265 Exploring AI's Impact on Business with Paul Daugherty: Accenture CTO & Co-author of Radically Human: How New Technology Is Transforming Business and Shaping Our Future | Partnering Leadership AI Global Thought Leader

***DISCLAIMER: Please note that the following AI-generated transcript may not be 100% accurate and could contain misspellings or errors.***

[00:00:00] Mahan Tavakoli: Paul Doherty, welcome to Partnering Leadership. I am thrilled to have you in this conversation with me. 

[00:00:05] Paul Daugherty: That's fantastic. We're great to join you. I think we're gonna have a fun time together.

So looking forward to the conversation. 

[00:00:10] Mahan Tavakoli: We are Paul, and I was mentioning to you, your book Human and Machine, along with AJ Agrawal book, prediction Machines both coming out in 2018 started out my own fascination with the impact of artificial intelligence on organizations. Then you wrote Radically Human, which I absolutely love because it's that humanity that we need more in those future organizations. I can't wait to talk about those, but would love to first find out more about you, Paul, whereabouts you grew up, and how your upbringing impacted the kind of person you've become.

[00:00:49] Paul Daugherty: Yeah, that's a great question. I think a great place to start. So I grew up in Wisconsin and New Jersey. A little bit of a mix of both. I was in a family of five there was five of us children. I was the youngest of the five. the roots of my family were farming and different things in the Midwest.

And always had a really strong sense of family instilled, and also a really strong sense of human values and a strong sense of storytelling, from the way my family and friends of our family gathered together. So that shaped a lot of how we think about things.

Going forward. And at her early age, I got obsessed with learning. There was a story that my parents and my sisters tell about me. I've got four sisters, four of the five of us four of my siblings her sisters. And they tell a story about one of my pastimes as a kid was reading encyclopedia.

So I was a really fun kid. But , it was just always obsessed with learning from any source I could get. And that passion for learning, stuck with me as I went through my life. 

[00:01:45] Mahan Tavakoli: That passion for learning Paul is something that's gonna become even more important in the acceleration You talk about, so you mentioned this great acceleration and one of the things I wonder about is if you had asked people in different stages of history would they have all said, , we are going through a great acceleration.

So is anything different now than it would've been if we had asked people a hundred years ago about an acceleration? 

[00:02:12] Paul Daugherty: I think, history itself is about change and history is about, changing, us as humans, changing the conditions around us through technology, inventions of different sort from early advances in agriculture, thousands and tens of thousands of years ago to.

Printing presses to the Industrial Revolution and to the digital age that we live in now. So I think, history is really about constant evolution and change and how that changes our human experience. I think the different thing about the stage of the digital revolution that we're in now Is the pace of change in the way that you feel the change because it's happening, on such a quick, continuous basis so you can see the change and feel the change on daily, weekly.

It's certainly an annual basis. I think that's really the difference is the tangible, tactical sense of change that people feel. And I mentioned the digital revolution, the way I look at this period we're in is it started back in the fifties roughly with the invention of the transistor.

And also, interestingly enough, when the term AI was coined, artificial intelligence was coined around the same time. So we're 70 years into this massive revolution that we've had in digital technology, transforming the way we live, work, and play. And we're now at a period, 70 years in where , the fact this exponential creates a knee of the curve in such a steep feeling that we really feel this tangible sense of change every day.

Just look at the headlines now about generative AI and concerns and risks and hope and optimism. All mixed together. And that's what's a little bit different than the prior periods or prior evolutions of technology. 

[00:03:43] Mahan Tavakoli: So that acceleration, Paul, I'm finding a lot of CEOs and executives are having a very hard time with it, both individually and then in trying to lead their teams and organizations.

 So both with your role in Accenture and as you work with clients, how do you guide them on how to deal with this acceleration as leaders themselves before then talking about how they lead their organizations through the acceleration?

[00:04:12] Paul Daugherty: I'll put some bounds on the way I think about the great acceleration first, or some definition around it. So the great acceleration, that I see is the acceleration in the potential and power of technology that we're feeling all around us. And you can define it a lot of different ways, and we'll talk about a lot of different dimensions of technology as we talk today, but there's three.

Core technologies that are driving this digital revolution, and that will drive it over the next decade plus. And it's the cloud, it's artificial intelligence, and it's the metaverse. I'll dig more into that as we go. Those three things are reshaping our human experience in very tangible ways.

And as you said, I think , a lot of individuals, a lot of leaders are trying to figure out, so what does this really mean and how do you chart a path through this? And to do that, we believe you need to step back and look at things differently than you have before.

We talk about this idea of total enterprise reinvention being a new way to look at how you instruct your strategy and run your business, that you're constantly reinventing. And I think if you get into a mindset of not a one-time transformation, but I'm trying to create a culture. And a set of processes and a strategy and technology foundation that's about agility and evolving to meet the needs in the future.

 That's the mindset that you need to have. Cause , if you try to, do a transformation, hit it perfectly to, get to the future it's always changing cause you can never get there. Thinking about building this foundation for agility, what we call, reinvention, is really key to charting your path through that.

And then it's about, becoming a learning organization. I started talking about, myself and the learning. But I think organizations need to be learners. Leaders need to be learners. You need to have an empathetic, listening capability to understand and learn from others.

And that's key to charting your way through it. And that's what I'm finding in this age of generative AI that we're in. Is what I talk to CEOs, I talk to board members. I talk to friends and colleagues and family members. And they're all trying to understand, they're all trying to learn so that they can chart their way through it.

So I think those are some of the elements that are really important to think about. 

[00:06:09] Mahan Tavakoli: As leaders are thinking about these, you mentioned that we are all tech companies now. How then does that impact the strategic thinking for the organization if we are to exhibit and practice Aztec companies?

[00:06:26] Paul Daugherty: Do I think that's a really key. Value that companies need to think about is this idea of being a technology company. About 10 years ago, I wrote a report that was titled Every Business is a Digital Business. And that was 10 years ago. And at the time it was viewed as very controversial.

I don't think it's controversial anymore. Digital transformation is, what's defining the evolution of companies And the one criticism I have of myself in that report was that really to be a digital leader, you have to be great at technology. Cuz digital, in many ways it's a lot of things, but it's founded on the ability to, use technology to drive change in your business.

And that's what's really becoming apparent today and why I've been saying now, Yes every business is a digital business, which means every company needs to be a technology company. You need to be as good at digital native companies at technology. And that's what's really required to get ahead of the stay ahead.

And I think it's essential to this idea of reinvention. When we did this survey around this idea of total enterprise reinvention it came back with a finding that 91% of executives, 91% believe technology is central. To their evolution the change the transformation and reinvention that they're driving through.

So everybody believes the technology's important but you have to go to the next step. Not to say it's important, but really change your company to put technology at the heart of it. Change the capability you have so you have the leading and the best technology capability to chart your course into the future.

[00:07:55] Mahan Tavakoli: There is a huge difference between knowing what we're supposed to do and being able to do it and then actually doing it, and there is a huge gap in all of those. Wanted to highlight a couple of things You mentioned, Paul before going on. I love the fact that I. 10 years ago you had written about the need for the digital leader, Marty Rogers, a dear friend, said, even when it comes to ai, you were talking about it before, other people were convinced that it's gonna be as transformative as it is.

So you do have great perspective into what's happening in the future, and I love the growth mindset you talked about. The criticism you have of your own position 10 years ago. So it's that constant learning where gets us to assess our perspectives and constantly updated, which is required with respect to the strategy that you also mentioned.

So as you are reflecting on that, in human and machine, you wrote about the six types of hybrid. Human and machine roles. So this augmentation, which is one of the things that really stuck with me in my mind about the role AI can play in our lives. How has your view on those roles changed since you wrote the 

[00:09:10] Paul Daugherty: book?

 I'll go back a little bit in time and then I'll come back to the present. A lot of my thinking has been shaped by some insights I got back in my university days when I was studying computer engineering at the time. And I took a course by a guy named Douglas Hosh Debter on cognitive psychology, and he had written a book called Go to Lesher, bk, the Eternal Golden Braid.

And the book was about the interplay of logic and, computer programming, Escher. Art and design Bach music and how the three strains were essential in understanding, the, cognitive process of human beings and the connection between, computer science and the human brain.

That was, transformational book for me. A change, my life in a lot of ways, cuz it got me really hooked on this idea of thinking about technology on the one hand. And us as humans on the other hand, and what that intersection meant, how technology was changing humans and how humans were shaping, technology.

And that really drove all of my work since then. Back to the present when it came to Human Plus Machine, that was a culmination of a lot of that thinking because we wrote the book. Because at the time it wasn't gender of ai, it was the prior generation.

It was deep learning. And that wave of ai roughly 10 years ago, that was causing people to say, it's the end of, human civilization, AI's gonna take over the world. It's gonna eliminate the jobs and beat us at all our favorite games and all this sort of stuff. And I strongly believe in my co-author, Jim Wilson.

Strongly believed that was the wrong narrative and that we needed to set the record straight. So we conducted a long research project talking to 6,000 organizations, and then wrote what became Human Plus Machine, talking about the fact that it was really the way we use the technology that was important to focus on.

And if you take a Human Plus machine view and look at how the two work together. That was the key to unlocking the potential and the value of artificial intelligence. And if you do that, you can see the real possibilities. So you mentioned the six ways of reinventing work. We called that the missing middle based on the research we did, we identified, what we called the missing middle, which is the categories of jobs that were missing from the discussion, missing from a lot of people's thinking that were at the intersection.

Of where, humans and machines, humans and AI came together. Things like amplification of human capability through copilots, which is now, much more commonly being talked about. What's generative ai? That's one example , of the jobs in the missing middle that we talked about a lot in the book and have since seen come to fruition.

[00:11:32] Mahan Tavakoli: That amplification of humans, Paul, and that augmentation is a true power of artificial intelligence. It raises a lot of concerns though, in that in many instances, a few people, whether it's in coding or in content creation or other fields, can augment their work but get a lot more done, become drastically more productive, and that's causing concerns about displacement of jobs. What is your perspective with respect to that? That yes, some people will become tremendously more productive as a result. How will it impact that middle tier 

[00:12:11] Paul Daugherty: yeah, it's a great question. I don't have all the answers yet, is one thing I'd say, but I'll tell you what I do believe and what we do know from our research first is based on, the research we did for Human Plus Machine, which was before generative ai was really big on the scene.

 Our strong belief at the time supported by our research and supported since by what's actually happened was that AI would create more jobs than it displaced. Yes, it would displace jobs, but it would create more jobs than it replaced. And that was borne out. If you look at what happened over the last five years but that's not a satisfactory answer to your question though, cause it does displace some jobs.

So the question is, that's great if a. That new job, but how do you deal with the people who are displaced? And that's what we've put a lot of thought into. And that's where reskilling becomes very important. We donated all the proceeds of both of our books to organizations that are doing reskilling of people who are displaced by technology.

Cause we believe there's not enough funding, not enough attention going into that area. So that's a very real issue that leaders and organizations need to tackle. Businesses need to tackle that along with community organizations and governments and such, and educational establishments to really create the re-skilling programs.

There's been a lot of successes on that front but net, you can see it in the job statistics of today, even with the concerns on the economy and where it's headed. , we can see the possibilities that are out there. And it's about re-skilling people, stuff they're able to take on these jobs.

As you look at generative ai, then I believe it's the same type of impact. We have, don't have the research to prove it yet, but we're doing some research with some of the leading economists and AI experts in this area right now to look at what the impacts are. And based on the initial, steps in the research that we're conducting, we expect a similar type of result, probably more displacement.

Than we saw with the prior generations of ai, but also much more job creation and also even more power of the technology itself of generative AI itself to help in the reskilling of people and to provide copilots that could help people into new professions faster. We'll come back and maybe have another discussion once we're further through that research, but I suspect we're gonna see the same sort of narrative play out as we finish that research.

[00:14:12] Mahan Tavakoli: That's a magnificent opportunity both for individuals, executives, within organizations to augment and speed up that piece of learning that you were talking about. We need to become learning organizations and continually learn. AI can support us in that learning that's required in the organizations.

Now, part of what I love about your Radically human is that while you mentioned that we should all. B technology organizations. You also say more human, less artificial. , how can organizations focus more on the human elements while augmenting with the artificial and with technology?

[00:14:53] Paul Daugherty: Yeah, it's a great point. One of the things that's, endemic in us as humans is that. We naturally are fearful of new technologies. You tech, any new technology that comes along, set aside in digital technology and look at, through history, we've always been fearful of the impacts of new technology.

And the more human-like the technology, the more, fear that there's instilled until. We put it in context, understand the capability of the technology to really help us even more. And that's what I meant by even more human, less artificial. The better the artificial intelligence, the more human-like its capability.

The more power it gives us, think about what we think is state of the art in accessing technology today on our mobile phones. We think it's fantastic to type with our thumbs on the small screen on a supercomputer to try to get answers. Versus conversing with the technology like we could, with generative ai.

The power of removing us from the constraints of using technology and having AI that's more human-like and it's ability to communicate through large language models, powered by generative AI is super powerful. And I think it enables these co-pilot capabilities and enables us to build more human-like systems.

Systems. The other way I've been saying this recently is if you think about. All the automation we've been doing in companies for the last 50 to 70 years through this revolution, we've been producing software and we've been teaching people to use software to do their jobs more effectively.

And in doing so, we've been almost, Forcing people. It's, we call it change management and things like that. We force people to adapt to technology's terms. I think we're entering a new future where the technology will instead bend to the way that we humans work.

So using natural language and generative AI to query a system and get the answers we need is gonna, through these co-pilot capabilities is gonna provide us with these really rich. New experiences. And that's why, I've been saying that in the next wave we're gonna see, this phenomenon where, AI is going to eat software.

We used to talk about software eating the world. The famous statement from Mark and Dreesen, this is a new thing. AI is now eating software. AI is changing how software is made. And it's changing how we as humans experience technology. And the other thing is AI is the new ui. AI is the new user interfaces.

That happens and it's really exciting for us as people. That's why people are so enamored with chat. G P T I can text and talk and ask a questions and I can get these really cool results. Sometimes hallucinatory, sometimes real. But it's this power to converse as we tune it and train it and work on the issues of responsible AI and bias and hallucination and accuracy and all these things, it's gonna provide us super powerful tools to do more and do things better.

[00:17:25] Mahan Tavakoli: These super powerful tools, as you mentioned, are both augmenting individual work and helping with operational efficiency in organizations. Yeah. Would love to know your thoughts on the strategic implications of AI on organizations. So some parts of it is embracing AI tools. Tapping into the data to try to get insights based on what the organization has and making the professionals within the organization more productive and processes more effective.

What are the implications from your perspective on the strategies of organizations and how should leaders, CEOs, and senior teams think about the strategic implications, not just the tactical application? 

[00:18:10] Paul Daugherty: You need to look at it on two levels with what's happening on one level. The technology's moving so fast that it's a participation sport.

You need to, dive in and get experience with the technology and experiment. You can't just study it. So on one level, you need to play the participation sport and dive in and do some experimentation. Find the low-hanging fruit, keep the human in the loop and, figure out how you experiment with the technology and get some experience with it.

For example I'm Looking at my PC right now, looking at the window, and I've got Microsoft open AI capabilities for teams enabled. So I can do use the technology in very safe ways to get experience with it. And many people can do the same.

But that at the same time, this is game changing for organizations. It can allow you to do new things. There's one media company we're working with that there's a whole new stream of revenue, a whole new markets that they can access that they didn't have the talent to access without.

Generative ad now they can access this and create a whole new sets of products, whole new revenue streams, changing their strategy, disrupting, the way that they're part of the industry works in the media business. And that's a real strategic compared, you have to think about how do I take the steps to get there and build the business to do it.

So on the one hand, Play the participation sport experiment and get the familiarities that you can then build on that. And look at strategically where the technology could really make a difference and really differentiate You create new opportunities either for, cut radical efficiency or for, new growth opportunities.

As 

[00:19:34] Mahan Tavakoli: organizations do that, Paul, the ethics around the data use and the importance of data becomes more significant, but the ethics and the responsibility around data becomes a big issue. What are your thoughts with respect to that data integrity and ethics as organizations are tapping into these potential opportunities based on the data that they have?

[00:19:59] Paul Daugherty: This is a really important consideration and something we've spent a lot of time on since Human Plus Machine and before it gets into the area of responsible ai. And simply put, if you're an organization using ai. It's irresponsible to not have a real structured responsible AI policy program in place To guide your efforts instead of tools.

So responsible AI is really critical. Responsible ai gets into, the bias that could come about from buying the technology. It gets into the accuracy, the hallucination versus really verifiable accurate results.

It gets into transparency. Cause in certain cases you need to be able to explain what happened. It gets into, accountability. Who's responsible when something goes wrong. And at the heart of all that is using data in the right way. Making sure that the data that you're training the systems on is appropriate.

That you're not exposing data you shouldn't about customers or citizens or people. And to make sure the data isn't producing biased outcomes in the algorithms that you train. So responsible AI is really critical. We believe it's so important that we actually created in our company a compliance program, formal compliance program for responsible ai.

We've trained all of our 700,000 plus employees unresponsible. AI and what it means. And we've we've got these formal processes in place that we measure and report on to ensure that the AI work we do within our company and that we do for the clients we serve, meets those principles.

And we really encourage and work with a lot of organizations to put the same policies in place. So that's one level of it. Then you get into other levels of it, where in certain countries you have jurisdictional and sovereign data regulations that you have to comply with and, many other considerations that you have to bring into it.

I'd like to cease this phrase that cloud enables data drives and AI differentiates, and if AI is really the differentiation that you, we wanna get to. The first step is often getting to the cloud. The second step is getting your data organized and verified and complete in the right way to drive the ai.

And then you can do the ai. But the data is really a key step along the way. And one thing I commonly see with the organizations we work with is they have great visions around what they wanna do with ai, but then they look at it and say I gotta start here and get my data ready. Gotta get the digital core of my company in a position where it can produce the right, Data and treat the data in the right way so that I can then, move on and develop the AI that I aspire to.

[00:22:17] Mahan Tavakoli: So as the organizations you're working with Paul are looking to tackle this, I was reading an article just a couple of days ago talking about the new C-Suite office a chief AI officer. And whether it's the c i o, college chief AI officer, or whoever that person is, how do you guide organizations to go about tackling these strategic issues in a holistic manner?

[00:22:45] Paul Daugherty: We believe it needs to be A C E O level priority. So c e o needs to start with the leader of the organization and somebody in the C-suite at the senior leadership level needs to be accountable for all the elements of responsible ai.

And a common approach that we're helping companies implement now is creating an AI center of excellence that's not just the AI experts and developers of ai, but includes the responsible ai, it includes the policy, it includes the training of people, not just to do with ai, but you have to train people to use ai.

What's it like to use a co-pilot and the change required to drive that into your organization? So it's comes down to really setting the tone from the top and having the capability structured and well organized, and then, really pervasive education and creating this learning environment through the organization that's, the path to success.

Can't just be a pocket of the organization or delegated to a lower level of the organization. We believe it really does require the top level focus. 

[00:23:42] Mahan Tavakoli: And as that's happening. Paul, you also had an outstanding recent article in Fortune on generative ai, which has fascinated lots of people in part because of chat G P T, . And you quoted an m I t Stanford study that it can increase productivity up to 14%. So how do you see organizations being able to use generative AI in supporting the co-working that can be done with a generative ai. 

[00:24:15] Paul Daugherty: Yeah, generative AI really is a big deal.

I guess I'll start by saying that, which maybe I don't need to say cuz I think everybody's assumed that it is. But , I've been in the industry almost four decades now pretty close to it. Counting my student days. And there's four things that have surprised me in 40 years. One was the first time I saw the Apple Lisa, when I was a student at the University of Michigan.

And that's what led me to say, I'm gonna major in computer engineering, computer science, cause I wanna learn how to build those things and do that. That blew me away. The graphic user interface, Steve Jobs first pet project was the appa, so that was mind blowing. The second was around 1992 when I used one of the first internet browsers and you can see the power of the world's information being connected.

And what that would mean. The third was around 2008 with a iPhone. And this idea you could get a super computer in the pocket of billions of people around the world and transform access to information and, mobile services and such. And then the fourth was about 18 months ago when I started seeing the advances in the foundation models and large language models the transformer technologies and technologies that we're calling collectively generative ai.

So it's a big deal. One of the biggest things I've seen, and I think it's probably the biggest of those innovations in terms of the impact That's having on, the way that we work going forward. We've done some research and we're still, continuing some of this.

But basically initial research, we believe that generative AI will impact 40% of working hours across companies. So 40% of working hours if the work that's done basically that doesn't mean that 40% of jobs go away far from it because of everything we talked about earlier about the augmentation and, different ways that this could improve what people do.

But it does mean that jobs will change dramatically. And that's what we're really focused on as we look at generative AI is how will it change the jobs? How do we reskill the people that are displaced by automation? Which we talked about a little bit earlier.

 And how do organizations, deploy it successfully to drive their strategy going forward? So it's still the early days the technology really, bursted down to the scene in the last 18 months based on some advances became popular with chat G p t back around, November timeframe of last year.

And it will probably be one of the more transformative technologies through the rest of this decade. 

[00:26:24] Mahan Tavakoli: Another one of the technologies that you have written about and spent a lot of time on is the Metaverse and the N floor that you set up for Accenture. That can be another one of those transformative technologies.

Would love to get your thoughts on where you see the future of Metaverse and how that will impact organizations. This is one. 

[00:26:51] Paul Daugherty: I always get a raised eyebrow sometimes when I talk about the metaverse these days. Last year Metaverse was all the rage and for a lot of reasons we've gone from the peak of over-inflated hype to the reality of reset expectations, and that's where we are today with the metaverse. But make no mistake about it, the technologies underpinning the metaverse are really transformative and will reshape how we use technology going forward. And there's really two parts to the metaverse to think about.

It's not just about headsets and. And the avatars and non fungible tokens. The metaverse is really about two things. It's about new forms of spatial computing where you're not confined to two dimensions on small flat screens. So think about spatial computing. So that's extended reality, virtual reality ambient computing and the like.

And the second thing is about digital ownership. That's verifiable digital identity. It's the digital currencies. It's digital products that you can enable through blockchain and related technologies. Technology is making great progress on both those fronts, which means that You can create experiences in new ways.

I can create spatial experiences in virtual worlds to using tools like Microsoft, meher, a variety of other things that are out there, NVIDIAs, omniverse, and all sorts of technologies. Epic, unreal engine, many things. And I can, as technology's advancing use digital ownership in new ways.

So there's great advances happening around shared universal wallet technology. Now, if I have a digital universal wallet based on blockchain, rather than my identity being entered differently into hundreds of companies and systems and sites that I subscribed to, I could have one digital identity

that I share with the companies that I need to access. It's a transformative idea. We're not all the way there yet, but through things like the Linux Foundation digital Wallet Foundation through advances that are happening, digital currencies 105 digital central banks around the world, we are moving to this future of digital ownership.

So two of those together, it'll take a few more years to come together at scale, but it'll be really transformative until in the way companies operate. And the initial wave of that we see. Is through interesting work we're doing today. You mentioned Accenture's end floor. We've onboarded over 150,000 of our employees.

In the Metaverse using Microsoft Altspace now mesh. And it's a great experience for our employees. It's better than what they could do before they can meet people from around the world. We get tremendous engagement scores. The knowledge retention is demonstrably better.

 As we've been studying this, and it's a great experience, that's an example of us using the metaverse today at scale with great results and great business impact. We're doing amazing things with companies and industrial metaverse, creating new digital factory capabilities combined with augmented realities that could transform the way they do operations.

This is stuff that's happening today. That's the front edge of The metaverse environment that's building out and will be transformative as we go forward. 

[00:29:36] Mahan Tavakoli: I also had a conversation with Louie Rosenberg, who's one of the first people to develop augmented reality for us Air Force.

Yeah. And he mentions the same thing that a lot of times when people think about metaverse they're purely thinking about. The fully immersive experience, which has a lot of value to it, for certain applications, for certain periods of time, yes. But the most common applications will be augmentation of our real world experience.

[00:30:03] Paul Daugherty: Yes. Yeah. We already see it today. Augmented reality, we believe will be certainly for business, more transformative In its application and create greater value for businesses. And through the kinds of examples that I was talking about, and the technology is moving fast.

Going from headset mode down to eyeglass form factor down to retinal projection will happen over a, a period of several years, in the future. And that'll create the ability to really scale those experiences to a lot more people.

So 

[00:30:27] Mahan Tavakoli: Paul, to connect back to a point we started discussing at the very beginning, a lot of the CEOs that I'm interacting with are stressed beyond belief. And they say that I'm having a tough time as is keeping up with the changes in business. In some instances they are having a tough time even with the employee return to office and all of those aspects of it.

Yeah. So then there is. This AI metaverse, all of these things that can truly be transformative and impactful to the strategy of the organization. They can wipe organizations out or give opportunities to lots of other organizations. So how do you guide leaders and CEOs to stay on top of the more relevant information to be able to lead their organizations?

[00:31:17] Paul Daugherty: There's a number of things we try to do in our organization we believe, every company's a technology, company as we, we talked about earlier. And we really embrace that in our organization. One thing we do is we have a series called TQ Technology Quotient.

We believe we all have our iq, we all have our eq, set of skills. We believe everybody needs a tq, which is your technology quotient to be successful. In our company or any company. so we have a series of trading that everybody goes through. All of our 700 plus thousand people go through to familiarize themselves with.

All the kinds of technology we've been talking about and more even quantum computing and different things are part of this education. So people understand , the technologies have a familiarity with it and can understand, how to talk to their colleagues, how to talk to their clients and how to talk to others about their technologies.

So I think that's, A key part of it is creating those kind of platforms, for everybody to learn. Then you need to create the platforms for specialized learning and how you stay abreast of . Leading edge capabilities coming and for us that comes down to what we think about as our innovation architecture from our r and d and labs through our venture investing that we do with our corporate venture investing arm through the applied research we do, every day with clients out in the field and how we pull that together, into new innovation to drive to clients.

So those are some of the things that we look at. And then it's the ecosystem you build around you. , it's the partners we've got, which are everything from the hyperscaler cloud companies to startups, to the, enterprise application software companies, and more that we work with and the universities that we collaborate with.

That's the ecosystem in which we operate. We're always, kinda learning and combining ideas within that ecosystem. I think every company needs something like that. Were you have your internal mechanisms you have your talent, you have ecosystem that you build on, and you have to construct the way that you stay relevant, that can create the right ideas for the business and bring them in and create the capability to drive the innovation forward in the organization.

[00:33:09] Mahan Tavakoli: What an outstanding perspective, especially on the partners in the ecosystem that can support each other going through this transition. Additionally to that, Paul, one of the things I find is of tremendous value is finding Sources with lots of signal and very little noise. Yeah. As I mentioned early on in the conversation, human and machine got me started on this journey of understanding the potential power of artificial intelligence and the technologies and the changes that will happen as a result.

Radically human is an outstanding way to talk about. How organizations can transform. And in addition to the articles that you write, the Accenture technology vision report, which I'll put a link into, we didn't get a chance to have a conversation around that. So you put out a lot of outstanding content that the CEO's executives can benefit from.

How can they follow some of your insights and the content you put out? Paul? I think 

[00:34:13] Paul Daugherty: One thing is to follow what I'm doing and what we're doing at Accenture on LinkedIn. We publish, a lot of information. We try to really keep it in plain English or plain language in different languages we publish in, so it's easy to read, understandable, backed up by data and facts and research.

And something that they can read. We also have developed something that's that anybody can download and access called foresight. It's an application you can download that accesses all the knowledge capital that we have. It allows you to tune into real time, broadcast and things we do on new technology that encourage you to check out our Foresight app and we can provide a link to send Ron to the group.

And those are probably two of the best ways to do it. We do the vision once a year. The. The vision that we do, this year, it's called When Adams Meet Bits. We do this once a year and it really is a compendium of what we believe are the top factors that you need to think about, now for shaping your business strategy for the future.

So once a year, I'd suggest everybody pull that down and take a read. 

[00:35:09] Mahan Tavakoli: It's outstanding perspectives from the need for total enterprise reinvention to building a culture of innovation. I will link to it in show notes. Really appreciate you and this conversation, Paul, and all the great. Content you're putting out, helping all of us expand our thinking, reinvent our organizations to become those tech organizations, taking advantage of the opportunity to be radically human and transform the future of work. Thank you so much, Paul Doherty. 

[00:35:39] Paul Daugherty: Thank you. It's been great to be here. And we could have gone on for hours. But it's been a great conversation. We covered a lot of ground.