AI is changing the job market, but not in the way the panic suggests. The New York Fed now says the recent hiring slowdown is still being driven more by rates, overhiring and a weak labor backdrop than by automation.
The timing matters. Just as executives, founders and investors have started treating AI as the explanation for every layoff memo, a new Liberty Street Economics post from the New York Fed argues that the broad slowdown in hiring is still better explained by old-fashioned macro pressure than by machines taking white-collar jobs overnight.
That distinction is not academic. If the slowdown is mostly about interest rates and the hangover from post-pandemic hiring, then startups should not assume that every soft hiring trend is a sign of immediate AI replacement. The right response is different, because the problem is different.
The New York Fed's latest analysis, published on May 13, looks at job postings and early labor-market effects of AI. Reuters reported that the study challenges the increasingly common story that AI is the primary reason companies are pulling back on hiring, especially in white-collar roles.
That does not mean AI has no effect. The Fed's earlier survey work found that firms are using AI more, but most are still retraining workers rather than cutting them. In that September 2025 survey, the New York Fed said very few firms reported AI-related layoffs, even as adoption rose. The newer May analysis extends that line of thinking by arguing that the weakness in hiring is still too broad to be blamed mainly on AI.
Reuters' coverage also points to a key detail that matters for anyone reading too much into tech layoffs. Hiring weakness and job cuts have been concentrated in the tech sector, where companies spent aggressively during and after the pandemic and are now facing a tougher funding environment. That is a very different story from AI suddenly hollowing out the labor market across the economy.
Other recent reporting reinforces the same point. Schroders said in March that the global hiring slowdown is more convincingly explained by non-AI factors, including higher rates, trade uncertainty and overhiring. In other words, the New York Fed is not alone in pushing back on the clean AI narrative.
Why startups should care
For founders, the practical lesson is simple. Do not build your hiring plan around a fear that AI has already made headcount obsolete, because that is not what the current data show. The more immediate constraint is capital. When rates are high and money is expensive, every hiring decision carries a heavier cost, and that pressure can freeze growth long before AI does.
This also changes how teams should talk to investors. A pitch deck that treats AI as the main reason for a cautious hiring posture will look thin if the real issue is macroeconomics. It is cleaner, and more credible, to say that hiring is being paced to match demand, burn and financing conditions while AI is used to raise productivity in specific workflows.
That framing matters because investors can spot the difference between structural efficiency and reactive defensiveness. A company that understands where AI helps and where it does not will usually sound more grounded than one that uses automation as a catch-all excuse for slower growth. In 2026, credibility is an asset.
The same applies to recruiting. If you are trying to hire senior operators, engineers or product people, candidates will notice whether your story is built on real operating discipline or on vague claims about replacing work with software. The strongest startups will still hire selectively, but they will do it with a sharper view of unit economics and a better understanding of which tasks actually benefit from AI.
The real risk is capital cost
The bigger risk for early-stage companies is not that AI suddenly removes the need for people. It is that a high-rate environment raises the bar for every dollar spent before revenue catches up. That hits startups faster than automation does, because funding cycles, payroll and runway are all exposed at once.
Tech-sector layoffs are still important, but they should not be misread as proof that AI has already taken over labor demand. Reuters cited recent examples of layoffs linked to restructuring and investment shifts rather than direct replacement, and that fits the broader picture: companies are still adjusting to the post-pandemic reset, tighter capital and slower growth.
The result is a labor market that looks cautious, not transformed. AI is part of the story, and it will matter more over time, but the New York Fed's message is that the present slowdown is still mostly a macro story. For founders, that means the right response is not panic about automation. It is discipline about hiring, a cleaner pitch to investors and a more realistic view of where the real pressure is coming from.
Also read: Nous Research's new training method could change the economics of LLMs • Microsoft's AI chief says white-collar work may be automated fast • Musk says he will not sell SpaceX shares as IPO moves closer
