US Economy: What Generative AI Means for the Labor Market

Generative AI could transform the nature of work and boost productivity, but companies and governments will need to invest in reskilling.

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Stephen Byrd: Welcome to Thoughts in the Market. I'm Stephen Byrd, Morgan Stanley's Global Head of Sustainability Research.

Seth Carpenter: And I'm Seth Carpenter, the Global Chief Economist.

Stephen Byrd: And on the special episode of the podcast, we'll discuss how generative A.I. could reshape the US economy and the labor market. It's Thursday, November 2nd at 10 a.m. in New York.

Stephen Byrd: If we think back to the early 90's, few could have predicted just how revolutionary the Internet would become. Creating entirely new professions and industries with a wide ranging impact on labor and global economies. And yet with generative A.I. here we are again on the cusp of a revolution. So, Seth, as our global chief economist, you've been assessing the overarching macro implications of the Gen A.I. phenomenon. And while it's still early days, I know you've been thinking about the range of impacts Gen A.I could have on the global economy. I wondered if you could walk us through the broad parameters of your thinking around macro impacts and maybe starting with the productivity and the labor market side of things?

Seth Carpenter: Absolutely, Stephen. And I agree with you, the possibilities here are immense. The hardest part of all of this is trying to gauge just how big the effects might be, when they might happen and how soon anyone is going to be able to pick up on the true changes and things. But let's talk a little bit about those two components, productivity and the labor market. They are very closely connected to each other. So one of the key things about generative A.I is it could make lots of types of processes, lots of types of jobs, things that are very knowledge base intensive. You could do the same amount of work with fewer people or, and I think this is an important thing to keep in mind, you could do lots more work with the same number of people. And I think that distinction is really critical, lots of people and I'm sure you've heard this before, lots of people have a fear that generative A.I is going to come in and destroy lots of jobs and so we'll just have lots of people who are out of work. And I guess I'm at the margin a lot more optimistic than that. I really do think what we're going to end up seeing is more output with the same amount of workers, and indeed, as you alluded to before, more types of jobs than we've seen before. That doesn't exactly answer your question so let's jump into those broad parameters. If productivity goes up, what that means is we should see faster growth in the economy than we're used to seeing and I think that means things like GDP should be growing faster and that should have implications for equities. In addition, because more can get done with the same inputs, we should see some of the inflationary pressures that we're seeing now dissipate even more quickly. And what does that mean? Well, that means that at least in the short run, the central bank, the Fed in the U.S., can allow the economy to run a little bit hotter than you would have thought otherwise, because the inflationary pressures aren't there after all. Those are the two for me, the key things one, faster growth in the economy with the same amount of inputs and some lower inflationary pressures, which makes the central bank's job a little bit easier.

Stephen Byrd: And Seth, as you think about specific sectors and regions of the global economy that might be most impacted by the adoption of Gen A.I., does anything stand out to you?

Seth Carpenter: I mean, I really do think if we're focusing just on generative A.I, it really comes down, I think a lot to what can generative A.I do better. It's a lot of these large language models, a lot of that sort of knowledge based side of things. So the services sector of the economy seems more ripe for turnover than, say, the plain old fashion manufacturing sector. Now, I don't want to push that too far because there are clearly going to be lots of ways that people in all sectors will learn how to apply these technology. But I think the first place we see adoption is in some of the knowledge based sectors. So some of the prime candidates people like to point to are things like the legal profession where review of documents can be done much more quickly and efficiently with Gen A.I. In our industry, Stephen in the financial services industry, I have spoken with clients who are working to find ways to consume lots more information on lots of different types of firms so that as they're assessing equity market investments, they have better information, faster information and can invest in a broader set of firms than they had before. I really look to the knowledge based sectors of the economy as the first target. You know, so that Stephen is mostly how I'm thinking about it, but one of the things I love about these conversations with you is that I get to start asking questions and so here it is right back at you. I said that I thought generative A.I is not going to leave large swaths of the population unemployed, but I've heard you say that generative A.I is really going to set the stage for an unprecedented demand in reskilling workers. What kind of private sector support from corporations and what sort of public sector support from governments do you expect to see?

Stephen Byrd: Yeah Seth, I mean, that point about reskilling, I think, is one of the most important elements of the work that we've been doing together. This could be the biggest reskilling initiative that we'll ever see, given how broad generative A.I really is and how many different professions generative A.I could impact. Now, when we think about the job impacts, we do see potential benefits from private public partnerships. They would be really focused on reskilling and upskilling workers and respond to the changes to the very nature of work that's going to be driven by Gen A.I. And an example of some real promising efforts in that regard was the White House industry joint efforts in this regard to think about ways to reskill the workforce. That said, there really are multiple unknowns with respect to the pace and the depth of the employment impacts from A.I. So it's very challenging to really scope out the magnitude and cadence a nd that makes joint planning for reskilling and upskilling highly challenging.

Seth Carpenter: I hear what you're saying, Stephen, and it is always hard looking into the future to try to suss out what's going on but when we think about the future of work, you talked about the possibility that Gen A.I could change the nature of work. Speculate here a little bit for me. What do you think? What could be those changes in terms of the actual nature of work?

Stephen Byrd: Yeah, you know, that's what's really fascinating about Gen A.I and also potentially in terms of the nature of work and the need to be flexible. You know, I think job gains and losses will heavily depend on whether skills can be really transferred, whether new skills can be picked up. For those with skills that are easy to transfer to other tasks in occupations, you know, disruptions could be short lived. To this point the tech sector recently experienced heavy layoffs, but employees were quickly absorbed by the rest of the economy because of overall tight labor market, something you've written a lot about Seth. And in fact, the number of tech layoffs was around 170,000 in the first quarter of 2023. That's a 17 fold increase over the previous year. While most of these folks did find a new job within three months of being laid off, so we do see this potential for movements, reskilling, etc., to be significant. But it certainly depends a lot on the skill set and how transferable that skill set really is.

Seth Carpenter: How do you start to hire people at the beginning of this sort of revolution? And so when you think about those changes in the labor market, do you think there are going to be changes in the way people hire folks? Once Gen A.I becomes more widespread. Do you think workers end up getting hired based on the skill set that they can demonstrate on some sort of credentials? Are we going to see somehow in either diplomas or other sorts of certificates, things that are labeled A.I?

Stephen Byrd: You know, I think there is going to be a big shift away from credentials and more heavily towards skills, specific skill sets. Especially skills that involve creativity and also skills involving just complex human interactions, human negotiations as well. And it's going to be critical to prioritize skills over credentials going forward as, especially as we think about reskilling and retraining a number of workers, that's going to be such a broad effort. I think the future work will require hiring managers to prioritize these skills, especially these soft skills that I think are going to be more difficult for A.I models to replace. We highlight a number of skills that really will be more challenging to automate versus those that are less challenging. And I think that essentially is a guidepost to think about where reskilling should really be focused.

Seth Carpenter: Well, Stephen, I have to say I'd be able to talk with you about these sorts of things all day long, but I think we've run out of time. So let me just say, thank you for taking some time to talk to me today.

Stephen Byrd: It was great speaking with you, Seth.

Seth Carpenter: And thanks to the listeners for listening. If you enjoyed Thoughts on the Market, please leave us a review on Apple Podcasts and share the podcast with a friend or colleague today.