Ferrara, MassimilianoViglia, GiampaoloRomero, Jose Carlos2026-04-212026-04-2120261873-55090040-162510.1016/j.techfore.2026.1246532-s2.0-105033057978https://hdl.handle.net/123456789/9105https://doi.org/10.1016/j.techfore.2026.124653Organizations 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.eninfo:eu-repo/semantics/openAccessOrganizational TransformationWorkforce DynamicsResource AllocationValue Co-CreationGame TheoryStrategic Information SystemsValue Co-DestructionGenerative Artificial IntelligenceArticle