European banks see AI cutting jobs mainly via attrition

European banks are projecting modest net workforce reductions from artificial intelligence, with some executives and analysts questioning whether the forecasts match the scale of public claims about disruption.

A Financial Times report cited Morgan Stanley's analysis of 35 major lenders that expect a 10% workforce reduction, described as about 200,000 jobs by 2030. In a separate survey, Bloomberg Intelligence asked 93 global bank Chief Information Officers about expected workforce change. The survey found a projected average net workforce reduction of 3% over three to five years, with reductions concentrated in back office and middle office roles.

The projections come as banks expand the use of AI tools in customer service, compliance and operational functions. They also arrive amid investor attention on AI spending, productivity and cost targets across large employers.

Interpreting forecasts

Researcher Richard Foster-Fletcher said the headline numbers on job cuts imply disruption, but the implied annual reduction looks closer to normal attrition in large institutions. He wrote that a 10% reduction over five years works out at about 2% per year. He also argued that internal efficiency targets often fall during delivery, given regulatory constraints, legacy technology and institutional resistance.

"Two hundred thousand sounds like a reckoning. But ten percent over five years? That just sounds like standard attrition," said Richard Foster-Fletcher, Researcher and Writer, What Still Matters.

Foster-Fletcher said banks have long managed reductions in selected functions through retirement and resignation. He said some forecasts should be read as incremental automation. He also said that cuts could land below the most optimistic projections once banks start implementation.

Where AI sits

Banks are deploying AI in areas such as customer queries, document summaries, coding assistance and fraud flagging. These deployments sit mainly in operations and support functions. They do not represent changes to bank balance sheets, risk models, or the core economics of lending and deposit-taking.

The Evident AI Tracker has described banking AI adoption as clustering around operational efficiency. Foster-Fletcher also pointed to a McKinsey assessment of progress on banking AI use cases.

"Most banks are still experimenting with proofs of concept, such as document summaries or basic emails. Few have identified a path to value or seen substantial returns," said Foster-Fletcher.

Fair Work case

One of the most prominent recent disputes over AI-linked staffing has involved the Commonwealth Bank of Australia and the Finance Sector Union. Foster-Fletcher described the episode as a practical test of how banks translate automation claims into workforce decisions.

He wrote that the bank deployed AI voice bots and said they reduced call volumes by 2,000 per week. He said the bank then declared 45 customer service roles redundant and terminated staff. The union disputed the figures and took the bank to the Fair Work Commission.

Foster-Fletcher wrote that call volumes increased rather than decreased. He said the bank drafted team leaders onto phones and offered overtime to remaining staff. He wrote that the bank later reversed the terminations and issued a public statement about its initial assessment that did not adequately consider all relevant business considerations, and this error meant the roles were not redundant.

Foster-Fletcher said the case turned on productivity metrics used to justify the workforce decision. He argued that similar calculations often remain internal and do not face external scrutiny.

Narratives and pressure

AI claims on jobs have also surfaced beyond banking, with large employers tying workforce plans to technology shifts while reporting limited net headcount impact. Foster-Fletcher cited comments by senior executives at Amazon and Walmart alongside the scale of corporate job reductions and headcount plans.

He wrote that public messaging often frames AI as transformative. He said internal programmes often look like incremental automation because that is what organisations can implement in complex operating environments.

Foster-Fletcher said banking workforce reductions have remained concentrated in back office, middle office and operations. He said those functions have faced periodic cost pressure and consolidation for decades. He argued that a different pattern of cuts would be likely if AI were driving a more fundamental change in how banks generate revenue and take risk.

"The hype is optional. The numbers are not," said Foster-Fletcher.