Responsible implementation of AI in Government: A Systematic Review of Governance and Organizational Structures

Abstract

Responsible Artificial Intelligence (RAI) has emerged as a central concept to guide the development and use of artificial intelligence in government, yet its institutional implementation remains insufficiently understood. This study conducts a systematic literature review of 24 peer-reviewed articles to synthesize how organizational and governance structures enable or hinder the responsible implementation of AI in government. The findings reveal that while transparency, accountability, and legality are widely invoked as guiding principles, their realization depends on institutional capacity, organizational commitment, and the presence of formal governance mechanisms. The study contributes by consolidating fragmented evidence on RAI in government into a structured synthesis of organizational and governance determinants. Beyond mapping existing studies, it develops a conceptual framing that highlights how normative principles, organizational capacities, and governance mechanisms interact to shape implementation, and reveals the symbolic orientation of many current governance practices as a key challenge for moving toward actionable accountability.