Indian Banks Race to Adopt GenAI: Challenges & Future

Indian banks are rapidly moving Generative Artificial Intelligence (GenAI) from experimental stages to widespread adoption, with a significant increase in implemented use cases projected by 2026.

This transition is highlighted in a new report titled ‘Winning in the AI Era: The New Playbook for Indian Banks,’ a collaborative effort by Boston Consulting Group (BCG), FICCI, and the Indian Banks’ Association (IBA).

Key GenAI Adoption Projections

• GenAI use cases under implementation stood at just 10% in 2024.
• This share is projected to rise to 44% in 2025.
• By 2026, the report anticipates a significant jump to 86% adoption.

Successfully scaling GenAI across the banking sector will demand fundamental shifts in operating models, talent development, infrastructure, and governance frameworks.

GenAI’s Role in India’s Economic Vision

The banking sector’s robust credit growth is crucial for India’s ambitious goal of becoming a $30 trillion economy by 2047, which requires approximately $45 trillion in banking assets.

Lenders must maintain a 3.5-4 percentage point outperformance over nominal GDP to achieve this target.

Addressing Credit Affordability Challenges

A significant challenge for Indian banks is the high cost of serving borrowers, particularly for small-ticket retail credit, where operating and collection expenses constitute 40-50% of the total cost.

• AI-enabled lending journeys can automate document processing.
• They can streamline underwriting procedures.
• AI can also enhance efficiency in collections, thereby mitigating these high costs.

The Promise of Agentic AI

Agentic AI is identified as a transformative tool capable of handling complex and unstructured tasks, allowing employees to concentrate on higher-value decisions and customer relationships.

Despite a decade of digitization and increased technology investments, the benefits have not translated into proportional productivity gains, with cost-to-income ratios remaining elevated.

Navigating Implementation Hurdles

Broader AI deployment faces several significant barriers within the Indian banking sector.

• Data and infrastructure readiness remain key concerns.
• Shortages in skilled talent pose a considerable challenge.
• Regulatory and governance issues require clear frameworks.
• Uncertainties regarding return on investment (ROI) also hinder progress.

Banks must also enhance their capabilities in managing evolving risks such as fraud, cybersecurity, operational resilience, geopolitical shocks, and climate risks.

Prolonged geopolitical stress could lead to a 1.5-2 times increase in MSME slippage rates, underscoring the urgency of risk management.

Ruchin Goyal, Managing Director and Senior Partner at BCG, underscored AI’s immense potential to revolutionize processes, reduce credit operating costs, boost productivity, and facilitate faster, more accurate decision-making.