Indian banks may be approaching a major shift in the way they operate as artificial intelligence moves beyond basic automation and begins handling increasingly complex tasks. A new report by the Federation of Indian Chambers of Commerce and Industry (FICCI), Indian Banks’ Association (IBA) and Boston Consulting Group (BCG) says banks will need to fundamentally rethink their operating models to unlock the next major productivity gains from AI.
According to the report, simply converting existing processes into digital formats will not be enough. The bigger opportunity lies in redesigning how work is performed, allowing AI systems to take over repetitive activities while employees spend more time on decisions that require judgement, expertise and greater value creation.
Despite years of investment in digital infrastructure, several banking processes continue to involve major human intervention and paperwork.
The report highlighted the complexity involved in a typical loan journey. A single loan process can require more than 25 documents, along with 50 or more manual data-entry fields. In some cases, customers may also have to pass through six to eight levels of manual review before the process is completed.
Customer service is another area where banks continue to dedicate large numbers of employees to repetitive interactions. Routine servicing requirements can also account for 10-20 per cent of branch time, indicating that considerable employee capacity remains tied up in activities that could potentially be automated.
The report argues that these processes present an opportunity to use AI not merely as a digital layer, but as a tool to fundamentally restructure banking operations.
From ‘Coding The Known’ To Agentic AI
The report described the first stage of banking digitisation as “coding the known”. This approach involved automating clearly defined, rule-based processes where the information and possible outcomes were structured in advance.
Such automation has helped banks make major advances in areas including digital payments and identity verification. However, conventional systems remain dependent on rules and scenarios that developers have explicitly programmed.
Agentic AI could change that model.
AI agents can work with different forms of unstructured information, including voice recordings, documents, images and free-form text. Instead of following only predetermined instructions, these systems can interpret a user’s intent and carry out tasks across multiple possible scenarios.
This could allow banks to automate processes that were previously considered too complicated for traditional rule-based systems.
Conversational Banking Could Become The Next Frontier
The report also identified conversational banking as a major emerging opportunity. Rather than navigating multiple menus and screens within banking applications, customers could increasingly interact with banks through voice and chat-based AI agents using natural language.
Such systems could potentially understand what a customer wants, provide relevant guidance and execute transactions without requiring the customer to follow lengthy, predefined journeys.
This would represent a shift from the conventional app-and-menu model towards banking services that are more personalised and continuously available. The implications could extend beyond customer service. AI-driven interactions could potentially combine understanding, advice and transaction execution within a single conversation, creating a more seamless banking experience.
Banks May Need To Rethink Their Workforce
The transition to agentic AI is unlikely to be limited to technology upgrades. The report said banks will also need to reconsider how their organisations are structured. This could involve flattening organisational hierarchies, reskilling employees and giving teams greater authority to make decisions.
As repetitive work becomes increasingly automated, the role of employees could shift towards activities requiring judgement, problem-solving and specialised expertise. Instead of replacing digital processes with AI without changing the underlying structure, banks would need to redesign workflows around what humans and AI systems can each do most effectively.
The report’s central message is therefore not simply that banks should deploy more AI tools, but that they need to rethink the way work itself is organised.
AI Will Also Change How Banks Manage Risk
Greater use of AI will bring another challenge: risk management will need to evolve alongside the technology.
The report said banks will need to move beyond traditional credit-risk frameworks and develop a more integrated approach covering fraud, operational resilience, cybersecurity and climate-related risks.
AI-enabled systems could help institutions assess how developments in one area might affect other parts of the organisation. They could also support faster responses to emerging threats, particularly as financial institutions increasingly face risks that can develop at machine speed.
For banks, this means AI adoption cannot be separated from governance and risk controls. The technology could improve the speed and scale of decision-making, but institutions will need appropriate safeguards to manage the risks associated with increasingly autonomous systems.
The report suggests that the next phase of banking transformation will therefore depend on more than digitising existing processes. Banks that redesign operations, rethink workforce structures and strengthen risk frameworks could be better positioned to capture the productivity gains promised by agentic AI.