AI and jobs: 28,000 cuts a month in the US

According to Bloomberg data published on July 1, 2026, the ongoing adoption of AI in the US has led to the loss of about 28,000 jobs a month in the tech and finance sectors.

What does the 28,000 figure mean?

Twenty-eight thousand cuts a month is the combined figure for two sectors that, only a few years ago, were seen as the main drivers of employment growth for highly skilled workers: technology companies and financial institutions. These were the industries that first deployed language models and agentic automation systems at scale in everyday workflows.

Key facts from the report:

• 28,000 is the combined monthly job loss in the US tech and finance sectors
• Bloomberg published the data on July 1, 2026
• For the first time, AI appears in official labor statistics as a measurable factor in employment reductions
• The long-term outlook for mass layoffs remains a subject of economic debate

Bloomberg describes the trend with characteristic caution: AI is "beginning to leave a mark" on the data. The wording matters. The numbers have moved beyond corporate press releases about "optimization" and are now showing up in aggregate employment statistics across the whole economy.

Why were tech and finance hit first?

It is no accident that these two sectors are at the front. Both work with huge volumes of structured data, which is exactly what language models handle best today. Both also began large-scale investment in generative AI and in automation of operational and analytical processes back in 2023–2024.

In finance, AI is steadily displacing analysts: transaction processing, credit risk scoring, regulatory monitoring and report preparation are being automated. In tech companies, the roles at risk involve routine coding, software testing, basic technical support and first-line request handling.

In 2025–2026, the big tech companies were increasing their AI infrastructure spending while also announcing waves of layoffs, citing higher productivity per employee. Now the statistics show these two developments as a single trend.

Will AI create more jobs than it destroys?

The long-term answer is not settled. Some economists argue that every technological wave destroyed some occupations and created new ones. The steam engine, Ford's assembly line, the personal computer, broadband internet: in each case, total employment eventually recovered and surpassed earlier levels.

Skeptics point to a key difference in the current transition: for the first time, automation can take on not only physical labor but also cognitive tasks, such as data analysis, writing, legal expertise and operational decision-making. The pace of adoption is not comparable to earlier transitions and leaves the labor market without the usual time buffer for adaptation and retraining.

The very fact that sustained figures have appeared in official statistics marks a point of no return: AI's effect on employment has stopped being a theoretical model and become a measurable observation that demands a policy response.

What this means

28,000 jobs a month is not a catastrophe for a US labor market of 160 million people, but it is a sustained trend in two of the country's best-paid industries. If the pace does not slow, the debate will inevitably move from academic journals to legislatures, toward regulation of automation, taxes on AI systems and government retraining programs for workers in displaced professions.

How is AI affecting jobs in the US?

According to Bloomberg, AI adoption in the tech and finance sectors has led to the loss of 28,000 jobs a month. It is the first time AI's effect has begun to show up consistently in national labor statistics.