Blockchain Technology and Artificial Intelligence in Corporate Governance: A Comparative Analysis of Regulatory Responses and Fiduciary Implications Across Emerging and Developed Markets
Keywords:
Blockchain technology, Artificial intelligence, Corporate governance, Comparative corporate law, Fiduciary duties, Emerging markets, Digital transformation, Regulatory frameworks, Shareholder rights, Decentralized autonomous organizationsAbstract
The intersection of blockchain technology and artificial intelligence (AI) with corporate governance represents one of the most transformative developments in contemporary corporate law. This article provides a comprehensive comparative analysis of how different legal systems across emerging markets (India, China, Brazil) and developed economies (European Union, United Kingdom, United States) are responding to the integration of these disruptive technologies into corporate governance frameworks. Through systematic examination of legislative reforms, regulatory approaches, and judicial interpretations across these jurisdictions, this study identifies divergent pathways in addressing challenges related to board fiduciary duties, shareholder rights, transparency mechanisms, and accountability structures in technology-mediated governance systems. The analysis reveals that while developed markets emphasize standardization and cross-border harmonization through instruments like the EU Digital Corporate Law framework, emerging markets adopt more experimental and flexible approaches that balance innovation with investor protection concerns. This article contributes to the literature by proposing a "Hybrid Governance Framework" that synthesizes the strengths of both regulatory approaches, offering practical recommendations for policymakers, corporate practitioners, and scholars navigating this evolving landscape. The findings demonstrate that successful integration of blockchain and AI in corporate governance requires reconceptualization of traditional legal doctrines, particularly concerning fiduciary duties, legal personality, and liability attribution in algorithmic decision-making contexts.
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