Banks move from AI that knows users to AI that acts

Banks are poised to transition from AI systems that merely know their customers to AI systems that take action based on deep customer insights. This next wave of disruption could fundamentally reshape the banking landscape, driven by the vast troves of transaction data amassed by global and regional banks alike.

At the Global Fintech Fest 2026 in Mumbai, Amitabh Chaudhry, MD & CEO of India's Axis Bank, presented the bank's ambitious plans to leverage AI to deliver highly personalized banking experiences. With Axis processing an astounding 3,500 UPI transactions per second and holding data on 45 crore Indians, Chaudhry envisions a future where AI understands the context of every transaction, identifies unmet needs, and proactively surfaces relevant financial products or services.

However, Chaudhry warns that the true disruption may extend beyond personalization. As banks with larger customer bases and deeper transaction histories gain a significant advantage in building these AI systems, the competitive gap between large and small banks could widen. Smaller banks may struggle to match the data scale and market reach of industry leaders, potentially solidifying the divide.

On the global stage, J.P. Morgan is taking a step further, with AI moving from experimental to operational across the bank. Christine Tan, Head of Financial Institutions Group Sales, Asia Pacific, Payments, highlighted use cases spanning trade, customer service, fraud, and regulatory compliance. In trade, AI is analyzing documents to detect potential trade-based money laundering, cutting man-hours from nine to under one hour.

J.P. Morgan is also deploying agentic AI in customer service, with agents handling translation, transcription, information sourcing, and response generation during customer calls.

Both Chaudhry and Tan emphasize the critical role of governance and guardrails as banks move towards more autonomous AI systems. Tan notes that regulators worldwide are developing policies and frameworks to oversee AI, while Chaudhry stresses the importance of robust governance within Axis Bank. He warns that failures in AI-driven customer journeys could lead to sudden regulatory interventions, potentially halting further adoption of the technology.

In summary, the convergence of India's data-rich financial ecosystem and global AI advancements suggests that the next phase of banking's AI transformation will involve intelligence permeating every stage of the financial journey – from understanding customers to recommending products to executing transactions and monitoring outcomes. Success hinges on not only building sophisticated AI systems but also establishing robust governance structures to ensure these technologies operate safely and responsibly.