Major U.S. banks disclosed plans this week to limit hiring and restructure operations around artificial intelligence, marking a shift in Wall Street employment practices even as firms report record profits. JPMorgan Chase and Goldman Sachs announced they would constrain workforce growth while deploying AI systems across their operations, with executives telling managers to avoid reflexive hiring and warning employees of coming disruptions.
What to Know:
- JPMorgan Chase reported a 12% profit increase to $14.4 billion in the third quarter while headcount grew just 1%, with CFO Jeremy Barnum saying managers have been instructed to avoid hiring as the bank deploys AI across its businesses.
- Goldman Sachs CEO David Solomon told employees the firm would "constrain headcount growth" and conduct limited layoffs this year as part of a multi-year AI reorganization aimed at improving speed and agility.
- The announcements mirror statements from tech companies like Amazon and Microsoft, where leaders have warned workers about AI-related hiring freezes and job cuts as the technology becomes more capable.
Banks Embrace AI Despite Strong Earnings
The announcements came during quarterly earnings reports that showed robust financial performance across Wall Street. JPMorgan, the world's largest bank by market capitalization, posted third-quarter profits of $14.4 billion, up 12% from the previous year. Goldman Sachs reported an even sharper increase, with profits surging 37% to $4.1 billion.
Yet neither bank plans to expand its workforce proportionally.
JPMorgan's headcount increased by just 1% to reach 318,153 employees as of September, a restrained pace that CFO Jeremy Barnum attributed to deliberate strategy rather than market conditions.
The bank has instructed managers across its divisions to resist what Barnum called "the reflexive response to any given need to be to hire more people."
CNBC first reported last month that JPMorgan plans to integrate AI into every client interaction, employee workflow and back-office process. The technology allows for what executives describe as mass production of knowledge work, automating tasks that previously required human judgment and expertise.
CEO Jamie Dimon acknowledged in a Bloomberg interview this month that AI would eliminate certain positions. He said the company would retrain affected workers and suggested overall headcount might still grow, though the third-quarter results indicate that growth has already slowed considerably.
Goldman Outlines Multi-Year Transformation
Goldman Sachs CEO David Solomon provided a more explicit warning in a memo to the firm's 48,300 employees this week. He outlined a comprehensive reorganization that would touch how the company deploys staff, makes decisions and measures productivity.
"To fully benefit from the promise of AI, we need greater speed and agility in all facets of our operations," Solomon wrote.
"This doesn't just mean re-tooling our platforms. It means taking a front-to-back view of how we organize our people, make decisions, and think about productivity and efficiency."
The message contained language rarely used during profitable periods on Wall Street. Solomon said Goldman would "constrain headcount growth" and conduct a limited number of layoffs this year, despite the strong quarterly results. Bank spokeswoman Jennifer Zuccarelli said overall headcount would still rise in 2025, though at a slower rate than revenue growth would typically support.
Goldman's AI initiative will unfold over several years, according to Solomon's memo. The bank plans to measure success through metrics including client experience improvements, profitability gains, productivity increases and employee satisfaction. Initial efforts will focus on reengineering processes such as client onboarding and sales operations.
Solomon framed the changes as necessary for long-term competitiveness. "We don't take these decisions lightly, but this process is part of the long-term dynamism our shareholders, clients, and people expect of Goldman Sachs," he wrote. "The firm has always been successful by not just adapting to change, but anticipating and embracing it."
Understanding AI's Impact on Financial Services
The banks' approach reflects broader patterns emerging across corporate America as AI capabilities expand. Technology companies including Amazon and Microsoft have issued similar warnings to employees about workforce disruptions, implementing hiring freezes and targeted layoffs even while investing billions in AI infrastructure.
Companies have grown more direct this year about AI's employment implications as the technology's underlying models demonstrate increased sophistication.
Investors have rewarded firms perceived as leaders in AI adoption, creating pressure on executives to show tangible progress.
Within banking, operations and support staff face the greatest exposure to AI-driven job changes. These workers, often categorized as back-office and middle-office personnel, handle tasks like transaction processing, compliance checks and data analysis that AI systems can increasingly perform.
A JPMorgan executive told investors in May that operations and support roles would decline by at least 10% over the next five years, even as business volumes expanded.
The technology works differently than previous automation waves. Rather than replacing manual labor with machines, AI systems can perform cognitive tasks that require understanding context, making judgments and generating written content. This capability extends automation into areas previously considered safe from technological displacement, including roles in legal review, financial analysis and customer service.
Closing Thoughts
The simultaneous announcements from JPMorgan Chase and Goldman Sachs signal a fundamental change in how major banks view workforce planning, with executives now treating AI deployment as a substitute for hiring rather than a complement to human workers. The shift arrives during a period of strong financial performance, suggesting that profitability concerns are not driving the restraint, but rather a strategic calculation about the technology's capabilities and competitive pressures from peers and tech companies.