<![CDATA[This study examines the implementation of a comprehensive Artificial Intelligence (AI) governance framework and its transformative impacts across the banking, healthcare, and judicial sectors. The article review was conducted using data extraction methods, sectoral analysis, and integrative synthesis of selected literature. The findings indicate that effective AI governance requires a structured approach across data, model, and system dimensions to ensure cybersecurity. Its implementation varies across sectors: in banking, it focuses on real-time fraud detection; in healthcare, it emphasizes data privacy through federated learning techniques; and in the judicial sector, AI functions as decision-support for judges under strong human oversight. The operational impacts of AI are reflected in increased efficiency and predictive analytics, while the social impacts include the potential for algorithmic bias and erosion of trust. Human–machine collaboration (human-in-the-loop) is proven to be a critical success factor in maintaining academic integrity, building customer trust, and ensuring substantive justice, by positioning humans as the final decision-makers in ethical and contextual considerations.]]>
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