Phil Fersht — CEO, HFS Research[00:22]
Excellent. Great to catch up with you again, Yusuf. You know, these are very interesting times, and I think it’s been about a year — or it’s over a year now — since we started getting very excited about generative AI. And obviously, Accenture has invested substantially to develop enterprise-level use cases. I hear about GenAI at scale a lot. But starting this year, how do you see things evolving and developing? I’m very interested as well in where you’re seeing the engagement come from. Is it all IT, or are you seeing a lot of interest from non-IT? If you can give us a level-set on where the business is and how you see this year shaping up.
Yusuf Tayob — Group Chief Executive, Operations, Accenture[01:09]
Yeah, absolutely. I think it was almost a year ago — we were sitting on stage together, Phil, in New York — and we were all still trying to unpack this notion of generative AI, that it kind of was building for a long time but had really sort of hit the scene, if you will, with a lot of enterprise excitement and interest. And as you know, at Accenture, we lean into technology; we lean in very hard on new technology that can help solve business problems. This one is particularly interesting and exciting. And as you know, we announced a $3 billion investment. We are moving from proofs of concept and pilots and ideas into scale, and really getting some meaningful results out of generative AI. And to answer your question, certainly there’s a lot of interest from technology organizations, and there’s a number of technology organizations that have ownership or responsibility for driving generative AI in the enterprise. But certainly the real attention that’s been captured has been by business leaders and by business executives, who I think can see the real power in how this can drive change and how this can meaningfully move up the value curve for the enterprise.
Phil Fersht — CEO, HFS Research[02:36]
Right, right. We talked a lot when we last spoke about this sort of AI-automation continuum, if you like, that you take your clients through. How do you see that evolving? Has this AI-driven automation conversation changed? Is it driving different roles within yourselves and your clients? How is that evolving?
Yusuf Tayob — Group Chief Executive, Operations, Accenture[03:02]
Look, as you know, for decades we’ve always sort of been on this continuous evolution of how do you drive more productivity within the enterprise? How do you drive more productivity out of the operations that we deliver for our clients? And for at least the last 15 years or so, there’s been an aggressive automation journey — basic automation, RPA, to AI as we all knew it over the last several years, now to this notion of generative AI. And while generative AI has captured a lot of attention and become a bit of a catalyst for driving more automation in the enterprise, we’re really seeing it as an opportunity now to talk about that full automation continuum and spectrum. In our Accenture Operations business, where we have about 215,000 people serving our clients, executing business processes on their behalf every day — that notion of being able to constantly drive productivity, drive automation, leverage AI to drive better business outcomes has always been there. Generative AI has really put that on a faster path — both an ability to achieve a bit more productivity, but also to pull in the time to achieve some of that productivity. And it’s really ignited the right conversations.
Phil Fersht — CEO, HFS Research[04:15]
Yeah, I mean, pivoting to GenAI really does seem to be something that’s come naturally to Accenture, right? For most of your Diamond clients — and they may be more from traditional industry sectors — is this less of a technological shift, more of a cultural shift for them? And how are you enabling the shift for them as well?
Yusuf Tayob — Group Chief Executive, Operations, Accenture[04:44]
I love your question, because in every client I talk to, everywhere I go, it’s really sparked a conversation about moving to a culture of innovation. You see business leaders at the table together with technology leaders. They’re talking about solving business problems in a very different way, because again, this thing has captured the imagination of what could be possible. And it really is driving these conversations that to me are about a culture of innovation. How do you knock down silos within the organization? In order to really take advantage of these technologies, you’ve got to have different functional areas working much closer together. How do you put data at the center of everything that you’re doing? Because in order to take advantage of these technologies, you’ve got to be data-led. How do you foster a culture of continuous learning? You see executives at all levels, and their teams, much more intellectually curious about the technology and what it can do — and therefore what new skills they need to develop. So I think you’re right: regardless of industry, regardless of size of enterprise, it really is driving a bit of a cultural revolution — to be one more of innovation, one more of a collaborative sense of enterprise, one that’s data-led, and one that’s about constantly learning.
Phil Fersht — CEO, HFS Research[05:57]
Yeah. Well, let’s talk about the elephant in the room — data. Many companies are only halfway through a cloud migration journey, and now we’re asking them to prep data assets for GenAI. So when it comes to data modernization, do we shout fire in a crowded theater? I mean, what is the plan here?
Yusuf Tayob — Group Chief Executive, Operations, Accenture[06:39]
Look, there’s no shortcut on this, right? As you and I both know — and what cloud has given us, and even before that — well, there’s no shortage of data. So, data proliferation across enterprises. As we talk to our clients, our latest research tells us that only 25% of companies out there are really realizing the full potential of the data that they have. So three-quarters of companies tell us they don’t feel like they’re really realizing the potential of their data, and only 55% — roughly half — tell us they can even trace the data from source to consumption point. So obviously there’s a lot still to be done when it comes to data. And you mentioned cloud, but as we talk about enterprise reinvention, we start with building your digital core. Your digital core is all about being able to put that data in a place where it then becomes consumable and usable to you. Then you’ve got to secure it. And then, as we talked about before, as an enterprise, you’ve got to be data-led in your decision-making, data-led in your process engineering. And that then unlocks the potential of all this technology.
Phil Fersht — CEO, HFS Research[07:55]
Yeah, and then obviously, coming from a process and operational standpoint, how do you see that playing in? I mean, processes are still there; many are still antiquated. They’ve been around for decades. How do we reimagine process to play into this broader GenAI conversation to really make this all work?
Yusuf Tayob — Group Chief Executive, Operations, Accenture[08:16]
It’s a great question. I think this is one of the greatest opportunities we have in front of us. If you think about how transformation has typically and historically worked inside most enterprises — you start with sort of a strategic frame, you look at and build operating models, you rewrite business processes to match those operating models and execute that strategy, and then typically you put in systems to be able to drive efficiency against those processes. And even if not waterfall, it’s oftentimes a serial process — you’ve got to do the process before you can do the other stuff. The beauty of this technology is that we’re finding it’s much more of a virtuous and continuous cycle. If you’re using generative AI correctly, if you’re using AI and tech correctly, it is informing you — it is proactively telling you about your process inefficiencies, about your process gaps, about trapped value that sits between processes in the enterprise. And so, leveraging that tech to inform process change that should happen — and as you get that process change, then seeing from the tech the value that you’re creating — it’s much more of a continuous reinvention. It’s much more of a continuous change, and it’s much more of the tech and the process and the people working in tandem versus working in a serial mode.
Phil Fersht — CEO, HFS Research[09:47]
I think that’s a very good way of putting it. So what do you think we’ll be talking about in the beginning of next year? Do you think we’ll still be talking about GenAI, or is it going to evolve into a broader value?
Yusuf Tayob — Group Chief Executive, Operations, Accenture[10:01]
Look, I wish I could predict it. When you and I were sitting here a year ago, I probably couldn’t have predicted we’d be this far along, as far as we’ve come. But I do think generative AI is one of these things — as you look at the evolution of technology — where the promise is real. If you look at where we’ve really been able to capture value so far, it’s in just a handful of functions: things that are customer-facing — marketing, sales, customer service — have had use cases that are quite ripe for generative AI. There are other enterprise processes and industry-specific processes where we’re also able to leverage generative AI, but I think there’s a lot still to come. And so what I think we’ll be talking about, Phil — what I hope we’ll be talking about — is the more pervasive nature across the enterprise, and the ability to get into deep industry-specific processes to really reimagine and reinvent those processes going forward.
Phil Fersht — CEO, HFS Research[11:06]
Becoming much more embedded in the enterprise. But this has been wonderful. Lovely to catch up again, Yusuf. I look forward to sharing this interview with our network and our friends in the industry.
Yusuf Tayob — Group Chief Executive, Operations, Accenture[11:13]
Excellent. Always good to talk to you too, and I hope to see you soon.
