Abstract: Organizations investing billions in artificial intelligence often see uneven adoption patterns across their workforce, despite strong leadership support and comprehensive training programs. This article examines why peer influence frequently outweighs formal leadership in driving AI adoption, drawing on social network research, organizational behavior theory, and emerging adoption data. Evidence suggests that while leadership creates necessary conditions for change, employees look primarily to trusted colleagues for social proof that new technologies are safe, practical, and valuable. We analyze the mechanisms through which peer networks accelerate or inhibit AI adoption, examine organizational consequences of adoption gaps, and present evidence-based strategies for leveraging informal networks to drive technology integration. The article synthesizes research on social influence, knowledge diffusion, and organizational learning to provide practitioners with actionable approaches for accelerating AI adoption through peer-to-peer influence rather than top-down mandate alone.
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