The adoption of artificial intelligence in government technology in developing countries: a systematic literature review

Abstract

This study systematically reviews empirical evidence on Artificial Intelligence adoption in Government Technology across developing countries, addressing three research questions regarding determinant factors for success, strategies to overcome absorptive capacity constraints, and governance frameworks for responsible implementation. To answer these questions, a systematic literature review was carried out using a structured methodology: The Scopus database was searched with a comprehensive keyword strategy, which initially yielded ninety-three publications. Through rigorous screening and eligibility assessment, fourteen articles meeting all inclusion criteria were analyzed thematically. The findings demonstrate that successful AI adoption requires holistic alignment among institutional factors including policy frameworks and public trust, organizational elements such as human resource capacity and bureaucratic culture, and environmental conditions encompassing infrastructure and societal demands. Effective strategies identified include strengthening digital infrastructure, developing human capital, implementing adaptive governance, fostering multi-stakeholder collaboration, and ensuring contextual adaptation. The study further reveals that legitimate and sustainable implementation necessitates integrating collaborative governance as a legitimacy foundation, Governance, Risk, and Compliance (GRC) frameworks as ethical control systems, and Explainable AI as a transparency mechanism. This integrated approach enables AI to generate both operational efficiency and strategic public value, including social inclusion and progress toward sustainable development objectives.