Accenture’s Chair and CEO shares insights on key questions leaders need to be asking to keep pace with fast-evolving A.I. technology, reinvent their enterprises and drive business value.

Fortune Brainstorm A.I. 2021: A.I. in the era of compressed transformation

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let's begin with this stat from our presenting partner center, 84% of C. Suite executives believe they must leverage ai to achieve their growth objectives. But 67%, I'm sorry, 76% acknowledged struggling with exactly how to scale ai across their business. So there's clear uncertainty among leadership about how to broadly implement artificial intelligence. And those uncertainties are also compounded by factors such as a pandemic and shifting economic realities. Let's talk about the ways to overcome these challenges. Please welcome a center Ceo julie, Sweet and Fortune Deputy editor brian O'keefe for a conversation on how to successfully embed ai to result in agile and resilient organizations with sustainable growth. Thank you Kristen and good morning to everybody. Um Thanks julie for being here, kick things off and build on the conversation yesterday and the stats that Kristen just cited um about the disconnect between the appreciation of the opportunity and the confusion about how to advance with that I think gets to what we want to talk about. Um you know that part of the title of of our discussion is the era of compressed transformation and it's something that you wrote about today unfortunate dot com. I encourage everybody out there watching to go read julie's piece. You talk about a sense of urgency. So first of all, just tell us what you mean by era of compressed transformation. Sure. There are three kinds of companies today, in our view there's leaders who are leading in digital, there's leapfrog others who have made the strategic choice to be a leader to go much faster than they were going. Pre pandemic and then there is everyone else. And the sort of one third of companies are engaging in what we call compressed transformation. So it's three characteristics. First of all they're touching two times the amount of processes in a much broader reach across the organization. That's the first. The second is that they are engaging in a cloud first strategy and embracing emerging technology. So in the U. S. For example 55% of the company's we categories as leapfrog ear's have significantly increased their investment in ai our topic today. And then the third piece is that the leaders and the progress are investing more in I. T. In innovation than NBA use. So they're you know changing the way they're doing their operations, their maintenance uh to really put much more money over 50% in innovation. And so uh when you think about the impact for that two thirds of company, you know I always joke that transformation doesn't happen fast. Right? So a lot of people said oh the pandemic you know shrunk transformation. We'll all of us who actually engage in it know that it takes a while but are you know we're predicting in 12 to 18 months that you're gonna start to see the results of these compressed transformation across industries and sort of that two thirds of other companies are going to recognize just how much farther they've fallen behind and you've already gone from sort of leaders being two X. Laggards, the bottom 25% pre pandemic to financial performance at five X. Uh And we think that gap is going to continue to widen as you think about the others. So I want to remind everybody if you have questions get them ready we'll have a chance to draw on those questions in a minute digging into that research a little bit more. What I thought was really interesting. Um If I got this right, you talked about the leap frogger. So the companies that maybe didn't go into the pandemic ready to invest aggressively in technology but then they made a decision to do that and that they've significantly outperformed the laggards I think four X. Um What does that look like? What is it, you know what's a successful leap frogger? Uh look like? What are some examples of how companies have been able to do that? Well. Um So we talked about the characteristics maybe take it to a. I so um you know yesterday we talked a lot about ai not being about the technology about being changed. You know think big start small. The reality is you have leaders and leapfrog us who have made a strategic choice to lead and if there's one phrase to remember from our talk today it's cloud is the enabler Data is the driver but Ai is the differentiator. That's how you win. Three examples. Let's start with accenture we're all about talent. We have 624,000 people. We have a database of automatically populated in the cloud of all of the skills of our client facing people. When the pandemic hit, we used Ai to identify who could be retrained to meet the new demand around cloud and collaboration tools. You remember when everybody shifted home and they were starting to accelerate, right? That's a huge differentiator and it's at scale. Right? Let's take a consumer goods company right there using AI right now in the market to see how in real time their products, performing how to adjust it, anticipate supply chain interruptions and then reach. We um redo their entire supply chain when they see a big issue at scale. Right? So 3rd, 3rd example, uh an automobile manufacturer who real time for customers is on the assembly line using Ai to be able to reimagine the different configurations and then do the manufacturing all of these things have at the heart of them a strategic choice and scale. So they're overcoming the cultural issues, the talent issues and you know what we talked about in the bike lane today is what does it take to go from understanding all of the challenges to actually using Ai to differentiate and it starts with that strategic choice and then the second piece is super important is what you're doing actually at the C suite table, totally different level of education and focus from the C suite. Uh And that's a big characteristic that's different when we look at the company's who are leaders in the progress versus the others today. Yeah. I mean I was going to ask you about that. What are the questions like that you're getting now when you talk to clients as opposed to two years ago when we were going into this, is it across the board, you're seeing like much more of a sort of understanding of how the technology can work and sort of the basic challenges and like a deeper level of what are the nuts and bolts of making that strategic shift. Well, one of things that's really interesting is that Ceos go pretty deep, right? So pre pandemic. They were not going deep to really understand the technology itself but I would tell you in the last three months there's been a significant shift in the tone of the conversation. And if you go back to clouds, the enabler uh data is the driver. The Ceos that I'm talking to now are really uh uh frustrated because if they started behind and they need to get to the cloud, they understand they've got to get to the cloud as fast as possible and they were accelerating before but they're trying to get to the prize of how do I use the data and ai to do something different. Uh And so that's very interesting to see that shift. And so things like culture is really important. The conversation I'm having with many ceos is there are ways to actually make the cultural change go faster and that you can't sort of embrace that culture takes a long time. Let me give you a simple example. You have office 365 which most of us have right. Use my analytics which we do at accenture but you can actually tell are the people that need to be uh collaborating differently in order to utilize the cloud et cetera. Are they actually doing that? And not in a creepy way? Right. But you can actually look at that right? Why is that important? Because cultural change requires you to work differently to collaborate across the organization in order to use the cloud data and AI and this is a way of having a leading indicator right? That would allow you to say wait a minute that's not happening. And I will tell you the you know Ceos are embracing the idea that cultural change can happen faster. And partially because the pandemic demonstrated how when when you need to the organization can change. And I think that's really important in the context of Ai to not use as an excuse the need of cultural change but really to embrace the challenge of achieving that change and bringing your people along as quickly as possible. I feel like after we get off stage I got to go use the cloud so I look forward looking but we have a question back here for julie if you could just identify yourself really quickly. Yeah. Hi abdication allowed Chief Ai officer of steadily black and Decker. Oh I love your statement about cloud. Is there the ability to the dry well at aI is the differentiator, Are you seeing qualitative shift in the strategic use cases of Ai or are you seeing it all pervasive what what I'm seeing is that the companies are leading don't confuse necessity with a strategic choice. And in other words um a lot of companies started using AI because of the pandemic like to use contact lists, manufacturing and pick up and you know chatbots to answer questions that I would call by necessity. The leaders are saying okay that's necessity. Now we're gonna make a strategic choice and their qualifying that strategic choice by making decisions to make it material and that's where um you know yesterday I think someone said think big start small. However you know, starting small pre pandemic took a long time and it's the strategic the qualitative decision to pick areas where you can move much faster have poc. That scale must much faster most of time doing that with partners. We just did something with a big consumer goods company and one of the ecosystem partners to go across the manufacturing plants. Pre pandemic would never move faster in this case it was like 12 weeks, it was using Ai digital twins and now scale and from the beginning it was let's let's figure this out together, let's get in a room let's get on the shop floor together. That's different. So it's both selection but also execution. Uh And if you know I ask a simple question that ceos who say they want to move faster I ask what have you changed and I think all of you can help uh you know yourselves your teams and the C street across the companies are saying what are we really doing differently to take advantage of the opportunities and the technology ahead of us? We have a question in the back and then we'll come back over here. So hi I'm rocket johann from Mastercard. I'd like to disagree with the statement that you just made So great. I love this agreement. We like push back so um you said data is the enabler and Ai is the differentiator is the data the driver clouds the enabler data as the driver and Ai is the differentiator and I and I take a position that the data is the differentiator and Ai is the enabler because in long and a long haul the only thing that will differentiate a company will be the data and not a I because I had already been commoditized. Every Ai algorithm is available in the open source so it is the data that brings it to life and hence data is the differentiator and not not the I think it's a great a great point because um you know right now every company is trying to struggle to get their data and that's why data and cloud is converging. However, I'd like you to think about what's also happening today which is the accessibility to third party data. And so while your own unique data can you know, you can say hey that's a differentiator, the leading companies are taking their data and they're figuring out how to bring in the third party data. And so I would say not not this moment, but think about 2-3 years from now where companies are able to access third party data mix it with their own data is your unique data truly the differentiator or how you use that data right? Uh to to build goods and services to personalize, which requires the Ai Now at the end of the day it's all in how you use it, right? So you know, its technology was the same for everyone. You'd never have differentiation, right? You still have to have the human ingenuity uh to sort of figure out what do the clients need, You know, what do the companies, what are your customers, B two B or B two C need. Uh And that will truly be you know what's gonna differentiate but that human ingenuity maybe 20% And the you know the cloud, the access to the data in the AI 80%. Right? So and I think trying to get that balance right will be interesting. They're all key. Let's get one more question in from our audience down here. Hi julie and formal. I lead the data science and analytics team at gap. Your team's doing some really cool work for that thing. One of the things we're doing um is uh, you know, acquiring a lot of AI companies and analytics companies to fill specific gaps in our capability. No pun intended. And I know that's one of the things that santa is also doing. You guys have acquired companies, What can we learn from you on, how do we integrate or not integrate or when do we integrate those companies were acquiring? It's a great question. I start with um how do you make, you know, what do you want from that company besides the talent. Like for example, sometimes we hire companies and they're really great at recruiting and early in the early days we've been managed to actually kill their recruiting because we imposed our things. So I think understanding what the capabilities they're bringing and therefore how to um make them, you know, thrive in your organization. Sometimes it's almost a reverse merger. We bought a organization for federal business where they were much bigger and more advanced than we integrated into them. Great in other cases we keep it separate because it's such unique skill set. So for example, think about some of the cyber stuff. We do, you know, the community, the type of people, it doesn't make sense to integrate it so but it starts with what is unique about them and then really clear eyed and what, you know what my organization might kill, what is unique, you know, or be enhanced by what is unique. And we start the discussion like we're really good at integrating. Um and uh you know, we, this is sort of a core competency of ours, but we have the very first integration discussion on the moment. Someone raises the acquisition and then we co create it with the people that were buying from the beginning. We have that discussion and we use, you know, they learn about us, we learn about them and we have very open and transparent discussions from day one to many companies wait on integration until they quote unquote decided and I will tell you that it's actually an advantage because when you're talking to target and we're already talking about integration, they learn more about us and they feel like well I maybe have a real home. So it's actually an advantage in recruiting companies because at the end of the day they're making choices particularly in the space that you're buying julie. Thank you so much for bringing your clear eyed perspective to where we are with AI now and where we're going and thanks for joining us today. Thanks everyone