Artificial Intelligence (“AI”) is reshaping industries at an unprecedented pace. In today’s technology-driven world, adaptability has become the key to survival. With AI now embedded in our daily lives, regulators too have recognised its disruptive potential and the need to ensure that it is harnessed responsibly.

In this context, the Reserve Bank of India (“RBI”) constituted a committee to develop a framework for the responsible and ethical enablement of AI in the financial sector (“Committee”). The Committee, known as the FREE-AI Committee, released its report on August 13, 2025, setting out its assessment of global and domestic adoption, associated risks, and a forward-looking framework for India’s financial ecosystem (“Report”).

The Report acknowledges that AI offers significant opportunities for the financial sector by analysing alternative data sources, improving customer service through context-aware chatbots, strengthening fraud detection and risk management, and supporting the delivery of inclusive digital services when integrated with India’s digital public infrastructure, such as Aadhaar and UPI. Importantly, the Report emphasises the need to develop indigenous models that can address India’s linguistic and cultural diversity and warns against over-reliance on foreign AI systems, which may not adequately reflect local realities.

At the same time, the Report highlights the risks as AI systems are often opaque and can inherit biases from the data on which they are trained. Errors, design flaws, and hallucinations in generative AI models may lead to unfair outcomes or misleading communications with customers.

The Committee also drew references from global regulatory trends. While the European Union has enacted an omnibus law through the European Union Artificial Intelligence Act, 2024, China has implemented type-specific legislation for different categories of AI, and countries such as the US, UK, and Singapore have opted for guidance-based approaches. Other jurisdictions, including Brazil, Canada, France, and Germany, have issued national AI strategies to signal policy priorities. A common thread across jurisdictions is the emphasis on transparency, accountability, and consumer protection.

In India, the policy approach has been one of enabling innovation while keeping a close watch on risks. Current laws under the Information Technology Act, 2000, and the RBI regulations already cover many AI-related issues, though not in a dedicated manner. Surveys conducted by the Committee revealed that adoption of AI in the financial sector remains uneven, with less than a quarter of entities currently deploying AI systems, concentrated largely among bigger banks and NBFCs. Smaller institutions such as co-operative banks and NBFCs showed little to no adoption, highlighting the divide in technological readiness.

To address these challenges, the Committee has proposed a framework anchored in what it calls the ‘Seven Sutras’:

1. Trust is the Foundation – No compromise being permissible for a sector that safeguards people’s money;
2. People First – Final authority should vest with humans;
3. Innovation over Restraint – AI should serve as a catalyst for augmentation and impactful innovation;
4. Fairness and Equity – AI outcomes should be unbiased and should not discriminate against individuals or groups;
5. Accountability – Entities deploying AI should remain responsible/accountable for their decisions and outcomes based on such systems;
6. Understandable by Design – AI systems must have disclosures and outcomes should be understood by deploying entities; and
7. Safety, Resilience and Sustainability – AI systems should operate securely be secure and resilient to risks (physical, infrastructural, and cyber).

The Report further makes a wide range of recommendations, some of which are listed below:

1. Developing a financial sector digital data infrastructure integrated with India AI’s AI Kosh, aimed at aggregating and standardising diverse datasets across the financial ecosystem;
2. Creating an AI innovation sandbox for experimentation before deployment of AI in practical use, which can be used by banks, fintechs to build, refine, and validate their AI models;
3. Building indigenous financial sector AI models to support smaller banks and institutions that may lack the cloud infrastructure or investment capacity to develop such models independently, thereby ensuring safe and compliance adoption;
4. Mandating board-approved AI policies at regulated entities covering governance, risk management, and consumer protection to ensure responsible and transparent use of AI within financial institutions; and
5. Requiring AI-related disclosures in the annual reports and on the websites of financial institutions to enhance transparency and accountability.

In conclusion, the Report provides a well-rounded roadmap for the responsible adoption of AI in India’s financial sector. It recognises the immense opportunities while addressing the risks with balanced safeguards. If implemented effectively, India can be positioned as a leader in responsible financial AI, fostering innovation without compromising trust and stability.

For regulated entities, the Report underscores that AI adoption can no longer be viewed as a distant ambition but as an imminent reality that requires board-level attention, robust governance, and investment in institutional capacity. If its recommendations are operationalised in letter and spirit, India’s financial sector has the potential to emerge as a global reference point for responsible AI adoption where technological advancement complements regulatory foresight and inclusivity.

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