You can’t cut yourself to growth: Phil Fersht with Julie Sweet

Hi, Phil. Thanks for having me today.

Sure. Well, I have to tell you, and 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 thinking about all the different developments. And for me and my entire leadership team, AI, learning about AI, thinking about how it works for clients is a part of the daily job. And then the 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 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.

You know, I'd say that the thing that's changing the most for CEOs to begin with is actually the macro. 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, can it be the solution they believe in its power. What's changed in the last couple of years though is kind of the increased and ongoing volatility of the macro. And when you kind of dig under economic growth for example, you know, if you take the US, 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. And then you add to that that at the same time there's 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. 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. 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 an 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.

Well, you know, first maybe before we start with the challenge, I'm really proud of and it's also representative of 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. 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 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 joining is not going to be the same company in three years. But even in that history, 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 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.

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, even like sort of industries that would typically lag like a chemicals industry, right? 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 haven't really changed your architecture over the last decade it's very hard to scale, right? So every proof of concept can work because you force data into it, right? Actually taking it across 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. And one of the biggest challenges is a 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 weren't using all of our own services and we wanted to get to a minimum of $1.5 billion 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. 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 scale.

Well, the first thing it takes is leader learning, right? Because you know actually lots of people coming in from the workforce and entry level jobs are already AI native, right? But for leaders, you have to understand the technology and the technology is not what we're all using every day to have better search, right? It is actually what does this technology do, what are its limits, where is the technology and that requires an in-depth understanding that is not like the old digital of yesteryear where you could go on a digital safari to Silicon Valley and you knew enough to say okay let's go move to the cloud, right? And so one of the things we did is we started a business unit called LearnVantage around training but we're doing a lot of work with leadership teams around actually the in-depth learning because it's not one session, right? Because until you understand the actual power of the technology it's hard to commit and it's hard to understand why Accenture comes in 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 that's sort of another question but all of these solutions are using all 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's how you radically need to change it, 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.

Yes. Well, first I'd sort of back up for a moment and think about like so we always like to be our own best 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 of a company, there's a business strategy of the company, right? So for Accenture, if you go back to when ChatGPT 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 set an initial strategy where 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 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 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, $5 billion in revenue, right? Because we said first things first before we start doing it at Accenture in terms of how we operate, the third category, our business strategy said like put the resources there. 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 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 etc. 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 at this point on the third category operating using it to reimagine order to cash, right? We already started in marketing, we use all our own services so we're doing a ton of it in our Synops platform that we use for our operations business 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, 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 we're delivering value using advanced AI but that a big part of the value starts with cleaning up the processes.