Technology Strategy 2023 Into the Metaverse - CXOTalk 748

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The future of technology, how will it affect  those of us in the enterprise? What will the   impacts be on consumers? Paul Daugherty  is with Accenture. Paul, tell us about   your role, your work at Accenture. Technology is reshaping the world   like it never has before. I think of my role and  Accenture's role as helping navigate through that. 

There are really three things that I think about  when I think about our business. It's our clients,   our people, and our partners. Our   mission is to help our clients achieve their goals  and harness technology to achieve their ambitions.  We're almost 700,000 people strong in  Accenture right now and well on track   to our goal of 50/50 gender diversity by  2025. That's a passion of mine as well:   gender equality in computer science and tech with  external roles on the board of Girls Who Code and   other things in addition to our internal efforts. Then there are our partners. The technology  

industry, what this is all about  is really leveraging the power of   all the amazing innovation across all the  technology companies (the hyper-scalers,   the enterprise application companies, the  startups, and others) in helping leverage   that technology – the first thing I talked  about, which is the clients – in helping clients   apply the technology to improve their businesses. That's, in essence, what it is. The formal   title is Group Chief Executive of our  Technology Business, which is about   $38 billion of Accenture's revenue and  about half of the people that I mentioned.  I also have the title of Chief Technology Officer,  which is about setting the technology direction.  

It's all those partner relationships that I  talked about. It's the roughly $1.1 billion   a year that we spend in research and development  on improving our business as well as the venture   investing and things we do to drive innovation. Paul, you have just written this book. It's called   Radically Human. It's an interesting title what  does Radically Human have to do with technology? 

Radically Human is the second book that  I've written. The first was Human + Machine,   which I'll refer to a little bit. What we're  talking about in Radically Human is a step   beyond where we went with Human + Machine. With Radically Human, we're talking about  

what happens as technology itself becomes  more human-like and how does that create   the potential for even greater radically human  potential capabilities that we can develop   in ourselves. That's kind of the balance we're  looking at. I view it as kind of a third step   in the evolution of how we use technology. The first step was people using technology.   We had to figure out how to use machines and  green terminals, punch cards, and things back   when I was initially programming. For  a long time, we've been subservient to   these machines. If you think about IT programs, it  was about investing millions of dollars in change  

management to try to figure out how to train  people to use all this complex, clunky technology.  We moved from that to the human plus machine era,  which is what I talked about in the last book,   which is about leveling the playing field between  humans and technology and creating this human plus   machine symbiosis, so to speak,  that we talked about in that book.  With Radically Human, we're  talking about the next step now,   as technology really becomes more human-like in  a lot of different ways that we can talk about.  

How do we take this new step into a really  radical human era, which is really truly   augmenting and maximizing the human potential in  us all using technology in a more effective way?  How do we accomplish that  transformation that you just described?  We talk in the book about some research we  did. We did what we think is the largest ever   research study of how businesses around the world  are using technology. The largest-ever study   of enterprise technology; we surveyed 8,300  companies. We asked all sorts of questions,  

and we found out some surprising things  in the course of doing the research.  Another interesting thing was the research started  before COVID, so we had a cut of the research   before COVID. Then we repeated it more recently  as we move to the post-COVID era. The dichotomy   that we saw was really striking and it reflected  this change in how technology was being used   that we write a lot about in Radically Human. Before the pandemic, our studies showed that   the leaders, in applying technology, the  digital leaders – there were about 10% of   companies that we identified in this category –  were outpacing the rest by a factor of 2x, which   was striking in and of itself. It was the way  they were using technology that was doing that. 

Then we redid that research, and we didn't know  what we'd find – to be honest. But what we found   really surprised us, which was that that gap  had widened from 2x to 5x. The top 10% were   now outperforming the rest by a factor of 5x.  Again, it was how they were using technology. 

We saw things like new technologies  being adopted at a 70% greater rate   during the pandemic than before, the pandemic  being this forcing function around innovation.   We talked about compressed transformation;  companies needing to figure out how to leapfrog   and become leaders in technology faster.  That's the whole shift that we experienced.  Then Radically Human, what we're looking at is,  what are the underlying patterns in that shift?   One of the things we talked about is what we  call the IDEAS framework. It's an acronym.   It's I-D-E-A-S. It stands for innovation,  data, expertise, architecture, and strategy. 

What we're positing with the book is that  you need to invert the assumptions you have   on these five areas to really look at how  you maximize your leverage of technology   and approach innovation in a different  way to create this radically human effect.  Can you give us some examples  of where organizations are   taking this and putting it into practice? Yeah, what we're talking about here is again   flipping some of the assumptions around using  artificial intelligence and what it means to   create these radically human capabilities. We're  talking about new techniques like common sense   reasoning, for example, moving beyond the machine  learning and more basic approaches in technologies   that companies may be using and the different  results that you can create as a result of this.  Companies like Effectiva (who I think you may have  talked to in one of your programs) are looking at   using emotional AI in this case that we're  applying with one industrial equipment   manufacturer to look at things like the safety  characteristics of their human heavy equipment   drivers so that they can understand alertness  and awareness and anticipate problems before   they might occur. Again, allowing a person  to be more effective, to be more human in   their characteristics by leveraging technology  more effectively, that's one example. 

Another example is in the data area. One thing  we talk about in data is moving from big data to   small, from maximum data to minimum data and  back, from big data to small data and back.   Big data in the GPT models that have billions  of parameters and such are important for certain   purposes. But in many cases, what we're  seeing, it's the smaller data that truly  

differentiates companies. Really understanding  what's the small data that leverages you.  This can come in a couple of ways. For example,  in your supply chain, really understanding   the small data that differentiates how you make  your products using big data for other purposes,   perhaps, but understanding the small data that  can drive you to have greater supply chain   advantage in the availability and the  way you use your goods, for example.  Another example of small data is what companies  are finding by using smaller data on edge devices   to do some of their processing because you can't  always get it back to a cloud or back to your data   center to process with the volumes of information  (as you move to more edge-based architectures).   It's a good example of the small data and what  you can do on the edge being more important   for some applications and the big data that  you can use at the core of the organization.  Those are a couple of examples. We can go  into more, Michael, if it's interesting. 

Paul, is the general idea here that  technology advances and the way that we   gather, use, analyze data, therefore,  enables the technology to fit more seamlessly   into what we could say the cracks, the crevices,  the various parts of our daily life, our business   life, so that it becomes more intuitive  and, ultimately, therefore, far more useful?  Yeah, far more useful. Again, it  enhances our human capability.  Look. We use AI continuously throughout the day  already, so it's already a part of what we do,   and it's become part of ourselves. The nature of  what makes us human changes as we use technology,   or the nature of our human capabilities  change as we use technology in different ways.  Again, using things like  Internet search capability   extends your recall powers and your ability to  find things, your directional capability, and such   (in many ways). That effect just gets magnified  as you look at applying those kinds of concepts   more profoundly throughout the way you run your  business and drive your business processes. That  

is what we are talking about and that is how you  use the human capability in your organization.  The E in the IDEAS framework is expertise.  We're talking here about things like machine   teaching – not machine learning  but machine teaching – which is,   how do you use human expertise to train your  processes and your systems more effectively?  We're talking about an example in the  book from Etsy (the e-commerce company)   where they use the human expertise of their  designers to establish design esthetic,   to train and run different design esthetic,  patterns, and such that then enhance the consumer   experience that people have on their website. It's  an example, again, of machine teaching and human  

expertise being leveraged in a very different way. I think, as you said, it's really that   amplification of everything we do in maximizing  the potential of the human capability.   At the end of the day, it becomes a lot of  the human expertise, the software skills, the   ability of humans to work together to collaborate,  to understand patterns, to do cross-domain   problem analysis, and things like  that that become real differentiators.  What should folks in the enterprise who are  listening do about all of this? What does   this imply for companies and the way that  we relate to technology and business?  It's got a lot of implications for the way you  think about things from a business perspective.   We talk in the book about, first of all,  the ideas framework in thinking about these   assumptions differently: the intelligence,  data, expertise, architecture, and strategy. 

When you get to the strategy, that's one thing  enterprises need to think about differently.   We talk about three different new forms of  strategy that we believe you need to incorporate   in the way that you plan for the future. One is called Forever Beta. This is the concept   that you're never quite done with your product.  Think about Tesla as an example, the way Tesla  

works in continual new software releases to your  car, changing your driver experience as you go.   That's increasingly a strategy and a  model that companies will need to follow.  Another strategy we talk about we call Minimum  Viable Idea, which is taking all these ideas –   the I-D-E-A things that we just talked about – and  blending them together to create a new form, a new   strategy based on leveraging the technology  in this more radically human way.   The example we talked about in the book  is Lemonade, this startup insurer who   has crafted a very different business  model with engaging their customers in   a very different way (leveraging the  concepts we talked about in the book)   to create a very consumer-centric way, a very  different way of constructing insurance products.  Then the third strategy we talk about is Collab,  which is a play on words a little bit, which   is collab, which is like collaboration but it's  also collab, bringing the science and technology   together, which we see has a big impact  as we look at where technology is going.  One of the companies we talk  about in the book is Moderna.  

This was a lesson learned during the pandemic  of how Moderna pioneered a whole new science of   vaccine delivery through messenger RNA, found the  treatment, clinical trials through diagnostics,   et cetera, at a very unprecedented pace. And if you look underneath at how they did it,   it was a drug discovery studio powered by  the cloud, convolutional neural networks,   data used in the way we're talking about to  drive a very different outcome. That's the   example of that Colab strategy to action. To answer your question, it's a different   way of thinking about the strategy. It's  a much more dynamic living way of doing  

your business and IT strategy together  than companies have previously done.  What about convergence of enterprise technology,  consumer technology, and consumer expectations?  It's all becoming inextricably woven  together, if you think about how   technology is proceeding. I'm not sure  you can differentiate the two anymore.  If you look at what's happening with  technology – from artificial intelligence   to the metaverse to Web3 to anything that you  might mention – the worlds are blending together   and you can't think about it as distinctly. I  think that creates a great opportunity for CIOs  

and for enterprise technology organizations in  terms of approaching technology differently.  Some of the implications we see (and we talk  about in the book and in the other work that we   do) is things like the product development and  how you shift from an IT mindset and a service   mindset to a product mindset and product  development mindset, product management   disciplines and such, which is becoming essential  as organizations look to shifting from IT running   the business to IT producing the digital products  that enable the business, which is the journey   that all organizations are on (to some degree of  change) right now. That's a dimension of change.  I think there's a whole set of changes around what  it takes to integrate consumer experience with   the enterprise experience, this whole  idea of experience-driven technology,   which is a whole chapter in the book. There's a  whole chapter in Radically Human dedicated to this   idea of experience and creating experiences  in the right way. It's really essential.  Those companies that create better experiences for  your consumers (or your workers, for that matter)   will be the winners going forward. That doesn't  just mean in the B2C market. If you're in a B2B  

business, it's how you work with your business  partners and such, create those distinctive   experiences in different ways and creating that  experience design and design thinking kind of   mindsets around it. Again, all organizations are  on some stage of that journey, but it becomes   increasingly relevant as you look at this. Then there's an element also around trust.   Again, there's a whole chapter in the book devoted  to trust because, if you think about experience,   you think technology, and you think about AI,  metaverse, and all these new technologies,   the issue of trust increasingly comes up. I would be willing to make a wager   with all of you that, as we look into the next  decade, the biggest differentiator among companies   will be the degree of trust that you can engender  with your consumers and workers because the trust   is going to allow you to get the data and  have the access to create those experiences   that are really going to differentiate you. Trust becomes a fundamental capability to   think about and really understanding deeply  what things that you do increase the trust,   what things that you do erode or challenge the  trust that you have with all of your stakeholders.   It becomes really critical. Those are some of the things  

that I think are really becoming center  of thinking as you think about this   consumer and enterprise blend that's happening.  As we look forward, we can get into metaverse,   Web3, and some of these things. It's even more  pronounced as we look to the future of where   digital technology is going, which is increasingly  in that direction, as we talked about in the book.  On Twitter, Louis Columbus, who is a great  software industry analyst, really latches onto   this idea of forever beta that you were just  talking about. It seems that a fundamental   aspect of all of this is really changing  the relationship that we have to technology,   which for many organizations (for many of  us) requires such a huge mindset shift: how   we think about the technology, how we think about  technology development. For example, forever beta   is a different way of developing software. What is, I think, one of the most challenging  

jobs of any today is the CIO job because of  some of these changes going on. The CIO has to   keep everything running and all  organizations are so technology-dependent.  I think we saw, during COVID, what a lifeline  technology was to keep every organization   running. The CIO role needs to be so much more  beyond that. It's about – as you said, Michael,   and the question coming in – innovation.  It's about thinking to the new and changing  

the approach. It's about inspiration. I'm intentionally using I's with all   these. These are the redefinition of the  CIO is information and infrastructure to   innovation to inspiration; inspiring the  business colleagues in terms of what's the   power and the new way to apply technology. It's the intelligence officer in terms of   understanding different possibilities and what's  out there. It's the inclusion officer in terms   of looking to create the talent and build the  inclusive and diverse talent that you need to   build technology properly. I think the CIO role  is increasingly stretching along these different  

dimensions, which makes it hugely exciting  but it also makes it a very challenging role.  I think one of the biggest challenges that all of  us (that are involved in technology and applying   technology) need to really do and think about  is helping reimagine what the future can be,   reimagine how you can do the business differently  because I think, too often, we get stuck in seeing   new technology, just pasting it in, and applying  it the same way we were doing things before.   There's a real need to resist that  temptation and look at how we create   that change as we go forward, which is why  we fundamentally wrote Radically Human.  Can you elaborate, Paul? If you were a CIO  (Chief Information Officer) today, what would   you be doing with respect to all of this? I'd be trying to really create a learning   organization because things are moving so fast.  By learning organization, I mean a learning  

organization within IT, but also cultural change  to help inspire the rest of the organization to be   a learning organization because,  with the technology moving as it is,   IT needs to move faster and reinvent themselves  every day to understand the new technologies   and what the possibilities are. The only  way to do that is by creating a learning   environment, a learning organization. We have something we call TQ (technology   quotient), which is a way we educate, inspire, and  inform all of our people in addition to all of our   other learning platforms. I'd encourage  everybody to really think about that.  The quote I keep making is, "You can't go hire the  skills of the future because they don't exist yet.   You have to figure out how to create them in  your own workforce," in addition to refreshing   and bringing in some from the outside. Then you need to do the same in the  

business because a lot of the next generation  of technology is about democratizing technology,   access, and impact. It's creating the learning  capability within the whole organization, so   you're democratizing through low-code/no-code  tools in terms of creating business capability.   You're democratizing decision-making through data  analytics tools and AI tools that are available to   more people across the business and such. The single thing I would zero in on   is a learning organization. The organizations  that can learn faster and spread it faster in  

the organizations, I think, are going  to be well-positioned for the future.  Let's go to some questions from Twitter. Arsalan  Khan says, "Large organizations have tons of data   that they can use for innovation. How can small  businesses compete when they don't have that much   data to work with?" I will just add, when they  don't have that much data but also their level   of sophistication and access to sophisticated  skills is less compared to large companies.  There are two sides to that. I think  large organizations do have access to data  

and sometimes more data and such and the skills.  But the democratization of technology is real.   The capability that you can easily access  through the cloud platforms, the AI engines,   and capabilities that are widely available is  profound, and it really does democratize the   access to smaller organizations. Yes, if you're in a really small   organization, do you have somebody who has  the time to go out and learn those tools?   That may be a challenge in some cases. But it's  very different than the way it was 5 years ago, 10  

years ago, or 20 years ago where you need to stand  up teams, data centers, and infrastructure, and   make big investments to get this stuff working. You could access a capability through an API,   a service, and a cloud platform, and funnel data  very quickly to do some very profound analysis. We   write about some examples in the book about very  small organizations who have taken advantage of   that capability to improve their businesses. I think there are two sides to that. Yes,   the big organizations have an advantage.  But the democratization of the technology   combined with some new learning technology –  we talk about few-shot learning, for example,   which is a much simpler way (sometimes  powered by the cloud platforms) to train   AI algorithms based on just a few instances  of data rather than hundreds of thousands of   instances of data – those types of techniques  stand to leverage the playing field more. 

There's a real opportunity for smaller  businesses because it's just so much easier   and so much cheaper, for one thing, to build that  infrastructure that you were just describing.  That's right, and there's a lot of publicly  available data and such as well, and   different platforms are opening up different  sources of data. It's all about figuring it out.  Any small business is going to have this strategy  of what differentiates you and then figuring out   how you get that data, whether it be big or  small. How do you access some of that data   to create the advantage you need? We have another really interesting   question, practical question, this time on  LinkedIn. This is from Suman Kumar Chandra  

who says, "How can CIOs bring themselves up to  speed to decide which technologies will be most   useful for their business and how to use them when  there are just so many technologies on the market?   Every day, new technologies are coming up. How  in the world do we prioritize and find our way   through this forest of great technologies?" That's again another reason why the CIO   job is a challenging one because the old  technologies don't really go away. They're   still out there somewhere in the closet,  and you need to take care of the current   and the legacy technologies as you investigate  and learn about the new and apply the new.  I think there are a couple of things I would  say. One is, it is about prioritization,  

figuring out those things that do make  a difference to your business, and   in channeling or in prioritizing and allocating  the appropriate amount of resource based on that.  For example, if you take different categories  of technology (with cloud technology),   we see many organizations, most  organizations moving rapidly to cloud.   Roughly, we see most organizations having  about 30% of their workloads in the cloud   – on average. A lot left to go  with the cloud migration still.  What's important about that, if you look at  that 30% statistic on cloud I just talked about,   if we ask another question about how much  are you really leveraging the power and   innovation of the cloud, only 13% of companies  say they're really doing that. So, 30% of the   workload is in the cloud; only 13% believe they  are leveraging the innovation because migrating,   getting the workload to the cloud doesn't, in  most cases, deliver the full potential yet.  That's kind of part of the answer to the question  of prioritization. To the extent you can get to  

the cloud, which is not just about cheaper compute  – it's about standardized platforms that allow   tremendous access to innovative capabilities,  services, and such – it becomes the platform   to drive your innovation at greater  velocity. That's one thing, I would say,   that we hear from customers (as we help them move  to the cloud) is, getting there is one thing but   then really growing and innovating the business  in the cloud is where they want to go from there.  It's kind of prioritized like that. I'd say  that's a strategy to prioritize so you can   get to a more innovative, higher  velocity innovation environment. 

You look to things like artificial intelligence. I  think every organization needs to be investing in   artificial intelligence in different ways. Do you need to be doing, again, the   most sophisticated deep learning neural network  models in every part of your business? No,   probably not, but you should be looking  at where it can make a difference.   And also, have teams looking at studying  the new techniques, studying the   new, evolving techniques, the common  sense, emotional AI, and other things   so that there's some effort being applied on  that and some effort being applied on scaling   the real capability and creating the centers  of excellence for that that you need to drive.  But as you look at newer things, metaverse  is coming on the scene and probably   the most talked-about technology. It's probably  the biggest surge of interest we've ever seen in   any technology (over my 30 years) has been what's  happening with the metaverse (in recent times). 

That's a technology where, again, it's not just  for tomorrow. There are implications of it today.   Depending on your industry and what part of  your business you're looking at, there are   moves you need to be thinking about today and  making today, in addition to areas you need to be   learning about and applying. For example, thinking  about augmented experiences for your workers   and virtual experiences for onboarding employees  and training employees, which we do at scale   in our company, as an example. That's today. Thinking about at-scale NFT-based products and   how you're going to leverage traditional  currencies and such, certainly should be   understood, and maybe dipping your toe into those  as well, but at least in the understanding curve.   I kind of look at it as a prioritization across  the spectrum and really keeping an open mind   as you look at the prioritization. Be sure to subscribe to the CXOTalk   newsletter. Hit the subscribe  button at the top of our website. 

Paul, the metaverse has become very  important to you. You just formed, I believe,   a new business unit focused on the metaverse.  Why? Why does the metaverse matter that much?  What we've done, to think about the metaverse,  we started this in Radically Human and then we   released our technology vision and expanded on  this concept. We really believe that businesses  

need to frame the way that you think about the  metaverse in a different way than you hear about,   generally, in the media. The metaverse isn't just   about consumers. It's not just about NFT and  cryptocurrency. The metaverse is really about the   next stage of how we create digital experiences. We call it the metaverse continuum. I'll come back   to what I mean by continuum in a minute. That's  an important way to think about it. If you reframe   your thinking this way, then a lot of aspects  of the metaverse become relevant immediately.  Today, a fundamental driver and why I  believe you can't ignore the metaverse   is because it really is driven by fundamental  technology advances that are happening. Whether  

you want them to or not or whether you  like it or not, they are happening,   and there are opportunities and generally positive  changes that are happening with technology.  Web3 is a big part of that. Web3, the  technologies coming out about Web3,   do enable a new set of experiences that  are enabling the metaverse capabilities. 

Web1, of course, being search and  basic data on the Internet where Google   Search was the killer app. Web2 being  (about a decade ago) social, mobile,   apps, and such came online. You saw the sharing  economy companies being the killer apps as 4G and   other technology proliferated. That was Web2. Now we're seeing Web3, and Web3 is adding two   new capabilities. Web3 is adding the Internet  of Place, which is shared, collaborative spaces  

not just through virtual reality, but through  2D reality or 2D interfaces as well: phones   and laptops. It's also creating an Internet of  Ownership for the first time having real distinct,   provable, verifiable identity, authenticity,  and ownership, which you couldn't have in   the Internet where if something forwarded  once, it could be forwarded a million times.  That Internet of Ownership and Internet of Place  is creating a potential for transformation bigger   than the jump from Web1 to Web2. That's why I  believe the next decade of digital transformation   is going to be bigger than the decade before. Michael, you mentioned we just introduced our   Tech Vision this year (earlier this month).  The title was "Meet Me in the Metaverse."  

Our Tech Vision ten years ago was titled  "Every Business is a Digital Business."  When we said that ten years ago when Web2  was coming online, people disagreed. They   thought that was farfetched and such,  but it really quickly became reality.  

The last ten years have been about every  business moving to become a digital business.  I think, with Web3 coming, and the metaverse,  it really is about a decade of even bigger   transformation than the one we've seen because  the new technologies fundamentally changed the   inside of how you do digital. They don't just wrap  digital around what you were doing previously,   which is why this is something every  business leader and technology leader   needs to understand going forward. The final point on it is,   what I mean by the continuum, as you reframe  it, is it's not just about the consumer things.   You read about Bored Ape and different  things you might see out there, Roblox   and such. It's about employees and what you do. We'll onboard 150,000 people in Accenture using  

virtual reality into our Nth Floor metaverse this  year. We've hosted our leadership, board, and many   clients in the metaverse. And so, it's creating  those new experiences for employees and workers,   not just consumers, and changing the way you work. It's not just about 3D experiences. It's about the   2D and how you blend the 2D and 3D. It's not  just about the virtual. It's about reality,   how you combine augmented work and digital twins,  edge, and such in to create a streamlined and   integrated virtual to real-world and back type  of experiences. It's a continuum in terms of  

time, as the metaverse, Web3, and  these technologies mature over time.  If it's not obvious, I believe this is a big deal.  I think this is going to be one of the things   (along with a few others that I can talk  about) that will define the next decade when   you think about how you apply technology. What's the timeframe for adoption of these   technologies, of the metaverse, do you suppose? Like any wave of technology, it gets a label after   it's been around for a while. We were doing  cloud work before the cloud became commonly   used. It was called utility computing and other  things, as you will recall back in the day. 

Similarly, augmented reality, virtual  reality, blockchain, digital currencies,   all the constituent components of this digital  twin technology, these things have been around.   What's happening with the state of  technology is the standards are converging,   the scale is increasing, and as some of these new  technologies are coming online to enable you to do   this in an integrated way as an enterprise. It's already happening. We have companies   doing interesting things. As I said, we'll onboard  150,000 people into what we believe is the biggest   enterprise metaverse, which is our Nth Floor. We're doing interesting work for clients around   augmented reality so that you can use a  digital twin to simulate performance and   then use augmented reality to change plant  performance in real-time, things like that,   blending the experiences together. For trading  organizations, very sophisticated organizations,  

in real-time, using the technology  in many different applications.  I'd say the retail and financial services right  now – an overwhelming interest and a lot of   experimentation – the real work we're doing with  clients is around creating their metaverse retail   presence, their metaverse products. How do they  bridge the real products and the digital products?  Things like Gucci's purse. Gucci's purse  sold for more in their metaverse than it   did in the real world. Things like that are  raising a lot of interest and attention. 

One point that I find very interesting  is, you're thinking about the metaverse,   thinking about digital twins as part of  the talent culture and training because,   historically, we've thought about digital twins  as being manufacturing equipment, simulating a   jet engine or a nuclear reactor, for example. My view is that we're on a journey that's going   to happen relatively fast for the enterprise  itself and business itself to be a digital twin.   The analogy I'd use is to think about  an annual report a few years from now. 

The annual report today, you read it on paper.  You post something online. It's kind of one-way.  You think about an annual report where you  can step into the company's board room,   interact with the executives, and hop off  to a retail store and see how consumers   are engaging with the product. Then go over to a  plant and see how they're manufacturing it. That's   not too far in the distant future. Think about  the engaging experience that you can create there.  As an executive at the company, think about  having that same kind of capability, so you can   see a digital twin of the business and simulate  different kinds of operating characteristics   and environments. Change and reconfigure the  business as a result. That is the path we're on,  

I believe, with enterprise technology. Again, the current wave of digital has   been a little bit of wiring the plumbing to  allow that to happen. The next stage that   we're entering into is a real exciting stage to  really run businesses differently. This is why   the connection to radically human comes back  in because I think this is a really interesting   future in terms of the potential of workers, the  potential of leaders, the potential of consumers   to use services in a much more compelling way. Wayne Anderson says, "What kind of antipatterns  

have we picked up during this tech and human  symbiosis that will hold us back from developing   as radically human, as the way you've been  describing it?" What do we have to change?  That is something that we need to work on. To  be honest, that's why I wrote the first book,   Human + Machine, because I was concerned about  the antipatterns and we wanted to put them out   there and show how they could be corrected. A lot of the work of Human + Machine was showing   positive potential and how to overcome things  like the fear of the technology, the fear   that it was going to put everybody out of their  jobs, the fear that it was going to take over   the human race and all these things,  which we fundamentally don't subscribe to.  I think some of those same patterns are still out  there because there's a fundamental human behavior   that we're the ones who create technology, so  technology doesn't create itself. We create   technology, and then we fear it. [Laughter] There's this dynamic with every technology   that comes about. We're seeing this with metaverse  right now and a lot of backlash against metaverse  

(justifiably so) because there are a lot of  real considerations around trust and privacy,   inclusion, children's access, and many other  things that are real concerns in the metaverse.   But that's true of the real world. It's just  a mirror of the real world and a mirror of us,   and they're all things that we  can deal with in the right way. 

One of the things we talk about in Radically  Human, and we also talk about in our Tech Vision,   is this idea of responsibility and trust. We  believe that, in the Web2 era, as an industry or   as a technology industry, we didn't start Web2  with enough focus on responsibility and setting   it up to avoid the antipatterns, as you say. We're at a point with Web3 and metaverse where   we can get it right this time. That's why we  (as an organization and individually) are really  

focused on all the elements of responsible  metaverse, which is trust and safety   around use of the Internet. It's data  privacy and identity, which again there are   very promising solutions to  with the Web3 technologies.  There's inclusion and behavior on the metaverse,  and a variety of other things, that we all need to   focus on. I think it's all of our obligation  to really study and understand these things   so that as we build our early forays into  metaverse (or with any new technology),   we're applying it in a responsible way and  avoiding, as you say, the antipatterns.  The other big issue that I've been very focused on  for a number of years, and still very focused on,   is how we create the right environment and  skills to enable this in a lot of those that   don't have the digital skills to succeed in  the new environment. That's why we've been   very focused on reskilling and talent creation.  How do we create people who can build these new  

jobs that don't exist at scale yet: the world  builders of tomorrow, the AI ethicists, and such?  That's why we're donating all the net proceeds and  royalties of Radically Human to organizations who   are focused on reskilling those who don't have  current access to those skills that they can   have viable skills in the new  economy that's being created.  Bhagya Subbareddy says, "Can you share a few  tips with CIOs on how to bring business along the   journey of the reimagined future?" Specifically,  she's talking about managing change for large,   global organizations that are risk-averse. Two things: One is education, and really   just focused on the education because I think  that goes a long way, education case studies,   and ways to help people understand the impact. The second is advice that we talked about,   as we're releasing our Tech Vision, which  is an approach of think big, start small,   and scale fast. Think big and educate around the  big potential. Start small and in a focused way  

where you can prove the results. But do that in a  way with the architecture, the foundation, and the   approach that you can scale it fast and meet  the expectations of the business as you go.  Arsalan Khan comes back, and he says, "To be a  data-driven organization, we need to have culture   and executives that have no veto power over  data recommendations. Do you agree or disagree?"  You need a clear and unified data governance  approach, so it's clear who can make the data   decisions. I think, in too many organizations,  the data governance is fragmented and not clearly  

understood. And so, you end up with different  versions of the truth and all sorts of things.  I think I agree with the question,  but I think it comes down to   a single, agreed-upon data governance approach.  Shailesh Pachori says, "What is the mantra  for success when it comes to adopting   current technology?" What's the  foundation of how to be successful?  Business value and human acceptance,  so implementing something that clearly   improves the business so people see the value  of doing it, support it, and rally behind it;   and the human acceptance, doing it in a way where  some of the constructs we've talked about today –   the machine teaching, the experience, the trust  – are thought about in a way where people are   accepting, using, and maximizing use of the  technology to increase their own potential.  Okay. With that, unfortunately, we are out of  time. We've been speaking with Paul Daugherty.   He is the group chief executive for technology at  Accenture. He is also Accenture's chief technology   officer. He wrote this book. It's called Radically  Human. His previous book was Human + Machine. With  

that, Paul, thank you so much for coming  back and being a guest on CXOTalk again.  Thanks. It's always a pleasure talking. I look  forward to the next time as well. The time really   flies, so thanks to you and your audience. Speaking of the audience, thank you,   everybody, for watching, and especially  to those folks who ask such insightful   questions. I love the CXOTalk audience.  You guys are so smart and so experienced.  

I certainly learn a lot from your questions. Before you go, please subscribe to our YouTube   channel, hit the subscribe button at the top of  our website so we can send you our newsletter,   and keep you up to date on who we have  coming up as guests. Thanks so much,   everybody. I hope you have a great day,  and we will see you next time. Bye-bye.

2022-04-23

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