AI Is Cutting Finance and Tech Jobs. It Is Also Adding Them

Payrolls in the US financial-activities and information sectors fell by an average of 28,000 jobs a month in 2026, a decline that Bloomberg reported on July 1 stands out against an otherwise resilient labor market. The economy added more than 113,000 jobs a month through May 2026, a number that would have been higher if banking and tech had not dragged the total down. June payroll data, set for release on July 2, was expected to show another month of solid gains.

The AI impact on tech and finance jobs is real, but it is not a single story. Three different sources, all published in the last 30 days, describe divergent outcomes inside the same companies. Challenger, Gray & Christmas tracks layoffs and reports a surge in AI-attributed cuts. Stanford’s Digital Economy Lab finds that AI has hurt hiring only where the technology replaces tasks outright. Ramp Economics Lab and Revelio Labs find that the heaviest AI spenders are growing headcount, including at the entry level. Read together, the data point to one design choice separating job losses from job gains.

Two Sectors Are Pulling the Average Down

The decline is concentrated. Bloomberg, citing government payroll data, found that financial-activities and information-sector employment fell by an average of 28,000 jobs a month in 2026, the period during which AI adoption rates have been fastest in those two industries. Other sectors have not registered the same drag.

US employers added 113,000 jobs a month on average through May, and the June report due on July 2 was expected to add to that. Strip out finance and information, and the rest of the economy was hiring at a healthier pace. Top executives at JPMorgan Chase, Citigroup, and Goldman Sachs have publicly said the technology will eliminate some jobs, per the same Bloomberg report, and Challenger’s tracker now ties close to a quarter of all announced US job cuts to AI.

The geography of the layoffs tracks the geography of AI use. Sectors with the highest adoption rates are also the sectors shedding the most workers. That correlation is what made the 28,000 figure a leading indicator for the rest of 2026, and what made the June jobs report the next reading economists were waiting on.

Why Tech and Finance Sit at the Eye of the Storm

The US Census Bureau’s Business Trends and Outlook Survey, drawing on responses from roughly 1.2 million businesses, reports that 39.7% of firms in the Information sector used AI in at least one business function as of the data collected through May 3, 2026. Finance and Insurance came in at 33.9%. The national average is 19.8%.

Adoption also scales sharply with firm size. Among firms with 250 or more employees, 37% reported using AI. Among firms with fewer than 20 employees, the rate stayed below 20% and did not move meaningfully between December 2025 and May 2026, per the Census summary. A separate Federal Reserve analysis of three surveys, the BTOS, the Real-Time Population Survey, and the Survey of Business Uncertainty, found that the largest firms have the highest adoption rates, and that the share of the labor force working at firms that have adopted AI is much higher than the share of firms that have adopted it.

Most AI users are still running the technology in a narrow slice of their operations. Among businesses that report current AI use, 57% apply AI tools in three or fewer functions. The result is a job market where the two most AI-saturated sectors are also the two cutting the most workers, while the rest of the economy holds steady.

The Federal Reserve analysis of AI adoption across US firms draws the same conclusion from a different angle: AI uptake in professional services and finance stands out among peer industries, and the strongest predictor of adoption is firm size, not sector alone.

What Challenger’s Layoff Tracker Has Recorded

Through June 2026, Challenger, Gray & Christmas has recorded 101,743 announced job cuts attributed to AI, roughly 23% of all layoffs announced this year. Since 2023, when Challenger first began tracking AI as a distinct reason, the cumulative total is 173,568 cuts.

The Technology sector leads by a wide margin. Through June 2026, tech employers announced 139,156 cuts, an increase of 83% from the 76,214 cuts announced in the same period in 2025. Tech now accounts for nearly a third of all US job cuts announced this year. The pace cooled sharply at the end of the quarter: June alone brought 45,849 cuts, down 53% from May, the lowest monthly total since December 2025.

Andy Challenger, the firm’s chief revenue officer, framed the year in two sentences in the Challenger’s June 2026 layoff report: “Tech remains the epicenter of this year’s cuts. AI is the dominant force as companies are restructuring around it, automating roles, and reallocating budgets toward new capabilities.” John Challenger, the firm’s CEO, told Bloomberg that AI is making an impact in a way that no technology has before, and that finance might be the next big sector affected.

Snapshot of Challenger’s 2026 data:

• 101,743 AI-attributed cuts year-to-date, ~23% of all cuts
• 139,156 tech-sector cuts year-to-date, up 83% from a year earlier
• 443,604 total cuts through June, down 40% from the first half of 2025
• 173,568 AI-attributed cuts since tracking began in 2023
• 45,849 June cuts, the lowest monthly total since December 2025

Where AI Is Adding Jobs Instead of Cutting Them

A joint study by Ramp Economics Lab and Revelio Labs, released on June 30 and covering 21,599 US firms from January 2021 through February 2026, finds the opposite pattern at companies that spend heavily on AI. High-intensity AI adopters, classified by per-employee AI spend in the first three months after adoption, grew headcount by 10.2% in the two years following adoption. Entry-level hiring at those firms grew by 12%. Low-intensity adopters saw no statistically significant change.

The findings, summarized in three points:

• High-intensity AI adopters grew headcount 10.2% over the two years following adoption.
• Entry-level hiring at those same firms grew 12% over the same period.
• Low-intensity AI adopters saw no statistically significant change in headcount.

The lead author, Ara Kharazian, said in the Ramp and Revelio Labs study on firm-level AI spending that the research counters the prediction that AI adoption will lead to broad job loss, and that firms investing more in AI also hire more following adoption, including in entry-level roles. The paper’s small-business finding complicates the picture further: small businesses adopt AI less often than large ones, but when they do adopt, they tend to adopt more intensively, and the marginal impact on their headcount is higher. Finance is one of the sectors where this kind of deployment shows up in the market, as Airwallex’s $11 billion AI finance push illustrates with new tools aimed at AI agents handling corporate spending.

The Automate-vs-Augment Split Is the Design Signal

The reconciliation between Challenger’s layoff data and Ramp’s hiring data runs through one distinction. Stanford’s Digital Economy Lab, in research led by Erik Brynjolfsson, found that within firms, entry-level hiring in AI-exposed occupations declined 13% relative to less-exposed jobs. The effect appeared only after the proliferation of large language models, and only in occupations where AI automates tasks rather than augments them.

Strikingly, the Stanford team found the same decline in occupations with high automative AI usage, but not in occupations with high augmentative usage. That result survived a battery of robustness checks, including excluding the tech sector, controlling for firm-level time effects, and extending the sample back to 2018. Older workers showed no statistically significant impact.

The implication for builders and operators is that augmenting rather than automating a role changes whether AI shows up as a headcount cut or a headcount add. Barclays senior US economist Pooja Sriram, quoted in the same Bloomberg report, drew the same line in plain language: some of this could genuinely be productivity replacing workers, but the narrative that keeps coming up is a cost-cutting exercise by firms that have already committed to large AI investments.

“Strikingly, we then found the same result for occupations with high automative AI usage but not ones with high augmentative usage.”

The Stanford Digital Economy Lab on AI and labor markets frames the broader consensus: the overall economy-wide impact of AI on aggregate employment is likely small right now, but the impact on specific groups, especially young workers in AI-exposed jobs, is meaningful and concentrated. Ryan Nunn at the Yale Budget Lab told Bloomberg he does not see a broad impact yet, and that AI may be affecting employment first through slower hiring and attrition rather than headline layoffs. The pattern of automation-as-cuts vs augmentation-as-additions shows up in operations too, including in Meta’s 50% AI content moderation rollout, where the company is restructuring around AI rather than simply removing headcount.

What Practitioners Should Track Now

Two indicators will tell practitioners whether the split is widening or closing. The first is the BLS monthly payroll release, with the June report due July 2. The finance and information-sector lines are the ones to watch, because they are the sectors where adoption is highest and where Challenger predicts AI-attributed cuts will spread next.

The second is the BLS projection that office and administrative support occupations, which include customer service representatives, bank tellers, and insurance claims processors, will experience some of the largest employment declines over the next decade, in part because of AI. Those occupations account for about a quarter of employment in financial activities, more than in any other major industry, per BLS data cited by Bloomberg. The California AI-Unemployment Tracker from UCLA’s California Policy Lab found no statewide surge in layoffs among highly AI-exposed workers through May 2026, but identified finance and insurance as the sector with the highest concentration of unemployment claims from AI-exposed workers in the state. Sam Altman has separately accused companies of “AI washing” their layoffs, blaming the technology for decisions driven by other factors. The June payroll release will be the first reading to test whether the divergence between heavy AI spenders and everyone else widens or narrows.

Frequently Asked Questions

Is AI causing mass layoffs in the US?

No economy-wide surge. The 2026 job losses are concentrated in the financial-activities and information sectors, where AI adoption is highest. Outside those two sectors, total US hiring has averaged 113,000 jobs a month through May.

Which sectors are losing the most jobs to AI?

Technology leads by a wide margin. Through June 2026, Challenger recorded 139,156 tech-sector cuts, up 83% from the same period in 2025, with AI cited in close to a quarter of all 2026 layoffs. Finance is the sector Challenger predicts will be next.

Why are some AI-adopting companies hiring more?

Companies that spend heavily on AI grew headcount 10.2% in the two years after adoption, including 12% growth in entry-level hiring, according to a Ramp Economics Lab and Revelio Labs study of 21,599 US firms. Low-intensity adopters saw no statistically significant change.

What is the automate vs augment distinction?

Stanford’s Digital Economy Lab found that AI hurts hiring in occupations where the technology replaces tasks, and has no measurable effect where AI augments a worker’s output. The split explains why AI shows up as a job cut in some companies and a hiring boost in others.

Will finance see more AI layoffs next?

John Challenger at Challenger, Gray & Christmas told Bloomberg that finance might be the next big sector affected, and BLS data projects steep declines in office and administrative roles common in financial activities. The California AI-Unemployment Tracker is a leading indicator for the question. The June payroll report, due July 2, is the next reading.