U.S. banks are increasing their investments in artificial intelligence technology at a rapid pace, but this growth is happening alongside mounting regulatory and compliance challenges. According to a recent Finastra report, financial services firms in the United States now lead global peers in AI adoption maturity, with a larger share of use cases already deployed in production. Nearly half of U.S. financial institutions surveyed plan to boost AI spending by more than 50% this year, signaling that tech modernization remains a top priority despite growing external pressures.
However, regulatory concerns are shaping how these banks approach AI deployment. About 50% of U.S. executives cited compliance and regulatory hurdles as significant barriers to scaling modernization efforts—higher than the global average. Data sovereignty and stringent data-handling requirements are among the issues that U.S. banks prioritize even when doing so could slow down innovation.
In addition to compliance challenges, many banks are grappling with talent shortages that complicate efforts to build and manage AI systems effectively. Skills gaps in areas such as data science, digital transformation, and AI governance were reported more frequently by U.S. financial leaders compared with their global counterparts, adding another layer of complexity to rolling out advanced technologies at scale.
Despite these obstacles, U.S. banks continue to lead in practical AI use cases such as data analysis, reporting, document intelligence, and credit underwriting. Banks are also participating in industry collaborations—like the development of standardized AI controls frameworks—to help navigate both regulatory expectations and operational risks, with hopes of accelerating secure and responsible AI adoption across the sector.
