Artificial Intelligence (AI) technology has been acknowledged for its transformative potential to improve decision-making processes, efficiencies, and service delivery in the public sector. However, the successful implementation of the AI technology requires the existence of organizational preparedness and supporting institutional contexts. This study assessed the effects of digital infrastructure, human capital, leadership support, data governance, and government support on the readiness for digitalization, AI, and AI-based decision-making in the Nigerian public sector. An explanatory sequential mixed-method approach underpinned by the Technology–Organization–Environment (TOE) and the Resource-Based View (RBV) was used. For the collection of quantitative data, a total of 120 public sector staff from selected Federal Ministries, Departments, and Agencies (MDAs) completed a questionnaire, which was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Qualitative data were collected using interviews conducted with selected key informants and analyzed using reflexive thematic analysis. The quantitative analysis found that digital infrastructure, human capital, leadership support, data governance, and government support positively influenced the readiness for digitalization and AI, which in turn improved AI-based decision-making. Qualitative results indicated that digital infrastructure limitations, disjointed data governance, skills gap in AI, lack of leadership support, and poor institutional coordination continued to represent the major challenges to the implementation of AI in Nigeria's public sector organizations. On the other hand, investments in digital infrastructure, continuous learning and training programs, efficient data governance, active and committed leadership, and comprehensive policy on AI governance were recognized as the key drivers of organizational AI readiness. The current research makes an important contribution to academic knowledge by proposing the Organizational AI Readiness Framework based on the integration of TOE framework and RBV to understand how organization resources and institutional factors enable organizations to make decisions via AI.