A PwC survey of more than 1,000 director-level and executives at United States financial services firms reveals that artificial intelligence is rapidly reshaping workforce strategies and compensation across the sector. The findings indicate that firms are prioritizing AI proficiency over traditional credentials, with 86% stating that AI skills training is more valuable than an MBA for many new hires, and 91% reporting increased compensation for employees with AI capabilities. Additionally, 58% plan to tie pay directly to AI-enabled productivity.
To source these capabilities, 62% intend to hire new employees with AI-specific skills, 61% plan to upskill existing staff, and 57% expect to partner with external vendors. The emphasis on AI proficiency coincides with significant workforce restructuring: nearly eight in ten executives anticipate their organizations will shrink by at least 20% over the next five years, with entry-level and middle-management roles most vulnerable. While 42% report having conducted enterprise-wide modeling to assess AI’s impact on labor capacity, far fewer have advanced to redesigning workflows or building career pathways for an AI-fluent leadership pipeline.
Employee sentiment presents a parallel challenge. Forty-four percent report that staff are concerned about job security, 43% observe that employees use AI only when required rather than proactively, and 40% say workers feel overwhelmed by the pace of AI-driven change. Change fatigue was cited by 34% as a key barrier to scaling AI across the workforce.
Despite the strategic focus on AI, the financial payoff remains largely unproven. Seventy-seven percent of executives say that most AI investments are not yet delivering measurable return on investment, even as firms report productivity improvements in technology, risk management, and operations. Nearly half have focused their AI workforce efforts on improving productivity, reducing routine work, and integrating AI into daily workflows.
Governance emerges as a critical unresolved area. While nearly 90% say their firms have clear ownership for AI agent decisions, there is no consensus on where material risk responsibility lies, with accountability split across chief executives, technology leaders, risk officers, and business unit heads. More than half report moderate use of shadow AI, unauthorized tools outside centrally governed systems, and 90% acknowledge that such practices create regulatory risk. Fragmented or low-quality data was identified by 41% as the single largest barrier to scaling AI across the workforce, underscoring the operational hurdles that remain as firms attempt to translate AI enthusiasm into sustainable, governed outcomes.
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