AI-DRIVEN CORPORATE GOVERNANCE:A STRUCTURED LITERATURE REVIEW OF AI APPLICATIONS IN FINANCIAL AND NON-FINANCIAL SECTORS

Abstract

This purpose of this study is to provide structured review of literature on Artificial Intelligence (AI) driven corporate governance and particularly its application in both financial and non-financial sectors. Through the discussion of 53 research findings delivered by various scholarly sources, the paper identifies how the field of AI applications, including machine learning, natural language processing, and blockchain, alters governance practices. The review looks at how AI transforms the most important governance tasks, such as risk management, monitoring compliance, making decisions, and interacting with shareholders. Artificial intelligence applied, in the financial field, to improve fraud detection, to optimize portfolio management and to enhance regulatory compliance. AI is also reshaping organizational decision-making in the non-financial sectors, supply chain administrations and corporate social responsibility (CSR). The article emphasizes the likelihood of AI to make governance more effective through analyzing data in the real time, ensuring transparency, and minimizing bias in the judgment. Nonetheless, it also deals with some issues of ethics, legal and regulatory barriers and technological constraints like the privacy of data and compatibility with old systems. Secondly, the paper advises on the prospects of AI in corporate governance in the future (the main aspects are its increasing automation, metrics that assessed in real-time and better stakeholder engagement). At the end of the review, it concluded that clear regulatory systems and organizational preparedness needed to achieve responsible and productive integration of AI. The results can complement the already existing literature on the use of AI in governance and inform the efforts of businesses, policymakers, and researchers that seek to maximize the influence of Al on corporate governance.