The rapid spread of artificial intelligence across regional businesses has not triggered the wave of job losses that many feared. According to the Federal Reserve Bank of New York's August business surveys, more than 60 percent of service firms and about half of manufacturers in the New York and Northern New Jersey region now use AI, up sharply from 40 percent and 26 percent respectively in 2025. Yet despite this acceleration, layoffs tied to AI remain uncommon, and the dominant workforce response is retraining rather than replacement. The findings matter because they offer an evidence-based counterpoint to widespread anxiety about AI-driven unemployment, suggesting that adoption is currently transforming how work is done rather than eliminating jobs.
The mechanics of adoption reveal a pattern of broad but shallow integration. Among service firms, 61 percent reported using AI this year, up from 40 percent last year and 25 percent in 2024. Manufacturers reported 51 percent adoption, roughly double the 26 percent from last year and triple the 16 percent in 2024. However, most firms characterize their AI investments as minimal to modest: three-quarters of service firms and more than 90 percent of manufacturers fall into this category, ranging from use of free AI tools to allocating a small share of overall spending. Only 15 percent of service firms—and no manufacturers—reported committing significant resources to AI adoption. Among AI adopters, the median share of workers using the technology was just 17 percent for service firms and 7 percent for manufacturers.
The workforce data underscores the limited labor market disruption so far. Only 4 percent of service firms reported laying off workers in response to AI over the past six months, compared to just 1 percent in last year's survey, while no manufacturers reported layoffs this year or last year. About 15 percent of service firms said they had hired fewer workers than they would have without AI, similar to the 12 percent reported last year. Offsetting those reductions, about 13 percent of service firms said they had hired more workers to help them leverage AI. Retraining remains the most common adjustment: just over a third of service firms and more than 20 percent of manufacturing firms that use AI report retraining workers, with retraining occurring across the educational spectrum but somewhat more among workers with college degrees.
The sectoral implications point to a nuanced picture. Knowledge-intensive service sectors—information, business services, and finance—show the highest AI usage rates, consistent with the technology's current strengths in text processing, analysis, and customer interaction. Manufacturers, while adopting at a faster relative pace, still lag in absolute terms and report no AI-related layoffs or hiring increases this year. The concentration of usage among a small share of workers within firms suggests that AI is currently augmenting specific tasks rather than substituting for entire job categories. For labor markets, the near-term effect appears to be a modest reshaping of hiring flows—some firms hiring fewer workers, others hiring more to support AI—rather than a sharp contraction in employment levels.
The evidence has clear limitations. The findings come from a single regional survey covering the New York and Northern New Jersey area, and the New York Fed notes that the adoption shares are toward the high end of existing studies of AI use in the workplace, meaning national patterns may differ. The survey captures self-reported behavior over a six-month window, which may miss longer-term restructuring. Non-adopters cite reasons unrelated to cost: about half say their type of work does not lend itself to AI, roughly a quarter say AI is not yet good enough to provide benefits, and more than a third express concerns about data privacy, security, or accuracy. What to watch is whether investment depth catches up with adoption breadth—if the current minimal-to-modest spending shifts toward significant strategic investment, the labor market effects could intensify beyond today's retraining-focused adjustment.