Operations and back-office roles are the first job category to show measurable headcount decline as companies deploy artificial intelligence, according to new workforce data. JPMorganChase reduced its operations staff by 4% and support staff by 2% while client-facing roles grew, and Standard Chartered announced plans to cut 7,800 back-office jobs by 2030 as it scales automation.
A recent analysis of AI spending data from 21,559 U.S. companies, conducted by Ramp and Revelio Labs, found that operations was the only job category that failed to see headcount growth among firms making heavy AI investments. The shift toward AI Agents & Automation in routine, repeatable tasks is driving the displacement, with work like reconciling failed equity trades, handling new account paperwork, and processing IPO filings among the prime targets.
Operations and support
The back office - where employees execute, clear and settle transactions, process loans and manage accounts - is the department most vulnerable to hiring freezes and cutbacks. As banks deploy more AI for Operations, repetitive manual work that once required teams of people is being handled by automated systems. Carissa Robb, managing partner at SolomonEdwards, said positions that are "more task-oriented, where we are pushing a widget, are benefiting at a faster pace from automation."
Wells Fargo cut 4,199 jobs in the first quarter, marking 23 consecutive quarters of headcount reductions. Citi eliminated 2,000 staff members and Bank of America cut 1,073 roles during the same period. All three banks have cited increasing use of AI among their employees. Robb also warned that the traditional career path from operations into client-facing roles is disappearing. "How much of that workforce was created and became successful in revenue-generating or customer-interacting positions because they had the opportunity to move through the operational and back-office support model?" she said in an American Banker podcast. "That's where I think we need to pay attention."
Jeff McMillan, former head of firm-wide AI at Morgan Stanley and now principal of McMillanAI, said mid-career workers face the greatest risk. "I worry about the people who are mid-career, whose job is largely going to be replaced by AI," he said. "What is unclear to me is: What is the path for that person to reinvent him or herself for the next 20 years in their career? As individuals, we can't wait for somebody to figure that out for us, we have to ourselves start to engage in this conversation."
Junior analysts and entry-level positions
Junior analysts who collect financial data, prepare reports, and assist with risk assessments are also seeing demand shrink. Debasish Patnaik, senior partner at McKinsey's AI consulting arm QuantumBlack, told Fortune that banks are cutting junior analyst classes by as much as two-thirds while sourcing roughly 62% of their AI talent from those same cohorts. Goldman Sachs CEO David Solomon said at the Cisco AI Summit in January that AI can now create 95% of an S-1 filing - the form a company files with the SEC when going public - in just a few minutes, work typically done by junior analysts and lawyers.
Morgan Stanley Research Economist Diego Anzoategui found that unemployment among workers aged 22 to 27 has increased the most since 2023 in occupations highly exposed to AI, including analysts, accountants, and judicial clerks. These professionals tend to have higher levels of education, earn higher income on average, and perform tasks that are primarily computer-based.
Outsourcing and offshoring
Experts expect AI to drive down banks' use of outsourcing and offshore workers. McMillan said the characteristics that make work suitable for offshoring - well-defined tasks, clear performance metrics, and easy monitoring - also make it a strong fit for AI automation. "No bank wants to fire people, they just don't," he said. "There are so many disincentives to fire people because it just creates noise and depression. I advise people to go after outsourcing work, because it's so much easier to automate that."
Why this matters for operations professionals
The data shows that routine, repeatable tasks are the first to go - not entire jobs. Operations professionals who handle exceptions, complex problem-solving, and work that requires human judgment remain harder to automate. The disappearing career path from operations into client-facing roles means mid-career workers cannot count on traditional promotion tracks. Building skills in AI oversight, model validation, and process design offers a way to stay relevant as the tools that displace routine work also create demand for people who can manage them.
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