Strategic tensions in organizational GenAI adoption: A game theory modeling of internal resource competition, workforce dynamics, and value management
构建多层级贝叶斯博弈模型，分析管理层、部门与员工在生成式AI采纳中的互动，发现协调策略优于技术优先策略，并给出三个成功条件。
Organizations adopting generative AI (GenAI) face complex strategic tensions among management, departments, and employees that fundamentally determine adoption outcomes. This study develops a multi-level Bayesian game-theoretic framework modeling these multi-stakeholder interactions, identifying four distinct adoption patterns through formal equilibrium analysis. Our theoretical derivations establish that successful GenAI implementation requires three analytically-derived conditions: (1) strong strategic complementarity across departments, (2) efficient investment allocation, and (3) effective employee displacement mitigation. The formal model specifies explicit utility functions for three stakeholder groups — senior management, departmental units, and individual employees — and characterizes Bayesian Nash equilibria under incomplete information. Companies must simultaneously invest in cross-functional coordination mechanisms, establish shared governance structures, and implement workforce development programs that position GenAI as a capability enhancement rather than a job replacement. Our computational analysis, based on 10,000 Monte Carlo simulations with explicit parameter specifications and convergence criteria, demonstrates that coordination-focused strategies significantly outperform technology-focused approaches in organizational welfare, providing actionable guidance for AI transformation leadership. • Multi-level Bayesian game models GenAI adoption inside organizations. • Strategic complementarity drives coordinated GenAI value creation. • Employee displacement risks critically shape adoption equilibria. • Coordination strategies outperform technology-first GenAI adoption. • Formal thresholds distinguish value co-creation from co-destruction.