How can we reimagine workplace productivity with GenAI?

0:01It's not that Gen.ai will take your job, right? It's the person that knows how to use the tools that's probably going to take your job. You can protect people, but you can't protect jobs. Jobs will continue to evolve, and they always will do. You have to be a bit of a dreamer. It's going to be really amazing if you look into the future to see what could be with this technology. Two years ago, it all felt like the world, including our jobs and how we work, would change forever. ChatGPT and other similar Gen AI technologies crashed onto the scene, impacting the way we think about everything, from drug discovery to how we communicate.

0:41Now, more than two years later, how is it changing how businesses run? And how can organizations roll out the technology to create a real impact, helping workers become more productive along the way? From PwC's management publication Strategy and Business, This is Take On Tomorrow. I'm Lizzie O 'Leary, a podcaster and journalist. And I'm Femi Oke, a broadcaster and journalist. This week, how is Gen. AI transforming the job market?

1:15Today, we'll be talking to Svenja Goodell, chief economist at Indeed, a global job site. She's been looking into how Gen. AI is transforming the workforce. First, we have PwC's global workforce leader, Pete Brown, with us to talk about what we can learn from companies considered early adopters of Gen.AI. Welcome back to the show, Pete. Thank you, Lizzie. Thank you, Femi. It's lovely to see you. Pete, we have talked about Gen.AI in the workforce and workplace on this show before, but what is the conversation that is happening today in companies? Are they eager to embrace this technology? As I reflect through probably every single conversation I've had with a client in the last year.

1:58And dare I say, if I added all my colleagues at PwC as well, I don't think I've had any conversation where the words Gen AI haven't come up. Does that mean they want to embrace it? I think it depends on the organization. Some are, and some are yet to start. But it certainly sparked huge curiosity and interest, there's no doubt. What was really surprising to me, though, against that backdrop and this tsunami of interest is that we survey workers every year just to work out what's on their mind, what's motivating them in the world of work. And only 12 % of workers say they're using Gen.AI in their day-to-day work.

2:36That was a surprisingly low number for me. So I think to answer your question, huge conversation topic, varying degrees of implementation adoption. Later, we'll hear how Gen.AI is completely transforming the way some businesses work. But first, what workers really need to know about what Gen.A.I. will change in our jobs. Femi, you spoke to Svenja Goodell, who's been looking at this in her role as chief economist at Indeed. Exactly. And I began by asking her about the type of changes and trends she's noticing in her work. AI is everywhere, right? We have been talking about it nonstop and are actually able to see some of these movements in our data.

3:17So we developed a new generative AI tracker that looks at all the different mentions of Gen AI inside job postings. Could be either for the creators of Gen AI, for example, someone that has to write a particular prompt, or a user of Gen AI, a marketing professional that has to be able to deal with these tools. And we saw over the last two years an 83x increase in those mentions, but we're still only about two out of every thousand jobs mentioning some sort of Gen AI term. So still early days here. Svenja, you are in a position to see trends across different economies in different parts of the world.

3:55What are you seeing? They're looking at what types of frameworks do we need to have in place in order for Gen AI to be successful in a given economy, right? Do you need certain digitization to have happened already? What does the educational system look like? What other support pillars do you need in order to make sure that Gen.AI can be used for good and have a productive impact in emerging economies versus fully developed economists? So there are a lot of conversations happening with that and I think made great strides in terms of providing access to a lot of people. But how, as a world, can we make sure that no one is left behind?

4:37So the basic needs are met in order to have Gen.AI be a tool that can be productive in a bunch of different settings. So what kind of tasks can Gen.AI help most with? It really helps to understand first what skills are being impacted, because a job really is a collection of skills and tasks that you perform. And Gen.AI is quite good at the technical knowledge, having a bunch of information gathered across really the entire web and everywhere else it can access this knowledge. So quite good at that. Not so great at problem-solving skills, like leadership skills, empathy, creative problem-solving.

5:15And the results were very mixed when looking at all skills and the need for physical execution, actually being physically present. Sometimes Gen.AI does really well because you're coding, for example. You can do that remotely, right? It doesn't require a physical presence. However, if you're taking blood, you're a nurse, having an actual physical presence there is really important. So their Gen AI doesn't do all that well. So I think the really important thing is, as you figure out what is Gen AI good at and what does that mean for me, I always think it's not that Gen AI will take your job, right?

5:51It's the person that knows how to use the tools that's probably going to take your job. So get in there, go figure out how to use these tools to your best advantage and see how you can be a more productive version of yourself. Svenja, we've been discussing AI as helping us do our work better and what additional tools can it bring to our work. But is there a way that Gen AI could actually create new kinds of services and new kinds of work? Absolutely. To me, Gen.ai is a game changer, just like with the computer, which was also a game changer and fully introduced new jobs out there. I don't think, at least with current data, that Gen.ai is going to wipe out whole jobs.

6:32It will, however, create new jobs, right? The prompt engineer, for example, is a pretty new job out there. Of course, some aspects of jobs will become obsolete. That's normal. That happens as part of any transition in the labor market. But I think you have to be a bit of a dreamer, right? A bit of an optimist to see what are the cool things that could actually happen with this. And I think we're starting to see some of these things happen in real life already. In farming, this technology where you have image detection of weeds in a field that happens real time. And then a laser goes in and zaps the weeds in the field as the machine drives through the field.

7:08That takes a ton of AI. And it's just amazing, right? And I think it will become incredibly powerful when you start to combine the thought of self, if you will, of Gen.AI with the actual machine, the automation part of things. If we can have robots be smart thinkers and react to certain things with the help of Gen.AI, I think the possibilities will be amazing in terms of what we can do. And I'm pretty optimistic that we're onto something here. We'll see some really cool applications, and it's still incredibly early to see a lot of that. Gen AI is supposed to help us save time, be more productive.

7:46But what could be the challenges to this in the workplace? We talk about Gen AI as being an incredible time saver at first and can start to help us do anything really fast. And there is a distinct learning curve here, right? There is, you have to actually understand how to use this tool. You have to make sure there are no hallucinations in the answer, meaning you're not getting made up things back from the tool. And I think that's really important to recognize. there is a training curve and you're going to have to learn a whole lot of stuff, how to interact with these and how to properly use them before you can actually start to save a whole bunch of time.

8:20And that's normal. That's always the case for new tools. So if you were going to advise somebody who's looking for new work opportunities in the job market, what would you tell them about Gen.AI? First and foremost, I feel like people should always be passionate about the job that they do, right? So that was always my first answer. Find something that you love to do because that's going to help you stick with it, right? But then given the fact that currently Gen.AI is not a whole slate replacing anything quite yet, I think it's really important to choose a job that you think you want to do for which there's good demand out there, right?

8:57And then learn the tools that will actually help you be successful in that job. So if you're an economist, I would strongly encourage you to start to learn how to code things and how to work with large data sets. Maybe you want to learn some large language models and how to work with those in order to do fairly detailed research on whatever topic you're getting into. So I think all these things are really important. Know the tools, know the technology, and how you can use it to actually get to your goals faster. And if you take a step back for a moment and look really big picture, if you look at where we are in the U.S.

9:31and many other industrialized countries around the world, we're facing a bit of a demographic cliff. Our labor force is going to start shrinking because our populations are getting older. And that means we're going to start feeling the crunch in terms of workers very soon. So workers are going to be in demand. So you can think about health care being a really large sector that's going to continually demand new workers. And then how can you use these tools to be able to make you even more productive in that setting? I'm thinking about policymakers who are listening to our conversation right now and listening to the changing work landscape.

10:07What recommendations would you give to them regarding Gen AI in the workplace? Policymakers have a pretty tricky job. They have to figure out what should be regulated. Can it be regulated? Does it need to actually be regulated? And especially for policymakers, although I'll say a lot of companies are thinking about this as well, of course, the side effects of Gen AI are really important to consider, right? There are certain biases that are inherent in our data and we train our models on. So how do you make sure that these biases aren't carried forward? So there's a lot of ethical considerations to be paid attention to.

10:40You want to make sure that no one is left behind in this advancement. Does everyone have access to this technology? What does it mean for workforce training? What kind of government support does there need to be in order to have successful upskilling, reskilling, to actually have workers fully embrace this type of technology? So I think there are a lot of open questions. Svenja, what can businesses, government, even different societies around the world learn from one another about how this technology is being implemented and what its impact will be? If you look at a lot of industrialized countries, of course, the skills are similar that are needed to do different jobs.

11:21So there, the labor market impact will be quite similar, but the adoption rate can differ quite a bit. So we actually just did a study and looked at results for Japan versus the U.S. And we found that while in the U.S. there's a bunch of anxiety around AI, right? A lot of people are still iffy on what does this actually mean? What does it mean for me? What's going to change? In Japan, survey respondents actually were much more optimistic and much more open to figuring out, OK, how might we adopt this? How can we use it? Even though they're not actually using these tools as extensively quite yet.

11:55I think the U.S. is showing a lot more adoption on these tools so far. So there are different speeds of adoption that we're starting to notice and different cultural bends in terms of, you know, how open are you to incorporate this? Because, you know, change is hard. And that's one, like, really interesting thing that's starting to pop out in the data and we're closely watching. Svenja, thank you. Thank you so much for having me. It was a pleasure.

12:23Pete, you recently collaborated with the World Economic Forum for their report on Gen AI for job augmentation and productivity. You talked to some 20 organizations about the lessons that can be learned from the early adopters of Gen AI. What are some examples of how this tech is being used by various organizations? many organizations have lots of policies and procedures and historically i think it's quite tiresome with the way people interact with those to understand how stuff gets done some organizations have embraced gen ai based around those policies actually enabling employees to get more accurate answers much quicker than before and i think that does a couple of things that i think enhances employees enjoyment and work and it creates greater efficiencies another good example would the number of organizations in the whole recruitment space in the world there is a fierce competition for those with skills and we know there's a shortage of critical skills in the world of work generally one of the metrics that many organizations use is the time to hire how they find the right person right individual the use of gen ai in that process to be able to source more accurately to find the right tons of people in the right part of the world as fast as possible And then as they bring them through the process of recruitment, Gen.AI and its role in that process has been, I think, truly transformational in terms of shortening that time to get the right critical resources into the organisation.

13:53So what are businesses divulging to you about where they're seeing the real gains with this technology, Pete? I think, look, one of the things that is consistent with many organisations where they've been either piloting or implementing is they're seeing that it starts to do things that used to take weeks and months in a matter of minutes. And often when you delve into that and look at the kind of activity that's been undertaken, it's the administrative stuff, the repetitive things that people we know from our surveys don't enjoy doing. And it's removing some of that and enabling, I think, much crisper, much more accurate outputs.

14:27but clearly not without its risks. There's the whole issue around the ethics of it, some of the inherent biases and the fact that it doesn't always give you the right answer. So I think that message around the importance of humans in conjunction with the technology, we heard that from just about every single organization we spoke to and that doesn't go away. Are those the main risks that companies are telling you about? The hallucinations, spitting out wrong answers, like what do companies worry about? They certainly worry about those, Lizzie, but I think there's a number of other things they think about.

15:02Human beings fundamentally don't particularly enjoy change. I think those organizations that have seen the best returns on the investments and the best results are those where they've been just really clear and embracing their workforce. We always talk about people-centered change, that people tend to adopt what they've helped to create. And I think in this world of the introduction of Gen.AI, it's no different. If you are an organization trying to get buy-in from your workforce and have them embrace this technology, how do you do that? Gosh, we could do a whole podcast on that very question. People tend to respond less positively to, I think, a top-down directive in most cases.

15:45I think as human beings, we want to understand what are the benefits of this? What does it mean for me? How's my work going to change? So I think the whole focus around communications and transparency is key. Secondly, it will impact some jobs. That's the nature of technology and disruptive innovation. And what we are seeing is creating new jobs and new opportunities. And I think an adage, again, we use a lot is that you can protect people, but you can't protect jobs. Jobs will continue to evolve. They always will do. So if you have AI doing some of this sludge stuff, drafting emails, what have you, how do organizations figure out what to do with their workers if they have new productivity gains?

16:31That's a really interesting question, Lizzie, because I think in the early days, probably talking a year ago, those organizations that were adopting at the time, I think actually hadn't really thought through how are they capturing that capacity that's being freed up and actually what are they going to do with it? What we see in some of the organizations that are maybe more mature in their deployment, where they're moving from those pilots into much more enterprise-wide deployments, is they're being very deliberate around a how they're capturing that capacity that value and b how they're then redeploying that into other areas of their business which need those skills and capabilities in play and i think for me that's a really good example of in some organizations where we're seeing the skills first skills-based organization approach around that how do you agilely move your skilled people to the right place at the right time and as soon as you've got gen AI in the mix, it for me opens up that skills first approach.

17:30In this gen AI era, Sonia Goodell said, when we're looking at the kind of skills that are needed in a workforce, leadership skills, communication skills, how do we nurture those kind of skills in a workforce? And actually she's echoing what I've seen. I think leaders in organizations are always short of colleagues with those skills you listed them some people call them soft skills i don't i call them human skills how do organizations engender that well i think there's a variety of approaches i think one is having a culture which has a growth mindset which empowers the workers to develop themselves it provides opportunities for them to upskill and to reskill so we know workers want that opportunity to develop and have opportunity to learn new skills.

18:22On the opposite side, when you ask the workers the same question, but does your employee give that opportunity? Only 40 % of workers say they work in an organization that they feel they're getting full and free access to skilling and development opportunity. When we talk about a big societal shift, right? There is a risk of creating losers as well as winners. And so when you think about skills and the workforce, what policymakers be thinking about to sort of provide that support where it's needed? I think the role of policymakers in all this is crucial. I think it's very easy as well for us to talk about Gen AI as if it's mainstream.

19:07Well, we're fortunate and privileged enough that we have access. We have the software, the hardware to be able to access it. That's not the case for everybody around the world. So creating that equality of opportunity to be able to work with Gen AI to learn the skills that are required. What do you say to organizations that want to integrate AI but haven't started yet? Work out which elements of the processes within your organization are those that are probably repeatable processes, things that lends itself to the implementation of gen ai i think secondly being clear about what it is you're expecting to see as the outcome and measuring your progress throughout that i think thirdly it's being transparent and clear about the what and the why with your workers and your employee base create that narrative and engage them on that journey and i think organizations the ones we've spoken to where they started in that way they've been able to actually scale much faster because they've been learning all the way through in the smaller pilots, which they're able to then scale going forward.

20:12If you could look back in five years from now, so we're in 2030, at what AI has done for workforces around the world, what would be your top positive changes, do you think? What a question, Femi. I think the whole makeup of the workforce will be different, as historically has been. But I think we will see the emergence of and probably embedding of much more what I call digital workers, working very closely with human workers. So I think we will see the embedding of digital workers in workforces across most sectors.

20:48Femi, that was completely fascinating to listen to because I came away with kind of two overriding thoughts. Number one, workers need to be brought on board. There needs to be kind of ownership and enjoyment of these tools. And number two from Svenja, that these are tools, that they're not wholesale replacements for people, but something that we're just going to learn how to use. And also, it's fast. So get ready. Be ready. Stand by. It's happening right now. Well, that is it for today. Next time, we're going to be in Switzerland for the first of two special episodes coming live from Davos as we hear the latest developments from the annual meeting of the World Economic Forum.

21:38To get every episode as soon as it's out, tap, follow or subscribe in your podcast app. Until next time, thanks for listening. 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 is a separate legal entity.