Indian Banks Accelerate GenAI Adoption As Implementation Rises To 86%: Report

New Delhi, Aug 13 (KNN) Indian banks are rapidly moving Generative Artificial Intelligence (GenAI) from experimentation to implementation, with the share of lenders having GenAI use cases under implementation rising to 86 per cent in 2026 from 44 per cent in 2025 and 10 per cent in 2024, according to a report by Boston Consulting Group (BCG), FICCI and the Indian Banks’ Association (IBA).

The report, ‘Winning in the AI Era: The New Playbook for Indian Banks’, said wider adoption will require banks to strengthen their operating models, technology infrastructure, talent and governance frameworks.

AI Seen as Key to Future Banking Growth

The report comes as the banking sector enters a period of stronger credit growth. Banking assets grew 3.5 percentage points faster than nominal GDP in the latest year. However, lenders will need to maintain an outperformance of 3.5-4 percentage points over nominal GDP to support India's ambition of becoming a USD 30 trillion economy with around USD 45 trillion in banking assets by 2047.

Reserve Bank of India (RBI) Governor Sanjay Malhotra, speaking at FICCI and IBA's FIBAC 2026 conference in Mumbai on Tuesday, said AI should be treated as a board-level strategic priority rather than a technology procurement exercise.

He said AI could transform financial decision-making in much the same way that UPI transformed payments, particularly by enabling lenders to use alternative data such as cash flows, tax records, utility payments and digital platform records to assess borrowers with limited traditional credit histories.

RBI Flags AI Risks

Malhotra also highlighted risks associated with wider AI adoption, including opaque or ‘black-box’ decisions, bias in lending, concentration among technology vendors, third-party dependencies, data privacy concerns, cyber and adversarial threats, and the weakening of human accountability.

He called on banks to maintain inventories of AI models in production, establish board-approved AI governance policies, ensure explainability for decisions affecting customers, conduct stress tests and red-team exercises, and retain meaningful human oversight where AI failures could cause material harm.

The RBI will continue its regulatory sandbox and develop shared infrastructure, including the digital payments intelligence platform, Malhotra said.

AI Could Lower Cost of Credit

The BCG-FICCI-IBA report identified credit affordability as a key priority for banks. Retail credit bureau coverage increased from 45.5 crore borrowers in 2021 to 78.9 crore in 2026, while MSME bureau coverage nearly doubled from 2 crore to 3.9 crore during the same period.

However, operating and collection expenses account for 40-50 per cent of the total cost of serving borrowers, making small-ticket retail lending particularly challenging. The report said AI-enabled lending could automate processes such as document processing, underwriting and collections, potentially lowering costs.

It also noted that productivity gains from the banking sector's digitalisation over the past decade have been limited, with cost-to-income ratios remaining elevated despite higher technology spending. 

Agentic AI could help address this by handling complex and unstructured tasks and allowing employees to focus on higher-value decisions and customer relationships.

Data, Talent and Governance Remain Challenges

The report identified data and infrastructure readiness, shortages of AI talent and skills, regulatory concerns, governance requirements and uncertainty over returns as key barriers to scaling AI across the banking system.

It also urged banks to strengthen their capabilities in fraud prevention, cybersecurity, operational resilience and management of geopolitical and climate-related risks. 

The report said Indian MSMEs have so far remained resilient to geopolitical pressures, but prolonged stress could increase MSME slippage rates by 1.5-2 times.

The report said AI could help banks redesign processes, reduce the operating cost of credit and improve the speed and precision of financial decisions. However, the benefits will depend on how effectively lenders combine technology adoption with appropriate governance, skilled personnel and accountability.

(KNN Bureau)