A new survey of senior financial executives suggests that artificial intelligence will initially expand, rather than shrink, the workforce across the financial services sector. The findings challenge the widespread assumption that automation will quickly translate into large-scale job cuts and lower operating costs.

According to Bloomberg Intelligence, which surveyed 151 executives at banks, insurers, and asset managers, roughly two-thirds of financial institutions expect staff numbers to increase in the early phase of AI adoption. More than 70% of respondents also anticipate higher operating expenses over the next three years, as firms make significant investments in technology, infrastructure, and capability development.

Bloomberg Intelligence analysts Diksha Gera and Tomasz Noetzel said this early stage of AI integration is less about cost reduction and more about “building the foundation” for long-term automation. They noted that firms are still laying the groundwork – training employees, restructuring workflows, and implementing governance systems – before AI can deliver large-scale efficiency gains. According to the report, cost ratios may begin to normalize after 2027-2028, potentially unlocking meaningful margin expansion.

The pace of AI adoption in financial services has so far been slower than in sectors such as retail or technology, largely due to stricter compliance requirements and higher risk-management thresholds. Still, several major institutions, including ING Groep, Allianz, and Goldman Sachs, have linked AI initiatives to future headcount reductions, signaling that longer-term efficiency gains remain part of the industry’s strategy.

Despite the cautious rollout, analysts generally agree that AI is set to transform the sector. Research from UBS Group AG suggests that banks may emerge as some of the biggest beneficiaries of rapidly improving AI technologies, with early signs potentially visible as soon as next year. UBS analyst Jason Napier wrote that 2026 could mark a turning point, as equity markets begin to price in AI-driven productivity gains even before hard data fully materializes.

Across industries more broadly, executives view the disruptive potential of AI as “high” to “very high.” Pharma companies expect significant reductions in drug-development costs, media executives anticipate personalized content and lower production expenses, and consumer companies foresee AI agents evolving into “shopping companions.”

While the long-term impact remains unmistakable, the message from Wall Street’s early experience is clear: the AI revolution will require more people – not fewer – before its promised efficiencies materialize.