Background and Aim: The rapid expansion of Generative Artificial Intelligence (GenAI) in the public sector presents opportunities for administrative efficiency and policy innovation, yet raises complex governance challenges concerning ethics, accountability, and institutional readiness. This study aims to develop a strategic governance model for GenAI adoption and management in public-sector organizations, with Iran serving as the primary contextual anchor within a broader cross‑national sample of developing administrative systems.
Method: Employing a qualitative grounded theory approach, semi-structured interviews were conducted with 22 experts, policymakers, and senior specialists selected through purposive and snowball sampling until theoretical saturation. Data were analyzed using open, axial, and selective coding procedures.
Findings: The findings reveal a paradigmatic model comprising causal, contextual, intervening, core, action/interaction strategies, and consequential categories. Institutional Adaptive Capacity emerged as the core phenomenon, operationalized through three interdependent dimensions: strategic data management, algorithmic accountability, and human–machine synergy. Key driving pressures, institutional enablers, and moderating factors (trust and risks) shape strategic responses and governance outcomes. Conclusion: Effective GenAI governance requires a proactive, multi-level, and context-sensitive framework centered on adaptive capacity. Such a framework supports responsible innovation, mitigates institutional and ethical risks, and strengthens transparency, accountability, and public trust in AI-enabled public services.