Emkay Research suggests that while AI is a major focus for Indian fintechs, meaningful revenue from these products is unlikely before FY28. Current initiatives are primarily targeting operational cost reductions rather than direct monetisation. Investors should track operational efficiency gains in FY27 rather than anticipating immediate AI-driven income.
Artificial intelligence has become the central theme in the Indian fintech industry, yet a recent report from Emkay Research suggests that the financial payoff will take time to materialise. While 32% of sessions at the Global Fintech Fest 2026 were dedicated to AI or agentic AI, the brokerage found that none of the companies covered have reported revenue from their new AI offerings. Emkay expects that significant, direct AI-driven revenue is unlikely to emerge until FY28, placing the industry in a phase where product launches signal strategic intent rather than near-term earnings growth.
Operational Efficiency Over Direct Revenue
The immediate impact of AI is focused on internal operations rather than creating new sales channels. Companies are deploying AI to lower servicing costs, enhance customer support systems, and accelerate technology integration. These moves are aimed at making existing business models leaner and faster. While these improvements are positive for profitability, they do not necessarily translate into immediate revenue growth. For investors, the distinction is important. The current focus on operational efficiency may lead to better profit margins over time, but the promise of AI as a direct, high-growth revenue stream remains a longer-term expectation.
Sector Innovation and Regulatory Reality
Major players are actively building AI-powered platforms. Paytm has showcased tools for banks and insurers aimed at fraud assessment and marketing, while Razorpay has demonstrated an AI account manager supported by proprietary data. Other firms, including Pine Labs and PhonePe, are working on AI-powered search, transaction insights, and agentic payments—technology that can execute transactions with minimal human intervention.
However, the gap between technical capability and market deployment remains substantial. Many agentic payment systems still require human checkpoints for verification, which limits their autonomy. Furthermore, while the Unified Lending Interface continues to expand with over 64 lenders and 136 data services, the regulatory framework for fully autonomous, small-scale payments is still evolving. The lack of a finalised Unified Agent Protocol means that companies are currently operating within a system where human oversight is mandatory, which creates an execution hurdle for fully automated products.
Investor Monitorables for FY27
For the current fiscal year and FY27, the market narrative is shifting from AI hype to execution. Investors may find more value in tracking how well companies use AI to optimise their existing cost structures and customer service functions. The primary monitorables will be whether these technological investments actually lead to lower operational expenses or improved user retention, rather than watching for immediate revenue spikes from AI products. As the sector navigates regulatory requirements and refines these tools, the ability of companies to convert proprietary data into meaningful cost advantages will likely determine which firms benefit most from this technological transition.