In the modern age of artificial intelligence, corporate governance has undergone an evolution that extends far beyond the mere management of managers, as it has come to include the corporate governance of artificial intelligence systems. This paper explores the use of artificial intelligence within the context of corporate governance, exploring how artificial intelligence affects boardroom decisions and creating important governance issues in the process. A comparative approach is used for analysis, comparing pre-AI and post-AI governance, pure human and human-AI mixed forms of governance, and permissive and governance-oriented approaches to regulation. The findings show that AI improves decision-making efficiency, predictions, and risk management by using real-time analytics and pattern recognition technology. On the other hand, several major problems exist, including the black box problem, algorithm opacity, automation bias, bias based on the data used in training AI models, and accountability issues. The article thus suggests that successful AI governance entails adopting a mixture of oversight structures that blend the strengths of machine effectiveness and human accountability, risk-oriented regulation, and effective transparency systems. Corporations should retain their ultimate authority to make decisions but make use of AI as a decision support system.
Arun Kumar Singh (Fri,) studied this question.