7 in 10 Indian Banks Run AI in Production; Security and Control, Not ROI, Is Now the Main Brake on Scale: Zeta Survey

7 in 10 Indian Banks Run AI in Production; Security and Control, Not ROI, Is Now the Main Brake on Scale: Zeta Survey

Survey of 40 CXOs across 18 leading banks and NBFCs finds AI live in bounded, reviewable use cases, with roughly three-quarters of technology and risk leaders naming security and data privacy as the leading barrier to going further.

Most banks direct less than 10% of new-project technology spend to AI, and four in ten digital leaders cannot yet point to a high-ROI use case, pointing to value that is real but not yet repeatable.

Zeta today announced the findings of its 2026 CXO survey on the state of AI in Indian banking, based on responses from 40 CXOs across 18 leading banks and NBFCs. AI is now in production at most institutions: 70% of CDO respondents place their banks at selective or scaled deployment, including 30% at scaled deployment. Adoption is strongest in bounded, reviewable areas such as customer service, fraud and risk analytics, document processing and software testing. Integration into end-to-end workflows and consequential decisions is at an earlier stage.

The survey points to a clear divide between piloting AI successfully and deploying it repeatably at scale. Banks have proven that AI works in production. What remains harder is reproducing that success across the institution without rebuilding data, integrations and controls for every new use case. The technology estate is more connected than ever, but the capabilities that make it usable by AI, from permissioned data and AI-operational infrastructure to engineering controls, governance and skills, are developing at different speeds.

Investment reflects this. Most institutions surveyed direct less than 10% of new-project technology spend to AI, including some with AI across multiple functions. The survey suggests this is not a lack of conviction: lack of ROI clarity is the lowest-rated barrier, and executive scepticism and employee resistance rank below skills and security. Banks are measured because control, not appetite, sets the pace.

Key findings from the survey

AI is creating meaningful operational impact, but it remains concentrated in structured workflows.

• - 88% of COO respondents identify retail lending as an area where AI is delivering meaningful impact.
• 75% cite customer service.
• 63% each cite CASA and back-office operations.

Banks are confident about data availability; making it usable for AI is the harder problem.

• 80% of CIOs and CTOs describe their data environment as mostly ready for AI at scale.
• 61% point to insufficient labelled or training data.
• 53% to privacy and consent.
• 46% to siloed data.
• 67% are using or piloting AI to enhance or enrich their data.

Technology assets are connected; making them operable by AI is the next step.

• Real-time data platforms and API-first architectures: 79% adoption.
• Core modernisation and cloud: 64%.
• Advanced analytics and MLOps: 43%.

AI has a foothold in software engineering; adoption thins as AI moves from producing to executing.

• 80% report using AI in testing and QA.
• 60% in code generation.
• 40% in code review.
• 30% each in specifications, documentation, deployment, CI/CD, and incident detection.

Banks are preparing to take AI into consequential decisions; governance is developing alongside.

• 60% of CROs identify AI-led credit-risk models, predictive early-warning systems and real-time fraud decisioning as top priorities.
• 60% say Responsible AI frameworks are under development.
• 20% describe model-risk management as very mature.

AI is changing work before it changes workforce size; internal capability-building is catching up.

• Half of operations leaders expect AI-led productivity gains to release capacity for redeployment.
• None expect workforce reductions above 20%.
• Banks are building AI skills faster through specialist hiring (3.33/5) and external partners (3.0/5) than internal development (1.0/5).

From selective production to repeatable scale

Taken together, the findings suggest Indian banking has moved past the challenge of taking AI from experiment to production. Production adoption is real but selective, concentrated where the problem is well understood, outcomes can be reviewed and existing controls contain the consequences of error.

The question now is whether banks can take what works in these settings and reproduce it across the institution without rebuilding the surrounding data, integrations, controls and engineering practices each time. The survey indicates that this depends on two shared foundations rather than more individual deployments: a core that AI can use, with banking meaning and permissions travelling with the data, and a control layer that establishes what AI may access, decide and execute and keeps a record of it.

“Indian banks have shown that AI creates value in production. The next challenge is making that success repeatable, and the survey is clear about what stands in the way: not conviction, but control,” said Sivaram Kowta, President, Zeta India.

About the Survey

Zeta's 2026 CXO survey on AI in Indian banking draws on responses from 40 CXOs across 18 leading banks and NBFCs, including CIOs, CTOs, CDOs, CROs and COOs. It examines AI adoption and the institutional capabilities required to scale it across data and infrastructure, operations and workflows, engineering and SDLC, governance and trust, and workforce and organisation.

About Zeta:

Zeta is a next-gen banking technology company. Its cloud-native and fully API-enabled platform supports card processing, issuing, lending, core banking, fraud management, loyalty programs, digital banking apps, and more. With over 1,700 employees globally, Zeta empowers financial institutions to innovate and rapidly launch compliant financial products. Globally, customers have issued over 25M cards using Zeta’s platform.

Media Contact:
Aafia Feroze | [9902491526](tel:9902491526) | aafiaf@zeta.tech