Artificial intelligence (AI) is becoming part of how banks plan their workforces, serve customers, review information, and manage costs. Recent reports show that major banking and financial services firms have announced tens of thousands of job cuts in 2026, including a large restructuring at Citigroup Inc. tied to changes in operations, document review, and internal processes.

Still, the story is not as simple as “AI means fewer jobs.” The broader labor market remains active. The U.S. Bureau of Labor Statistics reported that employers added 172,000 jobs in May 2026, while the unemployment rate stayed at 4.3 percent. At the same time, employment in financial activities declined, showing that job growth can vary by sector even when the overall labor market remains active. In banking, AI is becoming an important reason employers are rethinking which jobs they need, how much work can be automated, and which skills make employees more valuable.

One takeaway is clear: AI skills are becoming part of the basic career toolkit. A generation ago, finance students were told they needed Excel skills. Today, they still need Excel, but they also need to know how AI can help build spreadsheets, test formulas, summarize data, spot unusual patterns, and explain results. The job candidates who can combine business judgment with AI tools will have an advantage over candidates who know only one or the other.

Where AI Is Showing Up in Banking

Banking depends on information. Banks collect data from customers, process payments, monitor transactions, review contracts, prepare reports, and follow detailed regulations. Much of that work involves large volumes of text, numbers, and routine decisions, which makes it a natural place for AI tools to be tested.

Some banks are using AI to improve customer interactions. Others are using it behind the scenes to review transactions, summarize information, support compliance work, and help employees search internal research. Citigroup has been developing AI support for wealth management clients. Barclays has used generative AI to condense large numbers of customer-service calls into usable summaries. Revolut has introduced an assistant that helps customers understand spending and manage accounts.

These examples show why AI can appeal to bank managers and investors. If software can complete parts of support work more quickly, banks may be able to reduce expenses or move employees into higher-value work. That can help profit margins, especially in an industry where labor, technology, risk management, and compliance are major costs. 

But efficiency does not eliminate risk. Banks cannot simply replace people with technology and hope for the best. They operate under strict rules, and mistakes in lending, customer service, legal review, or compliance can lead to fines, lawsuits, regulatory attention, and reputational damage. AI systems also need employees who can test them, monitor them, and understand when the output may be wrong. In banking, a faster process is only valuable if it is also accurate, fair, and legally sound.

The Entry-Level Challenge

AI may affect entry-level work because many early-career finance tasks involve building spreadsheets, preparing reports, checking documents, updating models, and organizing information. These tasks are very valuable and are often how new employees learn the business. When junior analysts review documents or build models, they are also learning how deals work, how risks are measured, and how senior employees make decisions.

This creates a challenge for banks. If AI handles too much of the basic work, companies may save time in the short term but weaken the training path for future managers and executives. Some banks are already becoming more selective in graduate hiring and placing more emphasis on employees who can work with data, technology, and AI systems. At the same time, banking still depends on developing talent from within, so entry-level hiring is unlikely to disappear entirely.

The response has not been the same at every bank. Bank of New York Mellon has leaned into younger workers’ familiarity with AI by increasing opportunities for interns and analysts. Meanwhile, one global survey cited in reporting on the industry found that many CEOs expect to reduce junior roles over the next one to two years, while a much smaller share expect to increase them.

Other large banks continue to bring in new talent even as they look for productivity gains. Bank of America, for example, has continued to emphasize internships and full-time recruiting while also trying to keep overall staffing levels under control through AI-enabled efficiency.

AI is making banking more efficient, but efficiency is only part of the story. Banks may benefit from lower costs, faster processes, and stronger margins, but they also face risks if automation weakens compliance, customer service, or employee development. The central question is not whether banks will use AI. It is how they will use it without undermining the judgment, oversight, and trust that the industry depends on.

In the Classroom

This article can be used to discuss banking (Chapter 15: Money and the Financial System).

Discussion Questions

  1. What types of banking tasks are already being supported by AI?

  2. Why might investors like AI-driven restructuring at banks? 

  3. How could AI affect entry-level finance jobs and the career ladder?

This article was developed with the support of Kelsey Reddick for and under the direction of O.C. Ferrell, Linda Ferrell, and Geoff Hirt.