<![CDATA[Abstract— Background: The use of artificial intelligence (AI) in public services accelerates decision-making but also poses ethical risks, bias, and a loss of accountability. This article proposes an AI Government Audit Framework developed using a Design Science Research (DSR) approach. The methodology includes problem identification, artifact design and development, demonstration, and evaluation using conceptual case studies and cross-checking of policy documents. The results indicate that an audit framework combining documentation review, external (adversarial/black-box) testing, and policy compliance assessment can improve transparency and mitigate risks in public AI systems. Recommendations focus on strengthening internal/external audit capabilities, model documentation standards, and regulations for audit disclosure.]]>
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