AI capacity in the public sector: Pathways from the environmental context to an organizational impact

Artificial intelligence (AI) is reshaping the operation of public organizations, yet many still struggle to harness its full potential amid institutional complexity and digital transitioning. Characteristically different from the private sector, the public sector requires the development and testing of specific models. However, most studies on the impact of AI have focused primarily on the private sector, leaving public organizations largely underinvestigated. This study examines how public sector agencies develop AI capacity and how this contributes to performance through key internal mechanisms, including organizational creativity and AI management. Using the resource-based view as a guiding framework, a structural model was developed to capture the effects of government mandates, citizen expectations, regulatory clarity, and public incentives on AI capacity and its organizational outcomes. Survey data from 225 senior managers employed in Vietnamese public organizations were analyzed using partial least squares–structural equation modeling. The findings illustrate that environmental context plays a crucial role in enhancing AI capacity, which, in turn, impacts both creativity and performance. However, AI management is not yet consistently translated into AI-driven decision-making, suggesting that public organizations are still in the early stages of embedding AI into their strategic processes. The study demonstrates that the performance benefits of AI are contingent on a comprehensive approach. Further, these gains are a function of not only technology but also key complementary factors, such as cultural readiness, managerial alignment, and institutional support. The study provides practical recommendations for leaders in emerging economies, outlining ways to strengthen governance and address complex challenges via more effective integration of AI into organizational operations.