AI and Jobs: What Data and History Say

Our Global Chief Economist and Head of Macro Research Seth Carpenter discusses whether the economy can adapt fast enough to turn AI into a productivity boom rather than a labor market shock.

Read more insights from Morgan Stanley.

----- Transcript -----

Seth Carpenter: Welcome to Thoughts in the Market. I'm Seth Carpenter, Morgan Stanley's Global Chief Economist and Head of Macro Research.

Today we're going to try to look past the hype and the anxiety around AI and ask what will be the effect on the labor market.

It's Friday, May 1st at 10am in New York.

Now, odds are that you've used AI to draft an email or summarize a document, maybe learn about a new topic, help plan a trip. The new technology is clearly lowering the cost of certain tasks. And I think the research shows that there are plenty and an increasing number of tasks that AI can do better than most humans. But that's not really the question.

What I hear all the time is, ‘Well, if we can get the same amount of output with less labor, then surely millions of people will lose their job.’ I think the same logic also implies that we can just get a lot more output from the economy using all the labor that we have. And the difference between those two views really is at the heart of the debate.

So far, I would say the data allow for some cautious optimism. Despite rapid advances in AI capability and evidence that adoption is spreading, the broad labor market indicators still show remarkably little disruption. Economic growth is holding in there. The unemployment rate is not rising rapidly. If anything, it's ticked down recently. Job openings are not soaring, and separations do not suggest that there's systematic weakness in AI exposed industries.

Now, productivity data are beginning to show perhaps a bit of AI's positive effects, but they don't show the mass displacement that many people fear. According to our research, industries with higher AI exposures have recorded stronger labor productivity gains, driven mainly by faster output growth rather than fewer hours worked. And that distinction for me is critical. So far, the evidence looks like workers are producing more than firms are cutting back on labor.

There's also a physical constraint. AI adoption depends – and will continue to depend – on infrastructure that is still being built. Of the more than $3 trillion in expected data center and related infrastructure CapEx from 2025 through 2028, only about a quarter of that has been deployed so far.

The future remains opaque. No two ways about it. The biggest productivity gains from my perspective are likely still ahead of us, and some job losses are likely unavoidable. Earlier, innovation waves unfolded over decades, and AI is moving much faster, compressing the adjustment period. And that does create the central risk to the labor market; that job destruction happens faster than new job creation happens.

And so, what our research has been doing is to try to look beyond the immediate effects. Yes, some jobs and tasks will likely be disrupted. But higher productivity can also mean higher incomes. Higher wealth. With higher income and higher wealth can also mean higher spending, which, in turn, drives the economy faster.

Inside corporations, new tasks and new roles will likely emerge giving some of the displaced workers somewhere else to go. And even if employment does slow down for a while – and that could put downward pressure on inflation and maybe upward pressure on the unemployment rate – I don't really think policy makers are simply going to sit back on the sidelines. Central banks can respond by trying to stimulate the economy and bring it back towards full employment.

This is something that economists call General Equilibrium. We can't look simply at one side of the equation. We have to think about the system as a whole. And I have to say, if monetary policy runs out of room, fiscal policy makers can get into the game as well. Between automatic stabilizers like unemployment benefits and directed targeted government action, there's another way in which the economy could be pushed back to full employment.

So, the bigger point is this, AI clearly has a chance to create some labor market disruption, but the economy has all sorts of other systems and levers in place that can pull us back to full employment.

And with those buffers in place, any rise in the unemployment rate from AI is probably going to end up being smaller, shorter, and easier to manage – at least for the next couple of years than maybe some of the first pass analysis that I've seen suggests.

AI's labor market impact is not predetermined. The debate will almost certainly come down to speed. How fast is AI adoption relative to the economy's ability to adapt? History suggests that productivity ultimately wins. The economy gets bigger and people stay employed. History also tells us that not everyone benefits equally. And more importantly, not every transition is smooth.

So, what does that mean? Should we be just blithely optimistic? Absolutely not. For now, the early evidence is reassuring, but the story is still being written.

Thanks for listening, and if you enjoy this show, please leave us a review wherever you listen. And share Thoughts on the Market with a friend or a colleague today.