AI, Risk and Responsibility: A Pragmatic Approach to AI Regulation in Indian Securities
Pragati Purohit and Muskan Suhag
(National University of Study & Research in Law, Ranchi.)
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Abstract
The rising adoption of Artificial Intelligence (AI) in financial markets has prompted
regulatory bodies worldwide to reassess their regulatory mechanisms. In India, the Securities and Exchange Board of India (SEBI) has introduced amendments to impose strict liability on regulated entities using AI/ML. While intended to ensure accountability, SEBI’s approach poses multiple challenges, including the AI black box problem, misplaced liability for client decisions, unjustified responsibility for third-party AI tools and a failure to differentiate between various AI-driven trading models. The paper thoroughly examines these issues and contends that SEBI’s one-size-fits-all regulatory framework may stifle innovation and create burdens on market participants.
Taking lead from international best practices, such as the European Union Artificial
Intelligence Act, 2024, US Department of the Treasury, IOSCO’s 2021 Guidance and
ASIFMA’s regulatory principles, this paper calls for a more proportionate and risk-based
regulatory model. It proposes that SEBI adopt a classification-based approach, differentiating AI systems based on risk levels and human involvement, while also incorporating evolving regulatory frameworks that promote AI innovation without compromising investor protection. Further, structured industry engagement, technology-agnostic policies etc. are recommended as pragmatic solutions.
In essence, this paper highlights the need for a balanced AI regulatory mechanism that aligns with global standards while ensuring India’s financial markets remain resilient, competitive and innovation-driven.​