Regulating Artificial Intelligence in India: Legal Frameworks, Governance Challenges, and the Path toward a Dedicated AI Law

Artificial Intelligence (AI) has emerged as a transformative technology reshaping governance, economy, and social interactions across the globe. India, with its rapidly expanding digital ecosystem, is increasingly relying on AI-driven applications for public administration, law enforcement, healthcare, transportation, and financial services. Despite this exponential growth, the legal and regulatory architecture governing AI remains fragmented, relying primarily on sector-specific laws, the Information Technology Act, 2000, the Digital Personal Data Protection Act, 2023, and various policy documents. This paper critically examines the adequacy of existing legal frameworks in addressing the unique ethical, legal, and socio-technical challenges posed by AI. The analysis begins with an overview of current Indian laws applicable to AI, evaluating gaps pertaining to accountability, algorithmic transparency, data governance, and cyber-security. Special attention is given to the Information Technology Act, 2000 (IT Act) and its provisions relating to electronic contracts, intermediary liability, due diligence obligations, and cybercrimes involving AI systems. The Digital Personal Data Protection Act, 2023 (DPDPA) is analysed for its principles of lawful processing, consent requirements, duties of Data Fiduciaries, and rights of Data Principals in the context of AI training datasets and automated decision-making. Recognising limitations within the prevailing legal regime, the paper argues for a dedicated AI law that is adaptive, risk-based, and future-ready. Drawing comparative insights from the European Union’s AI Act—featuring unacceptable, high, limited, and minimal-risk classifications—and the United States’ evolving policy landscape driven by executive orders and voluntary frameworks, the paper evaluates different regulatory philosophies. Furthermore, it explores crucial themes such as cross-border data flows, data sovereignty, jurisdictional complexities, and India’s strategic stance in securing digital autonomy. The study also examines India’s role in international collaborations on AI governance through institutions such as UNESCO, OECD, and G20, especially in standard-setting, ethical guidelines, and global frameworks on autonomous weapon systems (AWS). Issues of liability, accountability, and responsibility in AI decision-making are analysed within the domains of torts, contracts, product liability, autonomous vehicles, and medical diagnostics. The paper underscores the importance of human oversight in AI systems, highlighting the concepts of meaningful human control, human-in-the-loop, and human-on-the-loop frameworks. Ethical concerns surrounding transparency, explainability, algorithmic bias, discrimination, and fairness are evaluated through emerging global FAT (Fairness, Accountability, Transparency) principles. Finally, practical aspects of AI legal education—such as moot courts, simulations, experiential learning, film reviews, news analyses, and field visits—are proposed to strengthen professional competence in AI law. Conclusively, the paper advocates for a comprehensive, multi-layered, and ethically informed AI legal ecosystem that aligns with international best practices while safeguarding India’s socio-legal realities and technological aspirations.