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Algorithmic Governance Under The Companies Act, 2013: Legal Accountability And Fiduciary Duties In AI-Assisted Decision-Making




Yashasvi Sharma, BBA LLB (Hons.), National Law University, Shimla


ABSTRACT


The growing integration of Artificial Intelligence (AI) into corporate decision- making is transforming how boards oversee strategy, risk, and compliance. While AI enhances efficiency and analytical capabilities, it also creates significant challenges for directors’ legal accountability under Indian corporate law. This paper examines the interaction between AI-assisted governance and the fiduciary duties of directors, including care, skill, diligence, and loyalty, as prescribed under the Companies Act, 2013. Through doctrinal analysis and lessons from international frameworks in the EU and the U.S., it identifies gaps in India’s regulatory landscape and considers potential liability scenarios for both directors and corporations. The study proposes practical solutions, such as algorithmic due diligence, transparency standards, and AI auditing mechanisms, aimed at ensuring that technological adoption strengthens governance while preserving legal responsibility. By addressing the intersection of law and technology, this research provides actionable insights for regulators, boards, and legal practitioners navigating the evolving corporate environment.


Keywords: Algorithmic Governance; Fiduciary Duties of Directors; Corporate Accountability.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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Licensing: 

 

All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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