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The Transformative Impact Of Generative AI on Indian Corporate Law: Efficiency, Compliance, And Governance In 2025




Rajaalan A & Thirumudhukundran V, LL.M., Central University of Tamilnadu, Thiruvarur


ABSTRACT:


This study explores how Generative AI (Gen AI) is change corporate law by 2025, filling a key gap in understanding its combined influence on operational efficiency, regulatory compliance, and governance practice particularly in the context of evolving data protection frameworks. The important challenge lies in maximising Gen AI’s productivity advantages while addressing emerging concerns such as data privacy, intellectual property (IP) violations, and algorithmic bias. The research shows patterns of adoption, compliance barriers, ethical implications, and the role of regulation in shaping responsible AI use. Using a qualitative review of existing literature, the analysis reveals that while Gen AI substantially enhances efficiency in legal processes, it also introduces complex compliance issues under the DPDPA, heightened IP risks, and pressing demands for stronger governance and ethical oversight. The study recommends implementing DPDPA aligned AI policies, proactive IP protection measures, robust internal governance systems, continuous professional training, and active participation in regulatory development.


Keywords: Artificial intelligence, Corporate Legal Practice, Regulatory Compliance, Ethical Governance, Operational Effectiveness.



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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