A framework for AI readiness and strategic adoption: developing a public sector AI maturity model through systematic review and synthesis
TL;DR
The analysis shows that AI adoption in public administration is primarily driven by organizational and environmental determinants rather than by technical capabilities alone, and proposes a five-level AI maturity model illustrating a cumulative progression from ad hoc experimentation to integrated and accountable AI use.
Abstract
The purpose of this paper is to identify the key determinants influencing artificial intelligence (AI) adoption in public administration and to organize them into a maturity framework that supports responsible and progressive implementation. This paper is based on a conceptual and integrative literature review of 32 academic and institutional studies on AI adoption in the public sector. Identified determinants were analyzed using the Technology–Organization–Environment (TOE) framework and subsequently structured into a maturity model inspired by the capability maturity model integration. The analysis shows that AI adoption in public administration is primarily driven by organizational and environmental determinants rather than by technical capabilities alone. Leadership, governance, transparency and ethical oversight emerge as central conditions shaping adoption trajectories. Based on these findings, the paper proposes a five-level AI maturity model illustrating a cumulative progression from ad hoc experimentation to integrated and accountable AI use. This paper contributes by organizing existing AI adoption determinants into a coherent maturity-based sequence. By combining the TOE framework with a developmental perspective, it provides structured guidance for understanding how public-sector AI capabilities evolve over time.