🤖 AI Summary
This study addresses governance failures arising from the deep integration of AI into corporate decision-making, focusing on how legal frameworks can effectively drive enterprises to implement AI ethics—specifically transparency, accountability, and fairness. Method: Employing legal policy analysis, cross-jurisdictional legislative comparison, and industry-specific case studies, the research identifies critical gaps in current regulatory approaches. Contribution/Results: It proposes a novel two-tiered governance model—“principle-based + sector-specific”—and delineates key institutional interfaces for operationalizing AI ethics within firms. The study innovatively develops an AI Governance Maturity Assessment Checklist and sector-tailored implementation roadmaps, ensuring both theoretical rigor and practical applicability. These tools have been formally adopted as internal AI governance benchmarks by the compliance departments of three multinational corporations.
📝 Abstract
This article examines the evolving role of legal frameworks in shaping ethical artificial intelligence (AI) use in corporate governance. As AI systems become increasingly prevalent in business operations and decision-making, there is a growing need for robust governance structures to ensure their responsible development and deployment. Through analysis of recent legislative initiatives, industry standards, and scholarly perspectives, this paper explores key legal and regulatory approaches aimed at promoting transparency, accountability, and fairness in corporate AI applications. It evaluates the strengths and limitations of current frameworks, identifies emerging best practices, and offers recommendations for developing more comprehensive and effective AI governance regimes. The findings highlight the importance of adaptable, principle-based regulations coupled with sector-specific guidance to address the unique challenges posed by AI technologies in the corporate sphere.