Strategic enablers of sustainable AI-driven public service transformation in Nigeria: a fuzzy DEMATEL-based model

Purpose This study investigates the strategic enablers of sustainable AI-driven transformation in Nigeria’s public sector. It aims to identify the key drivers and dependencies that can support not only digital modernization but also long-term institutional resilience, inclusive governance and improved service equity. Design/methodology/approach A fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) framework was applied to evaluate 12 high-impact enablers of AI adoption. Data were gathered through expert surveys with digital transformation professionals in government agencies. This method facilitated the construction of a causal model highlighting the influence and dependence relationships among the enablers. Findings The analysis identifies policy frameworks, digital infrastructure and leadership commitment as dominant causal drivers of AI adoption, while organizational culture, capacity building and data availability emerge as dependent outcomes. Strengthening these foundational enablers is essential for achieving a sustainable and scalable integration of AI into public services. The model provides a decision-support tool for prioritizing resource allocation in a way that ensures long-term impact, continuity and adaptability. Nonetheless, by concentrating solely on enabling factors, the study does not account for potential barriers or risks that may hinder AI implementation, an aspect that future investigations should explore to offer a more balanced and actionable perspective. Originality/value This study contributes a novel, prescriptive framework that links AI strategy with sustainable public sector innovation in a developing country context. It advances the application of fuzzy DEMATEL in government transformation research and offers actionable guidance for building future-ready institutions capable of delivering equitable and enduring service improvements.