U.S. Workers Proactively Driving AI Adoption in the Workplace

A KPMG survey of more than 2,100 U.S. employees finds AI adoption is being driven from the bottom up—87% use AI at least weekly and 51% daily—while anxiety about job displacement has nearly doubled to 52%. Although 77% say AI lets them focus on higher-value work, 84% want more AI training, highlighting a leadership gap where productivity gains are not translating into perceived career security and prompting calls to reinvest benefits into upskilling and clear career paths. The report also surfaces talent risks: six in 10 Gen Z workers fear replacement within two years and favor in-person mentoring, and women are markedly less likely than men to prefer full-time office schedules (31% vs. 50%), underscoring the need for apprenticeships, mentorships and flexible hybrid models to retain diverse talent.

Analysis

The 2025 KPMG American Worker Survey of more than 2,100 U.S. employees documents a clear bottom-up adoption of AI: 87% of workers use AI at least weekly and 51% use it daily, while 77% say AI helps them focus on higher-value work and 84% want more AI training. This adoption is translating into productivity at the individual level but not into confidence about career security.

Worker anxiety has increased materially: concern that AI could replace jobs nearly doubled to 52% year-over-year and six in ten Gen Z workers fear replacement within two years, creating a stark leadership gap between employee-led innovation and perceived long-term opportunity. KPMG highlights the need for employers to reinvest AI-driven gains into upskilling, mentorships and new career on-ramps to bridge this trust and value gap.

The survey also surfaces retention and diversity risks tied to workplace models: Gen Z values on-site mentorship while only 31% of women prefer full-time office work versus 50% of men, arguing for hybrid, apprenticeship and accelerated-development programs. External signals rate sentiment as mixed with a modest near-term market impact (market_impact_score 0.25), implying these are strategic human-capital issues likely to affect long-term operating efficiency and talent costs rather than immediate earnings shocks.

Key Decisions for Investors

• Assess company disclosures on AI training and measurable upskilling spend and favor firms with explicit plans to reinvest AI productivity gains into employee development
• Prefer employers that articulate modernized career pathways (mentorships, apprenticeships, accelerated programs) and flexible hybrid models to mitigate Gen Z and gender-related retention risks
• Monitor leading human-capital indicators — percent of workforce using AI, training participation, turnover among early-career cohorts, and RTO outcomes — as material long-term risk factors even if near-term market impact appears limited