TLDR: India’s market regulator, the Securities and Exchange Board of India (SEBI), has unveiled a five-point regulatory framework for the responsible adoption of Artificial Intelligence (AI) and Machine Learning (ML) in the securities market. The guidelines, outlined in a consultation paper released on June 20, 2025, aim to foster innovation while safeguarding investor interests through principles covering model governance, mandatory disclosure, data security, bias prevention, and risk controls.
The Securities and Exchange Board of India (SEBI) has taken a proactive step towards regulating the burgeoning use of Artificial Intelligence (AI) and Machine Learning (ML) in the Indian securities market. On June 20, 2025, the market regulator released a comprehensive consultation paper proposing a five-point regulatory framework designed to ensure the responsible and ethical deployment of these advanced technologies, striking a crucial balance between fostering innovation and protecting investors.
The move comes amidst the increasing adoption of AI/ML models by various market participants, including exchanges, brokers, and mutual funds. These technologies are currently being utilized for a wide array of functions, such as surveillance, customer support via chatbots, KYC (Know Your Customer) processes, digital account opening, order execution, fraud detection, and risk management. The advent of Generative AI and Large Language Models (LLMs) is expected to further expand these use cases, necessitating a robust regulatory approach.
SEBI’s proposed framework is built upon five core guiding principles:
1. Model Governance: Market participants will be required to establish internal teams with the necessary technical expertise to monitor AI/ML models’ functioning, efficacy, and performance. This includes documenting model development, handling exceptions, and ensuring traceability of reasoning. Senior management will be held accountable for the entire AI lifecycle, including oversight of third-party vendors. Periodic reviews and independent audits are also envisaged to ensure compliance and control.
2. Mandatory Disclosure: For AI/ML tools that directly impact investors, such as algorithmic trading or advisory services, firms must provide clear and transparent disclosures. This includes detailing the model’s purpose, associated risks, accuracy, and limitations, presented in simple, client-friendly language to foster trust and informed decision-making.
3. Data Security: Emphasizing data integrity and privacy, the framework aligns with India’s Digital Personal Data Protection Act, 2023. Market participants must ensure robust data security measures to protect sensitive information used by AI/ML models.
4. Bias Prevention: The guidelines mandate measures to prevent and mitigate biases in AI/ML models. This involves thorough testing and validation to ensure fairness and prevent discriminatory outcomes, particularly in areas affecting investor decisions or market operations.
5. Risk Controls: Comprehensive risk control mechanisms are a cornerstone of the framework. This includes rigorous testing of AI/ML models, not just before deployment but also continuously thereafter. SEBI has suggested ‘shadow testing,’ where models are run with real-time data without affecting actual operations, to identify potential issues. Market participants are also required to maintain proper documentation of all models and record data for at least five years.
Prior to formulating these guidelines, SEBI constituted a working group tasked with studying Indian and global best practices in AI/ML. This group also engaged with representatives from mutual funds, stock exchanges, and brokers to understand their current utilization of these technologies. The consultation paper, which incorporates the working group’s recommendations, was open for public comments and suggestions until July 11, 2025.
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SEBI’s initiative is seen as a commendable step towards integrating AI/ML governance into India’s capital market framework, aiming to create a future-ready regulatory environment that supports technological advancement while upholding market integrity and investor protection.
