ARTIFICIAL INTELLIGENCE IN CORPORATE GOVERNANCE: BOARD DECISION-MAKING, ACCOUNTABILITY, TRANSPARENCY, AND EMERGING ETHICAL CHALLENGES
Abstract
Artificial intelligence (AI) is a growing factor in shaping the future of corporate governance by impacting the decision-making process, risk management, accountability structures, transparency and stakeholder engagement. The use of AI in governance has legal, organizational, and ethical issues, but can also enhance information processing, forecasting, monitoring, and strategic decision-making. This narrative review brings together literature regarding the use of AI in corporate governance, focusing on how AI can support board decision-making, accountability for algorithm-based decision-making, explainability, ethical oversight, governance mechanisms, and regulatory expectations. The literature indicates that AI should serve as a tool for enhancing, not replacing, the director's ability to make decisions. There are decisions that are still human governance responsibilities, such as the fiduciary responsibility, reasoning in context, balancing the stakeholders and accounting for the ethics. One of the main issues is the accountability deficit resulting from opaque or autonomous systems that drive consequential corporate decision making. Thus, in responsible adoption, the following factors are essential components: explainability, internal auditing of algorithms, human oversight, board AI literacy, organizational AI governance structures, and clearly defined roles and responsibilities. The review also points out issues of algorithmic bias, privacy, employee effects, cybersecurity, sustainability, and efficiency versus stakeholders. A responsible AI governance framework is suggested, where the technological capability is paired with human oversight, transparency, accountability, ethical protection, and regulation. Empirical studies of the use of AI, interaction with AI, liability allocation, AI assurance and governance impacts in various institutional environments are areas of future research that should be explored.
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