How will GenAI transform the workforce?

As the capabilities of generative AI rapidly evolve, professionals around the world are watching attentively—and wondering how the technological leap will affect their careers. There is opportunity in this moment, and also some uncertainty. How disruptive will GenAI be to the workforce? Which sectors are likely to see the biggest changes? And what should business leaders be doing now to harness the potential benefits of GenAI tools for their workers? In our latest episode, hosts Lizzie and Ayesha sit down with Jerry Kaplan, an AI expert and author, and Scott Likens, PwC’s Global AI and Innovation Technology Leader, for a conversation about the cutting edge, where GenAI is shaping the future of work.

Jerry Kaplan: This will be like domesticating animals was over the history of humanity. We’ve created something extremely powerful, and, yes, your horse can kick you and kill you, or you can ride it. And all of a sudden, you don’t have to use your own feet if you need to go a long distance.

Scott Likens: These tools will help us think differently as leaders. And I think the workforce will start to embrace it a bit, versus being afraid of it. They’ll see the power, and you’ll see more daily use. You’ll see more creative aspects coming from people that didn’t, really, maybe have that creative brain before.

Jerry: What can you now use the machine to do that you used to use a human to do? And that is going to disrupt industries, and some industries more than others. But we’ve been through this before: the internet disrupted almost every industry.

Lizzie O’Leary: From PwC’s management publication, strategy and business, this is Take on Tomorrow, the podcast that brings together experts from around the globe to figure out what business could and should be doing to tackle some of the biggest issues facing the world. I’m Lizzie O’Leary, a podcaster and journalist in New York.

Ayesha Hazarika: And I’m Ayesha Hazarika, a broadcaster and writer in London. Today, we’re talking all about the jobs of the future and, specifically, how artificial intelligence is going to reshape our careers.

Lizzie: Across all industries, AI is moving fast. Progress in generative AI has been so dramatic that, in some areas, its output has become indistinguishable from that of humans. From screenwriters to insurance underwriters, many people are asking a question that until recently would have sounded like science fiction: can an algorithm do what I do? And, if so, what does that mean for me?

Ayesha: Meanwhile, there are predictions that artificial intelligence will add more to global GDP by the year 2030 than the current output of China and India combined—and that this growth could be more than enough to create many good jobs, while reinventing how current jobs are being done.

Lizzie: In this episode, we’ll be asking how AI is likely to transform different sectors, and in what way—and how can leaders of today prepare for all the changes, challenges, and opportunities this new era brings.

Ayesha: To find out more, we’ll be talking to Jerry Kaplan, an AI expert, author, and Silicon Valley veteran. But first, let’s bring in PwC’s Global AI and Innovation Technology Leader, Scott Likens. Scott, welcome. Thanks for joining us.

Scott: Thank you so much for having me here, very excited about the conversation.

Ayesha: Now, Scott, AI has been around for a long time, but, today, we’re talking about a particular kind of AI—generative AI—and I think it would be useful for you to just give us a clear definition of what that is.

Scott: I’m glad you opened up with the fact that it’s been around a long time. People forget there’s been over seven decades of research into artificial intelligence. Machine learning for the past decade has been something businesses have been investing in, and we’ve seen value. But about five years ago, when the transformer was created, there was something different happening, and really it’s a deeper set of machine learning, so, neural nets and deep learning. So the generative AI wave that we’re seeing that everyone is excited about is taking us into this new world where the machines and the AI can actually create new content or augment content we have. And that content could be text. It could be visuals, pictures, video. Could be audio. So instead of just using machine learning and these neural nets to predict an outcome, a single outcome, we’re seeing generative AI give us the ability to create brand new creative ideas. And I think the other piece of this is this massive amount of training. So the GPT, the pre-training—having the machines look at the entire internet or a lot of the internet, let’s say, and understand connections that humans just could never fathom, and being able to use that to generate new ideas. It’s really amazing.

Lizzie: Well, that must be coming up in boardrooms a lot right now. What are the questions you are hearing from business leaders right now?

Scott: It is pretty amazing to see the broad interest, and boardrooms are one of them. I’d say we went through this first phase, the questions were, what is it? Is it real? Is it just a flash? Is it the shiny object? So there was this educational wave. I say the summer was more of an experimental wave. So we’re starting to experiment with this in our organization. So the boards were asking, how do we start to dip our toe? Where do we start?

Lizzie: Hmm.

Scott: A lot of the questions were, tell me a use case, right? Very tactical, tangible, practical. We always step back and say, stop thinking about individual use cases and think about the power of creation, of generation, across your organization. Now, I think it’s about enabling. How do I look at my workforce and actually use this, either myself as an executive on a board or a CEO or a CIO? But how do my people use this? We’re in that enablement phase, which is exciting.

Ayesha: Well, thank you for those thoughts. Scott. We will come back to you very soon. But first, Lizzie, you spoke recently with Jerry Kaplan, who’s been working in this field for longer than most.

Lizzie: Yeah. Jerry is a serial Silicon Valley entrepreneur. He’s an adjunct lecturer on the social and economic impact of artificial intelligence at Stanford University, and he’s also the author of Generative Artificial Intelligence: What Everyone Needs To Know. I began by asking him for the long view.

You have been thinking about the social, economic, and workforce impacts of technology for a long time. And your latest book deals with generative AI—a technology that some people liken to the invention of fire. So, I guess I wonder, how disruptive does generative AI have the potential to be, especially when compared to other technologies you’ve looked at in the past?

Jerry: Well, I wasn’t around during the invention of fire, so I can’t really make that comparison. But I think that of all of the inventions in history that I think are most closely analogous to generative AI, I would say it’s the domestication of electricity. If you think about, in the late 1800s, before that, there was no use of electricity. It was known as a natural phenomenon. And then we began to harness it, first for the electric light bulb, and on and on and on, and all the way through modern computers. In fact, this may be much more than an analogy, because I think there’s an argument that generative AI is part of a century-long exploration of what we actually can do with electricity and what power it’s going to have for society.

Lizzie: When you say that, you know, you are painting a picture of something that is truly transformative. And one of the places that that gets talked about the most is on the workforce. You have people saying, generative AI is going to steal our jobs, or it will make them completely different. I wonder how you see its potential impact on how we work.

Jerry: Well, sometimes when you hear people talk about artificial intelligence, there’s a tendency to anthropomorphize it and to say, there’s us and there’s them, and they are coming for our jobs. And that’s not a productive or an accurate way to think about it. Generative artificial intelligence, and artificial intelligence in general, is really a new wave of automation. And automation is the substitution of capital for labor. We’ve been through many waves of automation, and this one will be no different. So, to understand its impact, all you need to do is to understand how previous waves of automation have affected our lives and our jobs. To give you a very short summary of that, it makes us more productive, and therefore, it makes us wealthier. That wealth will create new kinds of opportunities, because it’s going to get spent. And that eventually picks up slack in the job market, either through the expansion of markets or new markets that did not exist prior to the technology that it enables.

Lizzie: And so, in the short term, when we think about the changes that we’ll see rippling through the workforce, is that: this person is not needed because AI can do their job? Or, this person’s job changes?

Jerry: Well, it’s going to change a wide variety of types of jobs, and it’s going to create new ones. Again, I come back to the analogy of what has electricity done for us? What jobs involve or benefit from the use of electricity? Obviously, an awful lot of them do. I think we’re going to see the same thing here. The first phase is always substitution. What can you now use the machine to do that you used to use a human to do? And that is going to disrupt industries, and some industries more than others. But we’ve been through this before: the internet disrupted almost every industry.

Lizzie: Are there particular sectors that you have thought about that are likely to see the biggest changes?

Jerry: The most obvious ones, because it’s immediate, and we’re already beginning to see the effects today, are on what I might loosely call the creative industries. Because it becomes possible for a person to utilize a computer or work in conjunction with a computer to generate the kinds of creative outputs that previously could only be done by hand, by human beings. That’s why we’re seeing the impact first in those particular areas. And I’m talking about things like graphic artists, people who develop brochures or design logos. And obviously, writers of just about every variety, their work can be accelerated—I wouldn’t say supplanted, but accelerated—by proper and appropriate use of these new tools. One of the most surprising areas where we’re going to see significant disruption is in the practice of software engineering. The increase in productivity that’s being seen among people who do programming is astonishing. And at first, you might think, well, we don’t need as many programmers. Not so. What’s going to happen is it’s going to be economically viable to build programs to do all kinds of things that just, it wouldn’t have paid to do in the past.

Lizzie: You know, I would imagine, if you were listening to this and you’re an executive in a company, when do you need to be thinking, I’ve got to incorporate this into what my company does?

Jerry: In a year, two years, five years, ten years, there’s going to be all manner of systems that are going to be much easier to use and much more targeted for specific kinds of purposes. So it’s easy today to think that what we’re seeing is, my God, we taught this bear to ride a bicycle, you know? Look, it can do a picture. Look, it can generate a report. Oh, that’s silly. Look, it made a mistake. What a dopey bear on the bicycle—you know, it fell over. But that’s not really where it’s going to go. What’s really fundamentally happening here is that we need to change the way we view our use of computer technology. We’ll have whole departments of people inside most big organizations that will curate the data and decide exactly what should be fed in. So data curation is going to be very important. The process of training these systems to behave in ways that we find socially acceptable is going to be another major profession, whatever that’s going to be called. So they go through a period of socialization: no, you shouldn’t answer questions like that. You need to tell it this way. And that is very similar to the way in which we train our children or ourselves. And I think that will be a major profession. Teaching machines will be a profession very much like teaching humans.

Lizzie: Let’s talk a little bit about guardrails now. When we are thinking about AI, through the lens of the workforce, what do we need to be aware of?

Jerry: What we need to be thinking about is not, how do I regulate the technology? But, how do I regulate the uses so that what we judge as a society to be bad uses either are outlawed or are minimized in some particular way—and without holding back the tremendous benefits that society is going to get from a technology that is just so incredibly powerful. So, unfortunately, it’s, take your time, but keep your eyes open. So there’s some things we already know are problems: the effects on misinformation, disinformation, and propaganda that are created by this technology are very great. Well, let’s go to work on trying to see how and what we want to do to contain that. What I don’t think we need to be worried about is, there’s a lunatic fringe in this field of AI that has warned for a long time and is very vociferous right now that these machines are somehow going to come alive, rise up, and threaten humanity, and make humanity extinct. My personal view is, that’s nonsense. I think it’s exceptionally unlikely. I’m not even sure how it would occur if we wanted to do that. These are tools, plain and simple. We can argue whether they’re conscious or whatever it might be. They don’t have any goals or aspirations. They’re not going to be drinking our fine wine and buying up all the beachfront property and marrying our children. You know, that’s not the kind of thing we need to be worrying about. And they have no desire to wipe us out. If we build a machine using this technology to wipe us out, that’ll be somebody, a human, designing and building that and making that happen. And we just need to try to make sure that that’s as hard as possible to do.

Lizzie: Thinking about the future: I have a three-year-old, and I wonder all the time what the world is going to look like when he’s a teen, when he’s in college, when he joins the workforce. I wonder how you think AI, generative AI, might change his reality, you know, 15 years from now, 20 years from now.

Jerry: Your three-year-old is going to grow up in a very different world than we have today. It’s going to be a world where humans are not the only intelligent thing in the universe. This will be like domesticating animals was over the history of humanity. You know, we’ve created something extremely powerful, and, yes, your horse can kick you and kill you, or you can ride it. And all of a sudden, you don’t have to use your own feet, you know, if you need to go a long distance. That’s what this will be like. But they’ll have a very different view of the the place of humans in the world. This is going to be a shift of focus from humans to machines. In the future, when you want to get the most objective, accurate, sensible, and wise advice, you’re not going to turn to a human being. You’re going to go ask a machine.

Lizzie: Jerry Kaplan, thank you so much for talking with me.

Jerry: Oh, thank you very much, Lizzie. It’s been a pleasure.

Lizzie: Scott, let’s start with what Jerry was saying about the potential impact on the workforce. He was relatively optimistic that deploying AI will replace tasks but not remove jobs. How does that tally with your experience on the ground working with clients?

Scott: I tend to take a similar view. I like to step back and think about, we’ve been through these cycles before; they’ve just taken longer. I saw the birth of the internet working on the first browser in the ’90s. But it took decades for that to be infused into businesses. So I think here we’re seeing a pace of innovation that’s different. But the fact is it’s going to enable us as humans to do our jobs better if we embrace it and we create a responsible way to use it. Being positive around this is important, but being responsible around this is more important. Thinking about what guardrails to put in place so that we do use this in a good way for society, of course, and for business.

Lizzie: Scott, you’re talking about this pace of change and this, frankly, exponential pace of growth. I wonder if there are lessons that have been learned or that you have seen from early adopters about harnessing the power of AI and how that has changed a workforce, a company, kind of, what you’ve seen in this rapid transformation.

Scott: I do see the early adopters finding value and then reinvesting it in a bigger way. So, a lot of them started in small business units, and now they’re rolling it out across finance and to other areas just beyond IT. I think the next wave is at product development. We’re already starting to see it in being able to turn around products much faster, which is great. I think the others that are waiting, they’re waiting for that magical use case. That’s just not how this happens. You have to infuse it into your day-to-day and transform big parts of your organization. This is not the days of machine learning, where you solve one problem better. This is the days of generative AI that’s solving a lot of problems better, all at once. Unfortunately, we always try and go back to patterns we know. And this is not a pattern we know. We’ve never seen it before. So we have to take some risk. And I think we have to reinvest that, then, as we see success.

Ayesha: And I know you’ve deployed this technology inside PwC, Scott. What is your experience of the impact on people and on your own productivity?

Scott: We went down the route of, let’s give you a safe, secure environment to use it for work. Do not use the open public models. Use the secure, private model that we’re giving you, and think about how to change the tasks that you do day-to-day right now. But think about the future transformation opportunities. So, as you’re working with clients, think about how their business could change by using this tool. You can’t advise them if you’re not using it yourself. So we want people to learn that way. We want to enable them in a safe and responsible environment. And then we want them to innovate. I think citizen-led innovation, and just the grassroots innovation, is really important. But then again, translating that into business transformation or business reinvention is a big task, and we need a lot of people to think about it.

Lizzie: You recently published research showing workers were more likely to be optimistic than pessimistic about AI, but that they do have significant concerns around how they acquire the right skills, what it means for their future. So how should employers address those fears?

Scott: So, I think as an employer, you should embrace upskilling your whole workforce. You can’t just create pockets of capability. This should be for everyone to do their jobs better and find ways to be more efficient and create more productivity. Instead of just looking at the efficiencies, let’s look at the upside revenue opportunities, the profitability opportunities, new product opportunities. That’s going to come from the entire workforce. So for us, it’s about raising the floor for everyone, digitally upskilling and AI upskilling everyone, so that there’s this bigger, greater capacity to use technology across the entire workforce. And some of it is as easy as just starting and just prompting some of these models to see how they can help you.

Ayesha: And following on from that, how should workers and employers be thinking about skills in the age of GenAI? And whose responsibility is it to train employees on this newly developing tech?

Scott: It’s moving so fast, I think some of the challenge is, what do you even train on? Again, no matter when you hear this, something will have changed, because things are changing almost daily in the technology. So, part of the challenge is having a really flexible training curriculum. So I think it’s the responsibility of employers to enable this, but it’s also the responsibility of employees to be curious. Instead of just looking at it as a negative—it’s going to take away parts or all of my job—think about it as a positive. We can enable our employees to have access to the right tools to learn and then responsibly push them along this journey together.

Ayesha: Over the last few months, there have been a number of international events, summits, gatherings, occasions where governments across the world are coming together with tech giants to discuss the advancements in AI, but also to discuss regulation. How important do you think it is to have these big gatherings on an international level?

Scott: Yeah. I feel even weird saying this as a technologist, but this is an area I think some regulation is needed. Some technologists say that robots are going to take over the world, and some say, no, no, no. It’s fine. It’s no big deal. But this is an area I think we need to get ahead of. Now I do think there’s different perspectives around the world. So the EU has a different perspective than the US, than Asia-Pacific. There’s still a bigger problem to solve, but I think the first step is getting some of that together within regions. But I hope it’s done right. I hope it’s done in a way that creates that innovative spark. It gives some autonomy, creates that innovation platform. And so far, we’re seeing some of that.

Lizzie: If you have a business leader who comes to you and says, I want to upskill my workforce. I want to harness the benefits of AI, but I don’t know where to start. Where should they start?

Scott: I always start with the strategy around a secure environment and a way to upskill your people responsibly. How do you bring this tool into your enterprise? You have to think through this. So there’s ways to do that with partners, there’s ways to do it yourself. But if you don’t have that, experimentation becomes dangerous, because you don’t control the risks. So I say start with that secure area and the responsible strategy of where you’re going to implement this in your business. The enablement then looks at the patterns of ways to use generative AI, because it doesn’t solve every problem. Where is there an area I can augment or create new content or help my teams do that faster? And finding ways to test that out quickly, I think, is really important. So I say, start small, but with a strategy around a responsible and secure way to use this technology.

Ayesha: So, Scott, can you look into your crystal ball and give us an idea of where you think AI adoption by business will be in, let’s say, 12 months from now?

Scott: I’m glad you didn’t say five years, because I could never answer that. Twelve months from now, I think every business will be dabbling to some degree in generative AI amongst different areas of their business. I think large portions, probably 50% or so, will be implementing transformational generative AI. There’s no barrier to using it anymore—again, if you do it securely and responsibly. Let me restate that. But, absolutely, this will be infused across businesses. These tools will help us think differently as leaders. And I think the workforce will start to embrace it a bit versus being afraid of it. They’ll see the power, and you’ll see more daily use. You’ll see more creative aspects coming from people that didn’t really maybe have that creative brain before. They’ll be using this to really extend their own skills. So I’m excited. I’m a little bit frightened about how fast it’s working, or moving. But I love technology, so I’ll roll with it.

Ayesha: Well, Scott, it’s been such a pleasure speaking with you. Thank you so much for your insights.

Scott: Thank you. It was fun.

Lizzie: Ayesha, I am struck by something both Scott and Jerry talked about, which is the speed of this transformation, that this technology has been developed for decades and decades, and yet we have had this exponential explosion of AI tools being deployed and AI in the workforce and AI within different aspects of companies. Like, it’s all finally happening. It’s all coming together. I think that’s both why there is such excitement and, among some people, such trepidation about how quickly all of this technology is rolling out.

Ayesha: Listening to Scott and Jerry, the big takeaway is, look, you know, you have to be positive about this, because it is coming down the track. Whether you’re a CEO, whether you’re a tech expert, everybody is dealing with AI in some way. So you have to be positive, but you have to be responsible. We do have to innovate. But we also need the right regulation, and we actually do need the right guardrails. And I think that’s really fascinating to hear that from this very innovative community of people.

Lizzie: Well, that brings us to the end of this episode. Next time on Take on Tomorrow, we’re headed to Davos, and the World Economic Forum’s annual meeting. Join us for a special episode, where we’ll be asking how businesses can take action on their energy demand and thrive in the energy transition. We’ll also be releasing the findings of PwC’s 27th Global CEO Survey, which provides key insights from thousands of CEOs around the world on issues facing business, society, and the global economy.

Ayesha: Take on Tomorrow is brought to you by PwC’s strategy and business. PwC refers to the PwC network and/or one or more of its member firms, each of which a separate legal entity. 

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Lizzie O'Leary

Lizzie O’Leary
Podcaster and journalist

Ayesha Hazarika

Ayesha Hazarika
Broadcaster and writer


Jerry Kaplan Artificial intelligence expert

Jerry Kaplan
AI expert, entrepreneur, author, Generative Artificial Intelligence: What Everyone Needs to Know , and Adjunct Lecturer at Stanford University 

Scott Likens Global AI and Innovation Technology Leader, PwC US

Scott Likens
Global AI and Innovation Technology Leader, PwC US 

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Matthew Wetmore

Matthew Wetmore

Global Industries & Sectors Leader and National Managing Partner, Clients & Markets, PwC Canada

Tel: +1 403 509 7483

Scott Likens

Scott Likens

Global AI and Innovation Technology Leader, PwC US

Tel: 312-286-0830