AI disruption and geopolitical upheaval are forcing business leaders to make high-stakes decisions—fast. Accenture CEO Julie Sweet shares what she’s hearing from her 9,000 clients, and the hard-won advice she’s giving them. Sweet reveals why AI proficiency is now a requirement for promotion at Accenture, why she’s doubling down on entry-level hiring amid the automation wave, and she unpacks the hidden power of “leader-led learning.”
This is an abridged transcript of an interview from Rapid Response, hosted by the former Fast Company editor-in-chief Robert Safian. From the team behind the Masters of Scale podcast, Rapid Response features candid conversations with today’s top business leaders navigating real-time challenges. Subscribe to Rapid Response wherever you get your podcasts to ensure you never miss an episode.
Accenture works across 120 countries, 9,000 clients—you’re in every industry. You have this unique visibility into how organizations and leaders are navigating what is really a chaotic, fast-moving environment. Are there questions that you’re hearing particularly often right now?
Well, Bob, it’s interesting if I just start with Iran, because I’m getting a lot of questions, particularly in Europe, where if you think about a potential energy crunch, it’s expected to hit harder in Europe than, say, the impact on the U.S. Everyone believes that this environment, where energy is a risk, is just their new norm. And actually, there’s more optimism because if you compare this to 2022, when the war in Ukraine started, Europe is in a much better position from a resilience perspective.
And it’s a theme that we’ve been seeing for quite some time. I got the same questions even a couple of months ago when we had this whole issue around tariffs and imposing them, which is that CEOs are really just expecting the unexpected. It’s being built in, and that’s why resilience is such a big theme. There are also big questions continuing on AI, et cetera, but I wanted to address the latest, which is the impact of the Iran war.
When I talk to CEOs right now, there’s this sense that some of them seem almost frozen. They’re waiting for clarity. And I know you’ve encouraged the opposite: Don’t take cover; take chances. How do you know when to act and when to wait?
The reality is, as a CEO you can’t bake anything into your plan, simply because so much is unknown. And that’s where transparency really matters, being able to say, “Here’s what we know. Here’s what we don’t know.” And then we’re making our action plan with those things in mind.
So when you think about when you know to act or not act, in my view you’re always acting. It’s intentional decisions. It’s an action to say, “Because I don’t know this, I can’t alter my plans.” One of the biggest risks right now is even less about the impact on the economy from what’s going on in the Strait of Hormuz and energy. The bigger risk that many companies are talking about is, do we have a cyberattack or an attack on critical infrastructure that spins out of that?
And for that, there are actions you can take, because we’re helping clients look at their cyber resilience. This has already been a big growth area for us because AI itself has increased the attack surface. When you think about what the risks are, you can’t really tell what’s going to happen on the energy front. But knowing what you do know, what you don’t know, and whether there are actions that can be taken—and then acting—matters.
Alongside all this geopolitical activity, there are also the technological shifts that we’re experiencing. You made a bold move last year where you merged a bunch of divisions into a single unit that you call Reinvention Services around AI. You’re coming off your biggest-ever quarter of revenue growth in new business. We see businesses that are not tech businesses that may not be getting the return on investment from their AI that they had expected or hoped for. Does it work in some places and not others? Are there industries and functions that are more fit for AI than others? Or is it more about culture and commitment?
Well, in some ways it’s going to be all of the above. So first of all, we have to remember the technology, while changing fast, is still really early. And there’s a lot of actual value that companies can get before advanced AI. So let me give you an example.
We work with a pharma company that takes drugs to market, and there’s a process that, once the drug is approved, involves lots and lots of regulatory work. So what you write to explain it to the physician takes a long time. We’ve said . . . that you could actually shorten that. Instead of it being months, it could be much faster if you changed the process to be standardized, if you kept your data in one place. None of that requires generative AI or advanced AI, but for most companies, they haven’t done that.
So when we worked with [this company], advanced AI was the catalyst because it enables you, if you have all the standardized processes, to actually create the content faster. But the first piece always could have been done and hadn’t been done. And so much of the work that we’re doing is actually work where companies are saying, “Okay, wait a minute. Before I spend the money on advanced AI, I should clean up my fragmented processes. I should standardize things. I should not have as many people in middle management—completely apart from agents—because why would I spend money to create an agent to replace a manager that I shouldn’t have in the first place?”
Is part of the hope that the motivation for not having done this is, “Oh, the agent or AI will come in and do this for me. I can skip a layer, save money.” And that’s the silver bullet. And if I’m hearing you right, you’re like, “Yeah, maybe not.”
Yeah. I think there was this view at the beginning where companies thought, because it’s so easy, are they just going to do it all? Do I just ask this model, and this model is going to tell me how to change my company? One hundred percent, that is not it. The models don’t know how to change a company. And if you spend money on your current structure just replacing parts of it, you’re at best going to get incremental value.
The real value is to actually reinvent everything you do. And that reinvention doesn’t start just with advanced AI, but with a lot of really basic lessons where companies haven’t had the will to fix things. I tell CEOs every day: “In three years, you should be able to [answer], ‘What did I use AI to make possible that was impossible before?’” Because if the only thing you’re doing is incrementally improving how you’re operating, you’re not going to get the biggest value. The biggest value is in the core operations of a company—things you’re going to be able to do with asset management in any industrial company, things you’re going to be able to do with the grid in utilities.
The tech isn’t completely there yet. It’s still error-prone. That’s why everybody’s tracking things like how long the tech works and the memory piece of it. So where you get value today is anything with customers, because those are short interactions. The tech has to continue to improve, and the strategy has to be, “I’m going to use this tech to do something I couldn’t do before.”
There’s this phrase, “AI-first.” You’ve described Accenture as an AI-first company. It’s something a lot of other players aspire to but struggle to implement. Is it hard to be AI-first? What does it mean?
First of all, it is hard. And the reason it’s hard is that it requires your leaders to understand what AI does. And this is so different from the digital era. Moving to the cloud and stuff, a lot of it was plumbing. So as a leader, you didn’t have to understand it because it was being handled by the tech folks.
To be AI-first, you have to say, “What can AI actually do?” So you have to understand things like, wait a minute, it has to have a certain amount of memory to be able to do something. You have to understand what it’s actually able to be accurate about. And then think about your business to say, “Where can I get a big enough return for using something at this cost?” It starts with leaders having to understand technology in a totally different way.
When ChatGPT first emerged in November 2022, the people who received the most training initially were my top 50 leaders, because I knew that if they didn’t understand the power, they would not be able to help us transform how we’re delivering our services and what our clients could use it for. So leader-led learning is a huge unlock. And then AI-first is asking yourself, “Is this something that AI could do?”
