Board Oversight of Artificial Intelligence: Redefining Corporate Governance for Algorithmic Decision-Making
DOI:
https://doi.org/10.15662/IJEETR.2025.0704019Keywords:
Artificial intelligence, corporate governance, board oversight, algorithmic decision-making, AI governance, corporate accountability, responsible AI, strategic management, enterprise risk management, board leadershipAbstract
Artificial intelligence (AI) is increasingly transforming corporate decision-making by enabling organizations to automate processes, enhance strategic planning, improve operational efficiency, and generate data-driven insights. As AI systems become deeply embedded in organizational operations, they also introduce complex ethical, legal, strategic, operational, cybersecurity, and reputational risks that extend beyond traditional corporate governance mechanisms. While existing governance frameworks primarily emphasize financial oversight, regulatory compliance, and shareholder accountability, they often provide limited guidance regarding board-level oversight of algorithmic decision-making and AI governance. Consequently, corporate boards are under growing pressure to expand their governance responsibilities to ensure that AI systems are deployed responsibly, transparently, and in alignment with organizational objectives and stakeholder interests. This study develops a conceptual framework that redefines corporate governance by positioning board oversight as the central mechanism for responsible AI governance and algorithmic accountability. Adopting a conceptual research approach, the study synthesizes scholarly literature published through December 2024 on artificial intelligence, corporate governance, board responsibilities, enterprise risk management, AI ethics, and algorithmic decision-making. The findings indicate that effective AI governance requires boards to move beyond conventional oversight functions by strengthening AI competencies, integrating AI-specific governance structures, improving strategic and ethical oversight, and enhancing organizational accountability. The proposed framework demonstrates how board oversight influences responsible algorithmic decision-making through strategic governance, risk management, ethical leadership, regulatory compliance, and continuous organizational learning. The study contributes to the corporate governance literature by integrating fragmented perspectives into a comprehensive governance model while providing practical guidance for boards seeking to govern AI-enabled organizations responsibly
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