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@article{204153,
        author = {Abhemanyu Dhakkite},
        title = {Liability for AI Generated Harms: Rethinking Indian Legal Framework.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {2145-2158},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204153},
        abstract = {The increasing integration of artificial intelligence into decision-making processes has generated new forms of harm that challenge the foundations of traditional legal liability. AI systems, characterized by autonomy, opacity, and multi-actor involvement, disrupt core doctrines of attribution, causation, and fault that underpin existing legal frameworks. This paper examines the adequacy of Indian law in addressing AI-generated harm, focusing on tort law, product liability, contract law, and relevant regulatory regimes. It argues that the current framework is structurally inadequate, not merely due to gaps in interpretation but because of a fundamental mismatch between conventional legal principles and the operational realities of AI systems. Through a detailed doctrinal analysis, the paper identifies key challenges, including the attribution vacuum, causation indeterminacy, and the limitations of fault-based liability. A comparative analysis of the European Union and the United States highlights alternative regulatory approaches, revealing India’s fragmented and underdeveloped position. In response, the paper proposes a structured liability framework combining shared liability across actors, strict liability for high-risk AI systems, mandatory insurance mechanisms, and centralized regulatory oversight. The paper concludes that effective governance of artificial intelligence requires a shift from reactive legal adaptation to proactive regulatory design, ensuring that innovation is matched by accountability.},
        keywords = {},
        month = {June},
        }