Artificial intelligence use among regional businesses has surged over the past year, yet fears of widespread job losses haven't materialized, according to a September 1, 2026 report from the Federal Reserve Bank of New York. Drawing on three years of regional business surveys in New York and Northern New Jersey, the research shows that firms are retraining workers to use AI rather than cutting staff. While adoption has become the norm, investments remain modest and usage is concentrated among a small fraction of employees within each company.
AI adoption jumped sharply in 2026, with 61 percent of service firms now using the technology—up from 40 percent in 2025 and just 25 percent in 2024. Among manufacturers, 51 percent reported using AI this year, roughly double last year's 26 percent and triple the 16 percent from 2024. Knowledge-intensive sectors like information, business services, and finance showed the highest usage rates. Despite this widespread adoption, most firms haven't invested heavily: three-quarters of service firms and more than 90 percent of manufacturers characterize their AI investments as minimal to modest, ranging from free tools to a small share of overall spending. Only 15 percent of service firms—and no manufacturers—have committed significant resources, with just 5 percent of service firms treating AI as a major strategic investment. Among adopters, the median share of workers actually using AI was only 17 percent at service firms and 7 percent at manufacturers. Cost wasn't the main barrier for non-adopters: about half said their work doesn't suit AI, roughly a quarter felt AI isn't good enough yet to provide benefits, and more than a third cited concerns about data privacy, security, accuracy, or lack of technical skills.
Job cuts tied to AI have been uncommon. The report notes that only 4 percent of service firms laid off workers due to AI over the past six months, compared to 1 percent in 2025, while no manufacturers reported layoffs this year or last. About 15 percent of service firms said they hired fewer workers than they would have without AI, similar to last year's 12 percent, and a handful of manufacturers also reduced hiring. However, some firms moved in the opposite direction: roughly 13 percent of service firms hired additional workers to help leverage AI, matching last year's results. Retraining has remained the primary workforce adjustment, with just over a third of service firms and more than 20 percent of manufacturers reporting they've retrained employees in response to AI, spanning workers across all education levels though slightly more among college graduates.
The report explains that firms are focused on helping employees do their current jobs better rather than preparing them for entirely new roles. Training covers basic AI literacy, tool-specific instruction like chatbots and generative AI assistants, automating repetitive tasks, prompt engineering, and job-specific AI applications—for example, using AI for marketing, social media content, or accounts payable with human oversight. Many companies emphasized teaching responsible AI use, including verifying outputs, understanding biases, following data security protocols, and avoiding over-reliance. Delivery methods ranged from formal workshops and external consultants to informal peer learning and hands-on experimentation. The authors write that these findings align with broader research showing limited labor market effects from AI adoption so far, though one recent study suggests entry-level workers may face barriers as AI can substitute for routine tasks often performed by newer employees.
The report concludes that AI is reshaping work itself rather than eliminating vast numbers of jobs, with firms investing in existing workforces instead of replacing large groups of people. As adoption becomes the norm, retraining has only grown in importance, and evidence so far confirms that AI has been more likely to augment workers than replace them. However, the authors caution that AI technology and its applications are still evolving rapidly, and these patterns could shift as adoption matures. For now, the message is clear: businesses are transforming how work gets done, not who does it.