Welcome to Street Level, my new series on Liberty Street Economics. As research director, I try to keep track of the wide range of work that the economists at the New York Fed produce. My goal for this series is to periodically offer some thematic discussion of that work, highlighting recent analysis by Research staff and adding my own observations on the issue at hand. In this inaugural post, I’ll focus on perhaps the hottest topic going: How artificial intelligence is changing the labor market and hiring behaviors.
“Serving the public means being understood by the public.”
Kartik Athreya,
Research Director
AI Anxieties
In addition to price stability, the Fed has a mandate to conduct policy in a manner consistent with “maximum employment.” So it’s important for researchers at the Fed to understand how AI is likely to affect the economy overall, and labor markets in particular–a topic that’s top of mind for almost everyone in the workforce today.
Indeed, as our team found back in October 2024 (fairly early in the still-nascent AI revolution), individuals who had been exposed to generative AI tools appeared to be left with bleaker expectations for job availability and income inequality.
Labor Market Realities
Businesses seem less sure about that bleak outlook. In a September 2025 post, our regional survey team observed that while AI adoption is rising quickly across industries, firms report very few AI-driven layoffs. Instead, AI is reshaping hiring and skill needs, though firms do anticipate more reductions in *hiring *plans going forward—especially for college-educated workers.
Rapid Adoption of AI Across Industries
Share Using AI | Service Firms | Manufacturers | | In 2024 | 25 | 16 | | In 2025 | 40 | 26 | | In next six months | 44 | 33 |
Source: Federal Reserve Bank of New York, Regional Business Surveys, August 2025.
Moreover, recruiting patterns are shifting: some firms are reducing hiring because AI automates tasks, while others are increasing hiring for AI-proficient workers.
The data, then, indicate that AI’s labor-market impact has more to do with changing skill requirements than eliminating jobs—at least so far. These general findings are echoed in a couple of recent LSE posts that analyze AI’s imprint on job postings and the implications of remote work for entry-level college graduates.
Adaptation and Diffusion
As firms incorporate AI into established processes, it’s useful to think about each job as encompassing a “bundle of tasks” rather than a single function. This is an approach taken in recent work by Luis Garicano and coauthors, who argue that while some tasks will be taken over by AI, that transition opens the door for teams to work on other areas of production and, moreover, respond to changing demands as well. This seems like a positive aspect of AI disruption; we need not assume, as some have speculated, that AI adoption will only spare jobs that focus on physical tasks and personal care.
Of course, if workers are to adapt to this new world, some retraining will be in order. With that in mind, our team asked firms about their AI-related plans a bit more directly. The results, partly presented in the chart below, indicate that firms overwhelmingly intend to retrain workers rather than fire them as they adopt AI. (Data from our Survey of Consumer Expectations show that many workers also place significant value on AI training.) This evidence reinforces the theme that AI’s short-run effects might be more evolutionary than disruptive, with firms preparing workers for new tasks rather than replacing them. The matter of slow “absorption” or “diffusion” of a new technology is also not a new one. A classic example is that of the long duration between the invention of steam power and its replacement with modern propulsion on American rivers.
Businesses Expect Growth in Share of Workers Retraining for AI Use
*Street Level *Observations: AI Risks to Watch
Street LevelObservations
I’ll close with a couple of thoughts on how we might frame AI in our economy.
**First, certain occupations may be more at risk than others. **Specialization and trade are fundamental to how we work today. Each of us typically delivers only a narrow set of services/tasks/outputs. We may be economists, or florists, or architects, or welders. If we had to do everything ourselves, as would be the case if we were marooned on a desert isle, we’d welcome AI with open arms. So the real friction is that our specialization leaves us vulnerable to a sudden collapse in the value of the only skills we may have.
This is a serious risk. Finding ways to smartly insure against such effects is a worthwhile task and one that can allow the productive potential of AI to be shared in the way that, as Robinson Crusoes, we would welcome. The public debate recognizes this in its focus on retraining, a thicker safety net, universal basic income (UBI), and so on. Each of these responses could carry unintended consequences, the importance of which requires better understanding. Given the centrality of the labor market in these proposals, it will no doubt continue to be in focus for New York Fed researchers.
**Second, it’s also crucial to account for AI-driven changes on the demand side of the economy. **AI will likely render many goods and services far cheaper than at present, making us effectively richer. More speculatively, as AI-enabled algorithms supercharge social media platforms, our spending habits could tilt toward things whose value is more relative in nature—the types of products and experiences that “influencers” devote their careers to promoting.
Although an AI-enhanced social media marketplace can drive a certain amount of growth and employment, there’s a potential problem with this business model. A world in which our consumption patterns become less about need-based absolutes (“how much food did you eat?”) than status-driven comparisons (“how much cooler was your meal than mine?”) is a world where outcomes—as economists see them—will almost certainly be wasteful. Constantly chasing those outcomes would also be a zero-sum game, since there can only be a few “best” meal experiences; if some are best, then all others are worse.
While we don’t focus much on this aspect of what the plentitude of AI may bring us, I wonder whether—given the largely smooth absorption of technology into the supply side of the economy that we have for so long experienced—this demand-side effect might actually be the most profound in the long run. Ending where we began, we can say that while AI is in the air and on our minds, the evidence on adoption suggests more muted effects on labor and hiring so far, but anxiety remains just the same.
Kartik B. Athreya is the director of research and head of the Research and Statistics Group at the Federal Reserve Bank of New York.
How to cite this post:
Kartik B. Athreya, “AI’s Impact on Labor and Hiring,” Federal Reserve Bank of New York Liberty Street Economics, August 5, 2026, https://doi.org/10.59576/lse.20260805
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The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).