The largest U.S. banks shed jobs at the fastest clip in nearly a decade through 2024 and 2025, driven by aggressive investment in artificial intelligence and automation tools designed to cut costs. Wells Fargo, JPMorgan Chase, and their peers filed annual disclosures showing workforce numbers that reflect a sustained contraction, even as revenues held steady or grew. The trend is accelerating, with at least one major bank signaling that further reductions are planned for 2026.
Wells Fargo’s Shrinking Workforce
Wells Fargo reported approximately 217,000 employees as of December 31, 2024, with roughly 77% of that workforce based in the United States. That figure represents a sharp decline from the bank’s peak staffing levels earlier in the decade, when the San Francisco-based lender employed well over 250,000 people. The reduction has not been a single dramatic layoff event but rather a years-long process of attrition, restructuring, and selective hiring freezes that has quietly reshaped the company’s cost structure. What makes the current round of cuts different from past cycles is the explicit connection to technology. Wells Fargo CEO Charles Scharf said in December 2025 that AI was “extremely significant, both in terms of the efficiencies it can drive,” and that the technology “could change how work is carried out” across the bank. Scharf indicated that Wells Fargo expects more job cuts going into 2026 and plans to roll out AI tools gradually over the course of that year. The language is careful, but the direction is unmistakable: automation is replacing human labor in back-office functions, compliance review, and routine customer interactions. Executives have framed the shift as necessary to remain competitive against digital-first rivals and nonbank payment firms. Internally, managers have been tasked with identifying processes that can be standardized and handed off to software, from document classification in mortgage operations to automated quality checks in consumer lending. Employees in affected units describe a workplace where new tools arrive first as “assistants” and then, over time, become the default way the work gets done, reducing the need for additional staff.
JPMorgan Chase and the Scale of Industry Cuts
Wells Fargo is not alone. JPMorgan Chase, the largest U.S. bank by assets, disclosed 318,512 employees globally as of December 31, 2025. While JPMorgan’s headcount remains the largest among U.S. banks, the figure reflects ongoing adjustments tied to technology-driven restructuring across its consumer banking, operations, and technology divisions. The bank has invested heavily in AI and machine learning platforms over recent years, and those investments are now showing up in staffing decisions. JPMorgan has emphasized that technology spending is aimed at both growth and efficiency. AI models are increasingly embedded in fraud detection, credit decisioning, and customer service chat interfaces. In practice, that allows the bank to process more transactions and serve more customers with fewer incremental hires. Roles that once required teams of analysts can now be supported by a smaller group overseeing automated systems, creating a slow but persistent drag on overall headcount. Citigroup’s 2024 annual filing with the SEC details workforce changes connected to what the bank has described as a broad simplification effort, trimming management layers and consolidating operations. Citigroup’s disclosure outlines strategy language around efficiency programs and technology transformation that tracks closely with the patterns at Wells Fargo and JPMorgan. Similarly, Morgan Stanley’s report includes human capital discussion reflecting expense controls, though the investment bank’s workforce dynamics differ given its heavier reliance on advisory and wealth management staff. Across these firms, the headline numbers obscure significant churn beneath the surface. Banks continue to hire software engineers, data scientists, and cybersecurity specialists, even as they reduce or hold flat the number of operations staff and branch employees. The result is a gradual rebalancing of the workforce toward technical and client-facing roles and away from traditional middle-office positions.
AI Adoption Is Accelerating Across Workplaces
The banking sector’s push fits within a broader pattern of AI adoption across American workplaces. A Federal Reserve research note compiling survey evidence on AI uptake found that workplaces are adopting the technology at rising rates, with methodology-forward analysis showing that adoption is no longer confined to tech firms or early experimenters. Financial services, with its heavy reliance on data processing, document review, and pattern recognition, sits squarely in the path of these tools. Banks have historically been among the largest employers of middle-skill office workers in the United States. Loan processors, compliance analysts, call center representatives, and operations staff have long formed the backbone of megabank workforces. AI tools are now capable of handling significant portions of these tasks, from flagging suspicious transactions to answering routine customer inquiries through chatbots. The result is not necessarily mass layoffs announced in a single quarter but a steady erosion of positions that are simply not refilled when employees leave. Economists and labor experts note that this pattern (technology enabling firms to do more with the same or slightly fewer workers) can be difficult to measure in real time. Headcount may decline only modestly from year to year, even as the nature of the work changes substantially. For employees, the impact shows up as slower hiring, reduced opportunities for advancement in certain job families, and a greater premium on technical skills.
A Decade of Headcount Erosion at Bank of America
Bank of America’s trajectory illustrates how long this trend has been building. The bank’s more recent SEC filings trace a steady decline in total employees, a pattern that predates the current AI boom but has accelerated alongside it. Earlier filings from the mid-1990s and late 1990s show a very different institution, one that was still growing its workforce through acquisitions and branch expansion. The contrast with recent years is stark. During the 1990s, Bank of America used mergers to rapidly expand its geographic footprint, a strategy reflected in contemporaneous documents such as a regulatory filing describing consolidation moves. More branches and new markets meant more tellers, loan officers, and support staff. By the 2010s and early 2020s, however, the bank’s strategy had shifted toward digital channels, mobile banking, and centralized processing hubs. That evolution, combined with post-crisis regulatory pressures to control expenses, contributed to a long-running reduction in headcount. Bank of America filed its 2024 Annual Report on Form 10-K in late February 2025, continuing the documentation of this long arc. While granular headcount breakdowns for the most recent period are drawn from individual filings rather than a single industry-wide dataset, the direction across all major U.S. banks is consistent: fewer employees are needed to support a given level of assets and revenue than a decade ago. The gap between the labor-intensive banking model of the 1990s and today’s leaner, more automated operations continues to widen.
What the Cuts Mean for Workers and Communities
The shift toward AI-enabled efficiency is reshaping not only bank balance sheets but also local labor markets. Many of the roles most exposed to automation are concentrated in specific regions, including operations centers in the Carolinas and Midwest, call centers in smaller cities, and back-office hubs near major metros. As banks consolidate functions and close or shrink facilities, some communities face a slow bleed of stable, mid-wage jobs. For remaining employees, the message from management is clear: adapt to the new tools or risk being left behind. Training programs increasingly focus on data literacy, basic coding concepts, and the ability to work alongside algorithmic systems. In some cases, banks are offering internal mobility programs to help operations staff move into more technical or analytical roles. But not all workers can or want to make that transition, and the number of such positions is limited relative to the scale of traditional back-office workforces. Labor advocates warn that without deliberate planning, the gains from AI adoption in banking will accrue primarily to shareholders and highly skilled workers, while the costs fall on employees whose jobs are gradually designed out of existence. They argue for stronger disclosure around how automation affects staffing, as well as support for retraining and community adjustment in areas heavily dependent on financial services employment.
A New Baseline for Banking Employment
For now, there is little sign that the largest banks intend to slow their push toward automation. Executives at Wells Fargo and other institutions have framed 2025 and 2026 as transition years, during which AI systems will move from pilot projects to standard tools embedded in daily workflows. As those systems mature, they are likely to reinforce a new baseline for staffing, one in which the industry can grow its balance sheets and transaction volumes without a corresponding increase in headcount. That does not mean banks will stop hiring altogether. The need for cybersecurity experts, cloud architects, relationship managers, and specialized risk professionals remains strong. But the era when megabanks reliably added thousands of middle-skill office jobs each year appears to be over. The story told in regulatory filings, executive remarks, and workplace surveys is consistent: AI is no longer a distant promise in banking. It is an operational reality, and it is quietly rewriting the employment ledger of some of the country’s most important financial institutions.
Vince Coyner is a serial entrepreneur with an MBA from Florida State. Business, finance and entrepreneurship have never been far from his mind, from starting a financial education program for middle and high school students twenty years ago to writing about American business titans more recently. Beyond business he writes about politics, culture and history.
