How is one of the largest companies in the world, with more than 730,000 employees, transforming its business with AI? For one, by making large investments. Last year, the professional services giant Accenture announced it was pouring $3 billion into AI over the next three years and increasing the number of its data and AI staff to 80,000 people.
In this episode, chair and CEO Julie Sweet explains why Accenture is laser-focused on AI, how she’s training her people, and why leaders need to be using AI if they want to uplevel their business. Sweet joined Accenture as general counsel after a long career in law. In 2019, she became the first female CEO in its 35-year history.
Three big takeaways from the conversation:
We’re in a “PC moment,” Sweet says. Generative AI’s impact on individual productivity is akin to how the personal computer took us away from typewriters entirely. “It really is a rewiring of the way we work.” For business leaders, though, there is a bigger opportunity: reinventing business processes. “In the past 30 years, there is no single technology except for AI that I have been able to stand up in front of CEOs and credibly and authentically say that it will have a material positive impact on every part of their enterprise,” she says.
Sweet is an advocate of “compressed transformation,” a term Accenture coined to describe the accelerated process of enterprise-wide change as a response to an evolving working world. She says it’s what all businesses must now do with generative AI. And leaders can’t achieve compressed transformation simply by adopting technology—they need “to understand the technology at a much deeper level than other elements of the tech revolution, like cloud.” And most importantly, they need to use it themselves.
Accenture receives roughly 6 million resumes a year and hires about 100,000 people. Even at times when most companies struggle to find talent, as in 2020 to 2022, Accenture managed to add 200,000 employees to its staff. Sweet attributes its success to the “high-tech, high-touch capabilities of generative AI”—to review and identify strong resumes, and then get those resumes to the right highly trained deciders. “AI doesn’t make any hiring decisions for us, but it really helps,” she says. The top two skills Accenture looks for? Enthusiasm for learning and great communication skills.
WorkLab is a place for experts to share their insights and opinions. As students of the future of work, Microsoft values inputs from a diverse set of voices. That said, the opinions and findings of the experts we interview are their own and do not reflect Microsoft’s own research or opinions.
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Here’s a transcript of the conversation.
MOLLY WOOD: This is WorkLab, the podcast from Microsoft. I’m your host, Molly Wood. On WorkLab we hear from experts about the future of work, from how to use generative AI effectively to what it takes to thrive in our new world of work.
JULIE SWEET: I actually started with my most senior leaders, because in order to make the right decisions as a CEO or in the C-suite, you have to understand the technology at a much deeper level than you did other elements of the revolution of technology, like cloud. And we know that it’s not enough to simply tell people and try to train them, but they need to actually use it.
MOLLY WOOD: Today I’m talking to Julie Sweet, chair and CEO of Accenture, a global professional services company that helps businesses, governments, and other organizations build their digital core, optimize their operations, accelerate revenue growth, enhance citizen services, and much, much more. Julie joined Accenture as general counsel after a long career in law, and in 2019, she became the firm’s first female CEO in its 35-year history. Last year, Accenture announced it was investing $3 billion into AI over the next three years, and said it would increase the number of staff in its data and AI practice to 80,000 people. I spoke with Julie about why AI is taking the main stage at Accenture, the company’s own AI journey, and how the organization is positioning itself and its clients to use tech, data, and AI to reinvent every part of its enterprise. Here’s my conversation with Julie.
[Music]
MOLLY WOOD: Julie, thank you so much for joining us on WorkLab.
JULIE SWEET: I’m really excited to be here, so thanks for having me, Molly.
MOLLY WOOD: Let’s jump right into the conversation about the investment in AI. Just last year, Accenture announced its commitment to invest $3 billion into artificial intelligence and double its AI-focused staff to 80,000 people, which is significantly more than most companies even employ. Those are obviously really big numbers, and so let’s start off with, why this big bet?
JULIE SWEET: That’s a great question, and I’d answer it in two ways. So there’s looking at it from the individual and why is it a big bet, and then looking at it from a company. So I’m old enough to have actually taken a typing class on a typewriter. And when we think about the impact on our employees’ and the employees of our clients’ individual productivity, this to us is like a PC moment. Now, I’m not saying it’s like a smartphone moment, because that’s more about being in the world. But in terms of really how much it will change the way our employees do their jobs, it is like when we moved from typewriters to computers. And we’re super excited about that. It really is rewiring the way individuals work, and that requires an investment, both for us as a firm, but more importantly, we’re investing to be able to help our clients go along that journey using our experience, and how we’re going to be able to help them with change. So that’s on the individual side. As a business, in the last 30 years, there is no single technology that I have been able to stand up in front of the CEO of any industry and credibly and authentically say that literally every part of their business, every part of their enterprise, will have a material positive impact on the top line and the bottom line, because of gen AI.
MOLLY WOOD: Wow.
JULIE SWEET: That is a pretty powerful statement. And that’s why we talk about reinvention. But what that requires is not simply the technology. It is investing in, What does talent look like? What does change look like? How do you rewire it based on processes? And a lot of that can be done with Accenture. Investing in advance to be able to help companies do that faster. We like to call that compressed transformation.
MOLLY WOOD: I want a master’s thesis on compressed transformation. Can you talk a little bit more about that concept, because I think that sort of perfectly articulates what we’re all feeling at the moment.
JULIE SWEET: It’s funny, the term first was coined by us during the pandemic because, as we’ll all remember, when we all had to actually face where we were in digital and go online, speed really mattered. And companies started really taking on this idea that they didn’t have to do everything sequentially and that they could move ways of working and cultures much faster than they ever thought possible before the pandemic, because they had to be. And from that time, we as a company really started investing in, What does it take to move faster? As we sit here today and look at the impact of gen AI and the opportunities to change, we’re actually facing a similar moment in that the power of gen AI only comes about when you actually change the way you’re working. And so many clients today, they don’t take the step of saying, here’s the as is, looking at it across the enterprise and not in silos. This is what the to be is. This is how we could actually operate differently. And then build in a view of what that means for tasks and skills. And the way you get to compressed transformation is that you don’t simply say, here’s the technology and, oh, wait, that’s the outcome I want. But you understand the steps that you need to take to actually rewire your company to get to those outcomes, and we believe that that can be done on a compressed time frame when you understand each of the components, in addition to the technology.
MOLLY WOOD: I want to go back to the hiring and the people investment that you have made, this 80,000 AI-focused staff. What does AI-focused mean at Accenture?
JULIE SWEET: So AI-focused, the 80,000, are the people who are getting up day in and day out and helping our clients create the right data foundation and use AI really more on a technical side. So create the right AI backbone or understanding AI in a technical way, and then paired with our industry, our functional specialists, to be able to actually redefine, like, okay, that’s the as is, what’s actually possible? We make that distinction, first of all, because, you know, nobody has that scale that we even have today, we believe, where we started with 40,000 a year ago, now we’re at 53,000. We will—I think, I hope—overshoot our 80,000 by the end of 2026. But that is a certain kind of training and understanding that’s needed. Now on top of that, we have to train everyone at Accenture—we have over 700,000 people—in gen AI. And we start with a very strong basis, because going all the way back to 2019, when we said the next decade would be about using tech data and AI, we started creating Accenture’s future-ready workforce across Accenture. We introduced something called TQ, where it doesn’t matter if you work in workplace—so operating our offices, or you’re a strategist, or you’re a technologist—you have to pass a certain number of assessments on core technologies. So we had already trained 600,000 people on basic, traditional AI—it wasn’t traditional when we were doing it—when gen AI really kind of hit the world. Now we’re of course training all of our people on gen AI.
MOLLY WOOD: And for those who don’t know, you just mentioned TQ, which stands for technology quotient. I actually want to ask you a little more about training, specifically, because one of the first things Accenture did in terms of AI training was create this business case for using Microsoft Copilot, actually as an early adopter. And then I read that you insisted that most senior leaders, the most-senior leaders, be trained first, including yourself, because you said, you know, you have to have leaders who understand the power of AI, and they can’t rely on others. Can you talk a little bit more about that training approach and what it was like for you?
JULIE SWEET: So, maybe a little background, because I think sometimes people will say, like, What’s the business case? And where do we get the value? And we are one of the best learning organizations in the world. We spend over a billion dollars every year, we use learning science and how to train people. And one of the most important things we’ve learned as we’ve pivoted over the last several years to digital cloud and security is that it’s important to have a work and learn, so that you’re not just kind of learning on a computer-based course or even in a classroom, but that you actually use it. So it’s a work-and-learn fusion that’s super important. And so at Accenture we’ll have rolled out to 20,000 of our people, including our most senior leaders, Microsoft Copilot, and my number one point in my business case is that we are going to run Accenture and we’re going to deliver our services to our clients using gen AI. And I need to be able to train our people, and it can’t just be classroom and let me tell you about the power. You have to use it. And so I actually started with my most senior leaders, because what we’re telling all of our clients—and we, you know, we live what we say—is that in order to make the right decisions as a CEO or in the C-suite, you have to understand the technology at a much deeper level than you did other elements of the revolution of technology, like cloud. And we know that it’s not enough to simply tell people and try to train them, but they need to actually use it. So I really emphasize that because every single CEO says that they’re going to transform using gen AI. And they’re not focusing on how you actually make change and how you train people. And so Microsoft Copilot is absolutely essential to change and transformation. Then on top of that, what we’ve seen in our rollout so far is that our people are seeing productivity increases, they’re seeing better engagements because they’re not as tired doing repetitive tasks. And as we’re able to use it in more places, we’re then making the changes to actually go from the as is into the to be. If all you do is roll out Microsoft Copilot and you say, okay, we’ll just use it in that part of your job—now you can summarize notes better—and you don’t say, what’s the opportunity to now change the way we work, to reorganize into different ways to take advantage of that productivity, then you won’t have a business case other than each individual will be more productive. We used to have a lot of people making slides and doing reports, and we had whole groups around that, which we’re now changing because we don’t need those same kinds of groups. We can embed it in different groups. So that is going from the as is to the to be as a part of the transformation. And by the way, I use it every day. My favorite function is the ability to summarize notes at the end of a call. I don’t have to wait for someone else to do it. I look at them immediately and it’s very clear. I can just shoot off the next email. And that is awesome.
MOLLY WOOD: You have been quoted as saying that integrating and using AI isn’t about, you know, to the point you just made, it’s not about reinventing individual productivity, it’s about reinventing processes. And as you start to see that happen, as the productivity gains create the space to imagine a new type of process, how does that then start to feed your clients’ needs? You know, it sort of feels like it’s teaching the growth mindset alongside the adoption.
JULIE SWEET: That’s right. Well, let me just take a concrete example. If you think about a consumer goods company that has a lot of field salespeople, right? Because they go out and sell to, let’s say it’s a food company. They sell to everybody from mom-and-pop shops to big box retail or grocery stores. But they have field sales, which today, prior to the use of AI and gen AI at scale, about 50 percent of their job is highly administrative. That means, by the way, that when they’re hiring people, they hire people that have really good administrative skills. They may not have as great customer skills because, at the end of the day, they’re not getting product out to the customer unless they’re really able to do that administrative work. And most companies have the service, the actual delivery, versus the sales versus the marketing all in different places, and we know that companies struggle with operating in silos. We’re working with some consumer goods companies now to break down all of those barriers and be able to put in the hands of a field salesperson, every single day, the knowledge of things like, you know, Who hasn’t bought from me from the last three months who I should go after? What would be the right pitch based on their service and their needs? So someone telling them, guess what, you guys missed a delivery last month and they were really mad based on their emails. So now when he’s walking or she’s walking into that store, there’s a personalized pitch that takes into account the history, which prior to these tools and using gen AI to be able to look at data that’s not coming out of the systems and that’s coming in emails, that would have taken a lot of work, so it didn’t get done. When you think about, then, the power of this, you suddenly now provided this client with the option to take their field salespeople and either cover more territory or get more efficient and take out the bottom line. You’ve enabled them to, if they have the right skills, build deeper relationships and perhaps introduce different services. And you’ve changed what you need to hire for, because you were hiring for people with lots of administrative skills. Now you can hire for people who are more strategic, who have better customer skills and therefore deepen the relationships. That’s what the power of this technology allows. We had to understand the technology to take it from this incredibly powerful technology to delivering value to those customers who are now better served and have more personalized service to the bottom line because they’ve got efficiencies, and to the top line because they’ve now opened up both new services and perhaps a bigger footprint.
MOLLY WOOD: And you bring up, actually, I think another huge topic, because you mentioned hiring, retaining talent, and being able to do all of those things more efficiently. I’m going to focus first on Accenture, which has over 730,000 employees. I mean, this is a hard number for people to grasp, and 200,000 of that number has been hired in the last couple of years. How have you and how are you leveraging AI in terms of making that process better and expanding the types of skills you might be able to look for?
JULIE SWEET: We get roughly 6 million or more resumes a year and we hire about 100,000 people, not net but total, because you have attrition in that. So, in order to do that, we have used AI for now several years to be able to go through the resumes and really identify who we want to talk to. Then we have recruiting pods that are tuned to the kind—because we hire everybody, from doctors to programmers to, you know, cyber experts. So we hire a lot of different kinds of people. And so AI enables us to sift through the resumes and then get the resumes to the right highly trained individuals to make those choices. So there’s no hiring decision that’s made by AI today at Accenture, but AI is used to really help us. And the proof of how effective it is, is during the pandemic, when most companies were really struggling to hire. We went from 500,000 people in 2019 to over 700,000 people two years into the pandemic. So in the hardest labor market in history, and we were able to do so because of this high-tech, high-touch hiring.
MOLLY WOOD: What are the, not that we’re trying to give people a cheat code to become one of the 100,000, but what are the skills that you look for? You talked about the technology quotient, but I wonder, what are some of the skills you look for and how is that evolving, along with the understanding that the work landscape is evolving with the advent of gen AI.
JULIE SWEET: I think there’s two really important skills. So, one is the question we ask everyone, whether you’re an analyst out of school or a senior experienced hire. And we simply say, What have you learned in the last six months? It’s a super powerful question, because what we know for certain is that the skill requirements and the competencies are changing and that we need people who like to learn and embrace learning. So just think about what we’ve been talking about today. The fact that AI is going to rewire and you have to go from an as is to a to be. Well, underneath all of that are people who are doing the as is, right? And so they have to learn the to be. Think about where I started, where I wanted my most senior leaders to use Copilot to start to really learn, you know, what is gen AI and how can it help us? And so we have to have a company of learners. So we look for that as a competency. The second is that we look for great communication skills. Now, of course, we work with a lot of clients and you’d say, well, maybe that’s obvious. But, you know, I don’t think it’s as obvious to many, many companies, is that if your company is changing, then we often will say about the need to have the ability to change, the ability to bring people along. And that starts with great communication skills. And so this is something that we are both looking for and increasingly investing in building, because if you’re in a constant, we believe a constant state of reinvention due to technology, you have to be really great at change. And to be really great at change, you have to be great communicators.
MOLLY WOOD: It feels like a real opportunity, the way you’re talking about approaching people’s skills from, as a mindset, for example. I feel like consulting is one of those businesses where it’s known for having people from kind of traditional business backgrounds, but also people who get there in unconventional ways. How do you, and will you continue, do you think, to take more non-traditional approaches to finding new talent? And how does that contribute to one of your big passions, equity and diversity?
JULIE SWEET: Well, Molly, first of all, I define myself as an unconventional talent because I started as a lawyer, and I was a lawyer for 17 years before I joined Accenture as the general counsel. So, I absolutely am passionate about both learning and the fact that it’s important to look broadly at talent and to not put people into buckets. Along with that, as you’re alluding to, we at Accenture are very committed to creating new pathways for individuals who may not have the background but absolutely have the potential, including the learning competencies. So in the US, approximately 20 percent of our entry-level hiring are apprentices. And our apprentices come from non-traditional backgrounds but have amazing potential. And we consider that, as we move forward, there’s an even greater opportunity because, for example, we’ll increasingly use gen AI to augment our learning tools and to help people learn. We think that gen AI will continue to open up opportunities to better reskill and upskill people, and so we continue to have that commitment to providing those pathways in our markets around the world.
MOLLY WOOD: So that’s great to hear, especially because there are a lot of questions about data sets and inequalities as it relates to the recruiting process.
JULIE SWEET: Well, I’d really take us to this concept of responsible AI, and that is a new competency for companies. The good news is that Accenture, Microsoft are very focused on building it into our services and to the technology. But, you know, we didn’t have to have a responsible PC or a responsible cloud. AI is a very powerful technology, and therefore, as companies, we need to treat it just like other potential challenges. We all have anti-corruption programs. We all have data privacy programs. We have workplace compliance programs. Responsible AI is a compliance program, and at Accenture, it’s overseen by the audit committee of our board. And what we say to CEOs in the C-suite is that every time you are looking at a use case for gen AI, you should be asking the question, What are the risks and challenges potential in this use case, and how is our responsible AI program going to mitigate those risks and monitor them? Super important.
MOLLY WOOD: And finally, I would be remiss if I didn’t ask you for some advice for business leaders. Leadership is such a key component of compressed transformation. What advice can you offer business leaders in 2024?
JULIE SWEET: I might start with, take a deep breath, right? [Laughter] Because I think, you know, I laugh that I became a CEO six months before the pandemic. And at the time, we said, there’s no playbook. Well, I haven’t encountered anything since then for which there is a playbook, including now gen AI. So we all have to give each other a little grace, as this is certainly a great adventure and one that I feel privileged to have. I do want to emphasize that AI is a technology where the CEO and senior business leaders really need to understand the technology in order to be able to really get the value out of it. Because it really is the marriage of business and technology that gets the value.
MOLLY WOOD: Thank you again. Julie Sweet is Chief Executive Officer at Accenture. We really, really appreciate the time today.
JULIE SWEET: Molly, thanks so much for having me. It was really great to see you.
MOLLY WOOD: Thank you again to Julie Sweet, Chief Executive Officer at Accenture. And that’s it for this episode of WorkLab, the podcast from Microsoft. Please subscribe and check back for the next episode of this season, where I’ll be speaking to Michael Platt, Director of the Wharton Neuroscience Initiative, about what brain science can teach us about decision making, team building, and business leadership. If you’ve got a question or a comment, please drop us an email at worklab@microsoft.com. And check out Microsoft’s Work Trend Indexes and the WorkLab digital publication, where you’ll find all of our episodes, along with thoughtful stories that explore how business leaders are thriving in today’s new world of work. You can find all of it at microsoft.com/worklab. As for this podcast, please rate us, review us, and follow us wherever you listen. It helps us out a ton. The WorkLab podcast is a place for experts to share their insights and opinions. As students of the future of work, Microsoft values inputs from a diverse set of voices. That said, the opinions and findings of our guests are their own, and they may not necessarily reflect Microsoft’s own research or positions. WorkLab is produced by Microsoft with Godfrey Dadich Partners and Reasonable Volume. I’m your host, Molly Wood. Sharon Kallander and Matthew Duncan produced this podcast. Jessica Voelker is the WorkLab editor.
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