55
Speaker
as a business? Have you had to dig deep into the skill sets within your own organization, way that you look at your own process? Have you been through a ah reinvention that you feel you can go to clients with? Yes, well, first I'd sort of back up for a moment and think about like, so we always like to be our own bus credential. And so when we approach AI, we approach it for ourselves the way that we approach it for our clients. And so, because an AI strategy is not the strategy that of the company. There's a business strategy of the company, right? So for an Accenture, When, you know, if you go back to when ChachiPT first happened, right, we had a single leader, our chief strategy officer, who was our former chief technology officer. who we said who sort of we said an initial strategy where we we basically said there are three kinds of ways we're going to use AI. There's the what we do for clients, there's how we deliver for clients, and then there's how we operate Accenture.
00:10:56
Speaker
And we have to prioritize where we would do the investments based on our business strategy. And our business strategy was very clear. We had to take an early leadership in AI.
00:11:06
Speaker
And so that meant initially a lot of investment in creating the solutions for our clients. Right. So that's why we've had extraordinary sales, five billion dollars in revenue. Right. Because we said first things first before we start doing it at Accenture, we in terms of how we operate the third category, our business strategy said, like, put the resources there.
00:11:29
Speaker
We also were undergoing in our own back office at the time, we were actually undergoing the cleaning up siloed processes, using our own services, using all the the technology platform we had. And we said, we're not going to start, for example, when agents came, using agents on a process where we already thought we had too many people or too many steps, et cetera. This is real life, right? Like we often are going to clients and saying, you should use this as a catalyst to figure out all the cleanup that you need to do that gives you immediate savings before you start to use like kind of the new technology. So we are absolutely, you know, at this point on the third category operating, using it to, you know, reimagine order to cash, right? We already started in marketing. We use all our own services. So we're doing a ton of it, you know, in our Synops platform that we use for our operations business.
00:12:23
Speaker
But I share that story because the answer for our clients is they do need to prioritize. And they need to make sure a lot of, you know, just like us, like you have to pay for this along the way. And there's so much value. And I can give you very specific examples of where, you know, we're delivering value using advanced AI, but that a big part of the value starts with cleaning up the processes. it's like companies having to address things they've neglected for years are now forced to.
AI's Impact on the Services Sector
00:12:52
Speaker
Now, how is this impacting the services industry? and I think we saw IBM stock go down 13% because of a COBOL announcement from Anthropic this week. But how is this adversely or proactively impacting services from your experience, Julie? i think If you look at the market, there's a lot of factors going on in the market, including a lot of misunderstanding. IBM's a great example. We've been using Claude's, you know, the prior model to refactor cobalt into Java already, right? So the new one is even better at that.
00:13:25
Speaker
It's actually only about 25% of the effort of moving from the mainframe to the cloud, for example, because actually the hard part is all the architecture, etc. When we look at mainframe, there's a massive opportunity right now with IBM's new Z17 server. It allows you to now modernize in the mainframe. And our view has always been it's going to be a hybrid. There are certain workloads that should be in the cloud, like things like consumer facing. So like in retail bank, because you are constantly changing or things that require a lot of compute, like risk modeling. But, you know, things that require 100 percent uptime that are super intense, low latency, like checking and and processing, you know, interest rate changes, et cetera, every day. Like these are the kinds of things that you need. And they belong in the mainframe. The challenge was the lack of agility before and the ability to use AI, right? So we see things like being able to do the coding better just makes it now less expensive to do the mainframe modernization and the move to the cloud that makes sense. So we see that as a huge opportunity because banks haven't and insurance companies haven't moved that far because it has been expensive, right? The technology hasn't been there. That's a great example of an announcement that went out that sort of isn't fully understood as to, you know, what are the implications for that. There is so much opportunity right now to take the new technologies and other technology advancements and to do what I call, you know, to like help do make the impossible possible, right? And you want those kinds of investments, and that creates for the services companies, as well as for the technology companies, new opportunities. That's a very hard, you know, that's not being necessarily heard by the markets, but that's what we're executing, you know, day in and day out.
00:15:20
Speaker
At the same time, of course, like this also opens up, you know, challenges like in every technology. i mean, you remember with RPA, right? We used RPA. It eliminated thousands upon thousands of jobs in the services industry.
00:15:35
Speaker
And what did we do? We went after growth, right? We used that, that opportunity, and more than offset it by what does RPA then allow companies to do and how can we help those companies do that? And what are the new areas that you need to go through? And I've been saying this for, you know, at least two and a half years because everyone over-tilted on productivity with AI.
00:16:01
Speaker
You do not cut your way to growth. AI will
Reinventing the Services Industry
00:16:04
Speaker
benefit all when AI is the engine for growth and productivity. Couldn't put it better. You can't cut your way to growth. I think that's fantastic. So do you think the way services are set up today across, when you look across the industry, you look at your competitors and some of your partners, do you think our industry gets it? Do you think we're set up to drive companies along this path? Or do you think We're staring at a lot of interesting failures as we as we look at the next couple of years. I think our industry is like every other industry. It has to reinvent itself.
00:16:37
Speaker
And I'm making a bet on our entire industry. I mean, Accenture, I believe we're the best position and we're leading, but I bet on our whole industry. As it as an industry, we have reinvented ourselves. You know, when you went from on-prem to SaaS, when you went to digital, And you know you have serious leaders who under understand that yeah there's a big reinvention ahead. At Accenture, right we are leading the way because we are creating the solutions for our clients.
00:17:09
Speaker
We are also changing the way we deliver. And we are trying to work with clients to also change things like commercial models, which I know is dear to near and dear to your heart, right? Because, you know, we believe that the future should be much more about outcome-based models. The biggest constraint there is not actually the services industry. It is clients wanting to move to outcome-based models. As you know, that's, you know, not – it's easy to say. Actually executing on that with procurement officers and you know is not so easy. But know we're committed as an industry to to evolving our commercial models to meet the moment. And our clients need that as well. They don't want to take the risk around technology. right like When we bring a platform, like what we do in our IT or in our operations business, right We're taking the technology risk. We're making the investments, right? And our clients like want to continue to have to do this. They don't have the expertise. They don't want to have to build things that they don't need to. They want to spend their money on things that are going to make them really different in the market. So I believe our industry is committed to reinvention. We are all reinventing. And you know there's a there's one certainty, only one certainty in this whole AI.
00:18:34
Speaker
AI will not be successful unless adopted. And that is what our industry helps clients do. So are you seeing certain industries moving faster than others and taking the lead maybe because of competitive pressures or all that sort
Industry-specific AI Leadership
00:18:49
Speaker
of thing? I go back to like kind of what I said earlier, which is this time around, unlike with digital, there isn't like certain industries that are majorly lagging because in every industry there is somebody who's pushing ahead. And the reason I emphasize that, Phil, is that sometimes I get these questions like, oh, U.S. versus Europe or which of the industries. And for every CEO, the only thing that matters is, is there someone in their industry that's going to get there first? Yeah. And where when we were doing digital, and you'll remember this, there were whole industries. Energy was massively behind in cloud, right? like and and and that And everyone could be complacent because of that, right? Insurance lagged banking. Like, we all remember that, right? It is different. If you're a CEO in an industry today, you have to know That in your industry, there are players who are pushing ahead and you cannot be complacent that the whole industry is just going to be, you know, later. So that's one point. Now, where do you see industries doing more and where we're doing more? It is completely tied to two things.
00:19:58
Speaker
What was their tech stack to begin with? right So banks, for example, have done a lot of investment in technology, so they're kind of more ready. And then second, what is the usefulness of the technology today? So today, Gen.AI and agents are best in things like customer service, marketing, summarization, helping banks upsell because you put data in their hands, right? And so you're seeing industries where they have that need going faster because the technology is ready, right? So today, the technology, if you're going to stick it in the grid or stick it in you know asset management, right, it has more limitations just based on where the technology is today, the security and all of the things around it. And I think that's an important thing to understand is that you have to look at both the technology and stack, like what's starting with it. If you don't have data, for example, hard to scale. But also, where is the technology itself in terms of where is it ready to be deployed at scale? And that's why you have like consumer banking, you've got consumer goods and retail able to push ahead in certain areas faster that if you're a you know a manufacturer, you know you're not doing because you don't have the same needs.
Procurement Process Changes
00:21:17
Speaker
We talked about the shift to outcomes and you can't cut cut yourself mayor to growth with AI.
00:21:24
Speaker
Are you generally seeing clients realize that they have to change how they procure services, to how they engage with companies like you? Or do you feel that's moving very, very slowly at this point? I mean, the actual mindset of clients realizing we can't just do things the same old way. Many of our clients do recognize that. And we have some forward thinking clients. I would say that as a whole, it's moving slower than I think we would like as an industry. And so we're very focused on working with clients and getting input from clients on how to do this ah Our clients are saying, look, we need a win. They understand we need a win-win for them and for us.
00:22:05
Speaker
Right. And so we're focused on working with the ones that are ready and hoping that that will then create momentum later. I love that everyone needs a win-win, right? And, you know, let's fix
AI's Future Industry Transformation
00:22:16
Speaker
up a bit. You were at the Davos conference recently, and, you know, it's great opportunity to just talk with politicians as well as other CEOs. Did you come away thinking differently about this pace of change and what what clients need to do? Well, one of the messages I left Davos with, i was asked to speak at a dinner on the final night, and I predicted that this would be the last Davos where a i was the topic. And what I meant by that is that we think that, you know, next year it's going to be less about AI generally and more about what industries have been changed
00:23:00
Speaker
because of AI. So let's take, for example, agentic commerce. you know LLMs, so the models, are going to become the next mall.
00:23:11
Speaker
but This is a brand new channel that didn't exist before. We expect there to be a ton of progress over the next 12 months. We're deep in this. And so next year at Davos, it won't be about, hey, this is coming. It'll be about how is this changing the industries that go direct to consumers, right?
00:23:36
Speaker
We really are at that point where there are enough real people use cases and and things that can be material that we think, based on the work we're doing with clients right now, that 12 months from now, the conversation will start to really shift to how industries are being changed, not could be changed. Yeah, yeah. Well, mean, we're just talking about 2022 and ChatGPT, and it's only 2026, and the change is being significant already, right?
AI's Role in Economic Growth and Jobs
00:24:09
Speaker
Now, obviously, we have elections coming up this year in the US. I think AI is becoming a little dirty word in certain quarters you know when I talk to people. Do you think there's going to be more political backlash happening? Do you think there's going to be Are there issues that we're going to have to contend with as an industry as we move faster and faster into this? I sort of take a step back and think about it less around is there political backlash or this or that and more around what do we actually need to do as companies and countries in order to ensure that this powerful technology really benefits all? And i think there's three things we have to do. The first is we do need to use AI as an engine for growth because if you don't, then you just have you know significant unemployment without options. right And part of that needs to be focusing on small and medium-sized businesses. Around 50% of the global GDP comes from small and medium-sized businesses. And that's gonna take, it'll be a big opportunity if some of our clients are going after helping them. It's also something we need to do public private partnerships. Like for example, we're working with um a university system here in the US where we're funding internships at small and medium sized businesses to help them get access to the right talent and to help new graduates also ah ultimately get jobs. So, you know, AI is an engine for growth. The second piece is we do need to reinvent how we learn.
00:25:42
Speaker
And, you know, formal education is no longer a destination. It's a stop along a lifelong learning journey. And that is going to be a change for the private sector.
00:25:54
Speaker
It's a change for the government because the government cannot expect, again, small medium-sized enterprises to be able to fund that change, right, of ongoing skilling. And so there's going to be need to be new ways of doing that. And it's a big change for individuals, right, because... They have to embrace that they may be 45 years old and they're going to have to learn a new way of doing things. And so and then finally, and this is I'm super passionate about, we have to commit to being intentional about preserving entry level jobs. We are doing that at Accenture. We are hiring more entry level jobs in all of our major markets this year than we did last year.
00:26:33
Speaker
But to do that, we've reconstructed those jobs. We're doing different kinds of skilling when people come on board. We're hiring for different skills. And you know the economics don't work if you eliminate entry-level jobs. The building you know future talent doesn't work if you and eliminate entry-level jobs. But this has to be entirely focused and intentional. Otherwise, right you can just you can get unintended consequences of using this technology. So that's what I'm focused on. And I think when you focus on those three things,
00:27:09
Speaker
What you get is it it addresses if there's going to be a backlash, if there's misunderstanding, you know, what's actually happening in the communities. And as an industry and industries, we all have to do this together. This isn't about tech. It's not about services. It's not about any individual. We have to work together to find those solutions industry by industry. And we're spending a lot of time on that, both in paid work, but also in the work we're doing to invest in how to think about this. I mean, I get more questions from my clients asking me for advice for their kids now than ever. Like they, and she said, what should they study? What are they they worried about what their kids are going to do when they finish college, et cetera. It's you know, and a lot of it is driven by this fear of what AI is doing to
00:27:56
Speaker
society and you're you're right, the career progression of of where we all go. But it's fascinating to hear what you guys are doing, particularly in the mid market. That was really
Conclusion and Invitation to Continue Conversation
00:28:05
Speaker
enlightening. This has been like wonderful hearing from you, Julie, and getting a real flavor for where Accenture is and the way you're thinking about the market and the way where things are going. And I really look forward to sharing this interview with the industry. Well, thanks, Phil. And as always, we appreciate you you being a voice for the industry and and bringing voices from the industry to all of our clients. So thanks for having me today. And i really enjoyed the conversation.
00:28:31
Speaker
Yeah, me too. Thank you.
00:28:37
Speaker
Thanks for tuning in to From the Horse's Mouth, intrepid conversations with Phil First. Remember to follow Phil on LinkedIn and subscribe and like on YouTube, Apple Podcasts, Spotify, or your favorite platform for no-nonsense takes on the intricate dance between technology, business, and ideological systems.
00:28:56
Speaker
Got something to add to the discussion? Let's have it. Drop us a line at fromthehorsesmouth at hfsresearch.com or connect with Phil on LinkedIn.