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Artificial Intelligence (AI) has entered the public domain with remarkable momentum. Since 2022, AI models have significantly advanced in capability and accessibility, benefiting both organisations and individuals. As a result, the adoption of AI technologies has witnessed exponential growth over the past few years.
It has evolved from rule-based systems to machine learning and deep learning, with Generative AI now driving transformation across industries. In India, financial regulators are moving from observation to action and have guardrails in place for AI. SEBI’s consultation paper (June 2025) and RBI’s FREE-AI framework (August 2025) mark a shift, AI is now seen as regulated infrastructure, not just experimental tech.
Despite its potential, adoption remains cautious. RBI reports only ~20% of regulated entities use AI, mostly in basic or moderately complex forms. Key barriers include talent gaps, high costs, limited data quality, and legal uncertainty. Regulators are addressing these through collaborative frameworks involving government, industry, and SROs.
AI could automate or augment nearly two-thirds of financial services processes. But with innovation comes risk. The new frameworks aim to ensure AI is deployed responsibly, with clear guardrails, strategic intent, and sector-wide accountability.
AI is gradually transforming India’s financial services sector, but adoption remains uneven. While large institutions are advancing with sophisticated AI models, smaller firms face challenges like fragmented data, legacy systems, talent shortages, and regulatory uncertainty, widening the ‘AI divide.’
Key barriers include limited access to clean, representative datasets, high implementation costs, and dependence on opaque third-party solutions. Regulatory ambiguity, especially around the Digital Personal Data Protection Act (DPDP, 2025), adds to the hesitation.
Adoption also varies by sub-sector. Capital markets lead with AI-driven trading and surveillance, while banks, NBFCs, and insurers remain cautious due to systemic risks and longer feedback cycles. Regulators are expected to take a tailored approach—balancing innovation with safeguards to ensure responsible and inclusive AI adoption.
The Government of India is actively addressing structural barriers to AI adoption through national initiatives aimed at creating a level playing field. These efforts complement sectoral frameworks from RBI and SEBI, enabling financial firms to leverage AI responsibly and at scale.
Key initiatives include:
With an INR 10,371 crore outlay, this programme builds public infrastructure for AI, standardised datasets (AI Kosh), compute platforms, and skill development (IndiaAI FutureSkills Programme), to support smaller firms and reduce entry barriers.
Establishes a unified health data backbone, enabling insurers to adopt AI for underwriting, claims automation, and fraud detection.
CERT-In’s directives set baseline controls for AI-heavy systems, ensuring safety and accountability across digital platforms.
The Reserve Bank of India’s FREE-AI framework sets the foundation for safe, transparent, and inclusive AI adoption in the financial sector. Built on 7 guiding principles (Sutras) and 6 thematic pillars, it outlines 26 actionable recommendations for banks, NBFCs, fintechs, SROs, and regulators.
Key focus areas include:
Shared access to curated datasets and models via platforms like AI Kosh.
Board-approved AI policies with clear accountability and fairness thresholds.
Skill-building across roles and support for safe experimentation.
Tiered oversight based on model impact, with comprehensive inventories.
Fairness assessments, explainability, and customer recourse mechanisms.
Independent validation, audits, and incident reporting aligned with supervisory norms.
FREE-AI promotes innovation with safeguards, ensuring AI enhances inclusion, efficiency, and trust. It aligns with national initiatives like the IndiaAI Mission, DPDP Act, and CERT-In norms, positioning AI as a strategic, regulated infrastructure for the future of finance.
In June 2024, SEBI released a consultation paper on the responsible use of AI and ML in securities markets. Recognising AI’s growing role in trading, surveillance, advisory, and asset management, SEBI aims to ensure innovation is balanced with transparency, fairness, and investor protection.
Key proposals include:
Firms must maintain detailed documentation of AI models, including purpose, training data, and limitations.
Investors and regulators must be informed when AI tools are used in advisory or execution.
Continuous testing to ensure reliability, fairness, and compliance.
AI-driven advice must align with investor profiles and avoid bias.
AI systems must comply with data protection laws, including the DPDP Act.
AI algorithms must adhere to existing trading safeguards like circuit breakers and risk checks.
SEBI’s message is clear: AI must be transparent, auditable, and fair. Responsible adoption will strengthen trust and efficiency, while opaque systems may face regulatory and reputational risks.
While IRDAI hasn’t issued a dedicated AI rulebook yet, it is actively encouraging innovation with safeguards. Through its sandbox framework, insurers and insurtechs can test AI-driven solutions, like underwriting, pricing, and claims automation, in a controlled environment.
IRDAI also supports integration with the Ayushman Bharat Digital Mission (ABDM), enabling AI-powered processes based on standardised, consent-driven health records. The regulator emphasizes fairness, transparency, and data protection, ensuring AI doesn’t exclude vulnerable groups or compromise consumer trust.
As part of its broader reform agenda, IRDAI sees AI as a key enabler of scale and efficiency—provided it’s adopted responsibly, with strong consumer safeguards and explainable outcomes.
AI adoption is shifting from innovation to governance. Banks and large NBFCs must treat AI as a board-level risk, demanding transparency and assurance-ready models. Smaller NBFCs and co-operatives can leverage IndiaAI infrastructure but must build internal capacity. Capital market players must ensure AI is auditable, fair, and disclosed to investors. Insurers are encouraged to innovate via sandbox pilots, with strong safeguards. Fintechs must move from disruption to partnership, offering compliant, trustworthy solutions. Across sectors, the message is clear: AI is inevitable, but trust, transparency, and accountability are non-negotiable.
