SVENJA GUDELL: It’s not that GenAI will take your job, right? It’s the person that knows how to use the tools that’s probably going to take your job.
PETE BROWN: You can protect people, but you can’t protect jobs. Jobs will continue to evolve, they always will be.
SVENJA: You have to be a bit of a dreamer, right? It’s going to be really amazing if you look into the future to see what could be with this technology.
LIZZIE O’LEARY: Two years ago, it all felt like the world—including our jobs and how we work—would change forever.
FEMI OKE: ChatGPT and other similar GenAI technologies crashed onto the scene, impacting the way we think about everything. From drug discovery to how we communicate.
LIZZIE: Now, 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?
LIZZIE: From PwC’s management publication, strategy and business, this is Take on Tomorrow. I’m Lizzie O’Leary, a podcaster and journalist…
FEMI: …and I’m Femi Oke, a broadcaster and journalist. This week: how is GenAI transforming the job market? Today, we’ll be talking to Svenja Gudell, chief economist at Indeed, a global job site. She’s been looking into how GenAI is transforming the workforce.
LIZZIE: 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 GenAI. Welcome back to the show, Pete.
PETE: Thank you, Lizzie, thank you, Femi. It’s lovely to see you.
LIZZIE: Pete, we have talked about GenAI 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?
PETE: As I reflect through probably every single conversation I’ve had with a client in the last year, and I, 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 GenAI 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’s 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 GenAI in their day-to-day work. That was a surprisingly low number for me. So, I think, to answer your question, huge conversation topic, varying degrees of implementation adoption.
LIZZIE: Later, we’ll hear how GenAI is completely transforming the way some businesses work. But first, what workers really need to know, about what GenAI will change in our jobs. Femi, you spoke to Svenja Gudell, who’s been looking at this in her role as chief economist at Indeed.
FEMI: Exactly—and I began by asking her about the type of changes and trends she’s noticing in her work.
SVENJA: AI is everywhere, right? We have been talking about it nonstop and are actually able to see some of these movements in our data. So we’ve developed a new generative AI tracker that looks at all the different mentions of GenAI inside job postings. It could be either for the creators of GenAI, for example, someone that has to provide a particular prompt or a user of GenAI, a marketing professional that has to be able to deal with these tools. And we saw that over the last two years an 83 X increase in those mentions. But we’re still only about two out of every thousand jobs mentioning some sort of GenAI term—so, still early days here.
FEMI: Svenja, you are in a position to see trends across different economies in different parts of the world. What are you seeing?
SVENJA: They’re looking at what types of frameworks do we need to have in place in order for GenAI 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 supports pillars do you need in order to make sure that GenAI can be used for good and have a productive impact in emerging economies versus fully developed economies? So, there are a lot of conversations happening with that. And I think [we’ve] 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? So, the basic needs are met in order to have GenAI be a tool that can be productive in a bunch of different settings.
FEMI: So, what kind of tasks can GenAI help most with?
SVENJA: 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 GenAI 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. And the results were very mixed when looking at all skills and the need for physical execution, actually being physically present. Sometimes GenAI does really well, because you’re coding, for example, you can do that remotely, right? It doesn’t require physical presence. However, if you’re taking blood, you’re a nurse, having an actual physical presence there is really important. So, there GenAI doesn’t do all that well. So, I think the really important thing is, as you figure out what is GenAI good at, and what does that mean for me, I always think, it’s not that GenAI will take your job, right? It’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.
FEMI: 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 GenAI could actually create new kinds of services and new kinds of work?
SVENJA: Absolutely. To me, GenAI 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 GenAI is going to wipe out whole jobs. It 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, and in real life, already. In farming, this technology, where you have image detection of weeds in a field that happens [in] real time. And then a laser goes in and zaps the weeds in the field as the machine drives through the field. And that 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 GenAI with the actual machine, the automation part of things, right? If we can have robots be smart thinkers and react to certain things with the help of GenAI, 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 [laughs]. We’ll see some really cool applications, and it’s still incredibly early to see a lot of that.
FEMI: GenAI is supposed to help us save time, be more productive. But what could be the challenges to this in the workplace?
SVENJA: We talk about GenAI as being an incredible timesaver 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 most properly use them before you can actually start to save a whole bunch of time. And that’s normal. That’s always the case for new tools.
FEMI: 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 GenAI?
SVENJA: First and foremost, I feel like people should always be passionate about the job that they do, right? So, I know it’s 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 GenAI is not 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? And 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 datasets. Maybe you want to learn some large language models and how to work with those in order to do a 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 US and 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 healthcare 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?
FEMI: I’m thinking about policymakers who are listening to our conversation right now and listening to the changing work landscape. What recommendations would you give to them regarding GenAI in the workplace?
SVENJA: 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 GenAI 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 they’ll have ethical considerations to be paid attention to. You 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.
FEMI: 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?
SVENJA: If you look at a lot of industrialized countries, of course, the skills are similar that are needed to do different jobs. So 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 US. And we found that while in the US 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? Well, how can we use it? Even though they’re not actually using these tools as extensively quite yet. I think the US 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 incorporating this? ’Cause you know, change is hard. And that’s one really interesting thing that’s starting to pop out in the data, and we’re closely watching.
FEMI: Svenja, thank you.
SVENJA: Thank you so much for having me. It was a pleasure.
LIZZIE: Pete, you recently collaborated with the World Economic Forum for their report on GenAI for job augmentation and productivity. You talked to some 20 organizations about the lessons that can be learned from the early adopters of GenAI. What are some examples of how this tech is being used by various organizations?
PETE: Many organizations have lots of policies and procedures, and, historically, I think it’s quite tiresome the way people interact with those who understand how stuff gets done. Some organizations have embraced GenAI based around those policies, actually enabling employees to get much faster answers, more accurate answers, much quicker than before. And I think that does a couple of things: I think it enhances employees’ enjoyment in work and it creates greater efficiencies. Another good example would be, a 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 GenAI in that process, to be able to source more accurately, to find the right talented people in the right part of the world, as fast as possible. And then, as they bring them through the process of recruitment, GenAI 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 organization.
FEMI: So what are businesses divulging to you about where they’re seeing the real gains with this technology, Pete?
PETE: I think, look, one of the things that is consistent with many organizations where they’ve been either piloting or implementing is they’re seeing that it’s starting 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 that, dare I say, mundane stuff, 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, but clearly not without its risks. You know, 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.
LIZZIE: Are those the main risks that companies are telling you about? The hallucinations? Spitting out wrong answers? Like, what do companies worry about?
PETE: They certainly worry about those, Lizzie, but I think there’s a number of other things they think about. Human 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 GenAI, it’s no different.
LIZZIE: If you are an organization trying to get buy-in from your workforce, and have them embrace this technology, how do you do that?
PETE: Gosh, we could do a whole podcast…
LIZZIE: [Laughs]
…on that very question. People tend to respond less positively to, I think, a top-down directive, in most cases. I 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. What we are seeing, though, it’s creating new jobs and new opportunities. And, I think, an adage 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.
LIZZIE: 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?
PETE: That’s a really interesting question, Lizzie, because I think in the early days, we’re 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’re seeing 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’ve been 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 GenAI in the mix, it, for me, opens up that skills-first approach.
FEMI: In this GenAI era, Svenja 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?
PETE: 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. On the opposite side, when you ask the workers the same question, but, does your employer give you 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.
LIZZIE: When we talk about a big societal shift, there is a risk of creating losers as well as winners. And so, when you think about skills and the workforce, what should policymakers be thinking about to provide that support where it’s needed?
PETE: I think the role of policymakers in all this is crucial. I think it’s very easy as well for us to talk about GenAI as if it’s mainstream. Well, 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 GenAI to learn the skills that are required.
LIZZIE: What do you say to organizations that want to integrate AI but haven’t started yet?
PETE: Work out which elements of the processes within your organization are those that are pretty repeatable processes. Things that lends itself to the implementation of GenAI. 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.
FEMI: If you could look back in five years from now, so we’re in 2030, you look back at what AI has done for workforces around the world, what would be your top three positive changes, do you think?
PETE: What a question Femi! I think, one, I think the whole makeup of the workforce will be different, as historically it 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 we—I think we will see the embedding of digital workers in workforces across most sectors.
LIZZIE: Femi, 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 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.
FEMI: And also, it’s fast, so get ready. Be ready. Stand by. It’s happening right now.
LIZZIE: 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!
FEMI: To get every episode as soon as it’s out, tap follow or subscribe in your podcast app.
LIZZIE: Until next time, thanks for listening.
FEMI: 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.
