BFSI Summit 2026: 'Time to implement AI at scale, with clear objectives'

Private bank chiefs say AI adoption must move beyond pilots to large-scale implementation, with a focus on customer experience, productivity, data governance and cybersecurity

Indian banks need to move beyond experimenting with artificial intelligence (AI) and focus on implementing the technology at scale, with clear business objectives, stronger data practices, and safeguards to ensure accountability, private bankers said during the Business Standard BFSI Insight Summit.

 

While banks have kept pace with technological developments, translating AI pilots into measurable business outcomes will require careful selection of use cases, investment in data and cybersecurity, and continued human oversight of decisions.

 

R Subramaniakumar, managing director & chief executive officer (MD & CEO) of RBL Bank, said Indian banks were ahead in identifying AI use cases, but the focus now needed to shift from experimentation to practical deployment, which would bring greater responsibility for banks. “The Reserve Bank of India (RBI) is very clear: you have to move from experimentation to implementation,” he said.

 

 

He also said that Indian banks had identified promising use cases and were not necessarily behind their global peers, but adoption remained at an early stage. Subramaniakumar said that

 

“for AI to be successful, the underlying data has to be quantum-wise, volume-wise, value-wise, and quality-wise far superior”.

 

Voicing a similar opinion, Rajiv Anand, MD & CEO of IndusInd Bank, said that over time, the benefits of AI is expected to be more fully realised. When it comes to the guiding principles for AI adoption, the foremost consideration should be identifying the problem that needs to be solved. Given the significant hype surrounding AI, it is essential to remain focused on its practical applications and business value. 

  

“We have to get out of the mindset of pilots and go to scale execution and for that, we have to think in terms of what are the AI use cases that can be used,” Anand said.

 

He also said that Indian banks should not be worried about if they are lagging or ahead in AI race, as they have demonstrated a fair amount of flexibility to be able to adopt new technologies. “As a banking system, there are various models that are currently playing out. Either they (the models) should change the customer experience or improve productivity. A large part of work in banks is happening in improving productivity,” Anand said.

 

“AI is dramatically changing the way employees are working and how the customers are going to experience banking,” said V Vaidyanathan, MD & CEO, IDFC First Bank.

 

Bankers also said that they could choose between different types of AI models — enterprise-based model as well as specialised models. However, ownership, accountability, and decision-maki­ng would continue to rest with the banks.

 

While banks can deploy AI across different functions, bankers said that its value would depend on identifying the right use cases and integrating the technology into business processes at scale. Anand said AI could help banks gain deeper insights into customers and assess creditworthiness, while enabling them to redesign customer journeys rather than merely automate existing processes.

 

“AI should not be viewed as a technology that can simply be added to an existing process. That is not the right way to approach it. The technology gives us the ability to completely reimagine customer journeys,” Anand said.

 

For instance, a customer could upload documents through WhatsApp for a housing or auto loan, enabling the system to read the information and potentially pre-approve the application. This would change the existing process, in which customers submit physical documents at branches. Banks are also using AI agents and voice-based applications to automate routine work and improve productivity.

 

Banks also needed to ensure that AI systems were transparent and their decisions explainable to regulators and customers. The economic benefits of AI may not necessarily translate into higher profits for lenders. It could improve operational efficiency while allowing customers to benefit through faster loan processing and lower borrowing costs.

 

The bankers also highlighted the need to invest in safeguards alongside AI deployment. Banks must assess business vulnerabilities, establish traceability, and ensure that AI-supported decisions could be audited. Resilience was equally important, particularly if a model failed, became obsolete, or developed a significant problem.

 

Cybersecurity and data governance are emerging as important considerations as banks deploy AI agents that can reason and access multiple sources of information. Banks need controls to prevent unauthorised access to data, while ensuring that the technology does not introduce bias or misinterpret regulatory requirements.

 

On technology spending, Vaidyanathan said banks needed to distinguish between investments in technology and the practices required to use data effectively. “Data practices are extremely important and are just as critical as having a good technology stack,” he said.

 

He estimated that most banks were spending around 10 per cent of their operating expenditure on technology, which he considered a good level of investment. “Almost all banks are investing about 10 per cent of their operating expenditure on technology. It is a good number and it gives comfort that banks are still investing for the future,” Vaidyanathan added.

 

Subramaniakumar also said that investment was also required in cyber-resilience, and data-layer security, and that the systems needed to deploy AI safely. The case for additional spending would depend on whether experimentation produced demonstrable business outcomes.

 

Banks are also exploring AI for customer grievance redress. Sentiment analysis can help categorise complaints received through social media, telephone calls, email, and other digital channels. AI agents can connect information across complaints and identify patterns, enabling lenders to take a more proactive approach to resolving customer issues.

 

The bankers attributed growing inte­rest among foreign investors in Indian banks to India’s growth prospects, demographic opportunity, formalisation of credit, and infrastructure development. Additionally, governance, market liquidity, and talent availability, among others, are also boosting investor confidence.

 

Even as banks discuss moving from AI experimentation to full implementation, they also believe that the lenders must establish clear AI policies and security protocols. “Every bank has to have a policy on AI because it is a fast-moving technology that requires strict security protocols and guardrails,” Vaidyanathan said.