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September 5, 2026
The Lede
India’s payments stack enters a new AI era
AI is moving from the chatbot to the checkout stage for payment companies
India’s payments industry is entering an AI-led phase, with companies increasingly embedding artificial intelligence into the plumbing of transactions rather than treating it as a side feature.
- From improving payment success rates and detecting fraud to automating merchant operations, AI is being pushed deeper into the payments stack.
Razorpay, for instance, has built a payments foundation model trained on nearly four billion payments and around three trillion data points.
- The company says early tests have improved payment success rates, fraud detection and dispute identification.
Cashfree is taking a different route, using its AI super-agent Relay to automate repetitive payment operations for merchants, including failed payments, abandoned carts and disputes.
The next frontier: AI that can transact
The ambition is now extending beyond making payments work better. Payment companies want to become the infrastructure through which AI agents eventually transact.
- Cashfree, Razorpay, PhonePe, Paytm and Zoho Payments are among those experimenting with AI-led commerce, integrations and payment operations.
Some are working on enabling payments inside AI interfaces, while others are allowing merchants and developers to use natural-language instructions or AI coding tools to set up and manage payment functions.
- This could fundamentally change how consumers shop, moving from manually browsing, selecting and paying to asking an AI agent to complete the entire transaction.
But AI comes with a bill, and a burden of trust
The AI push is not cheap. GPUs, cloud infrastructure, model training and real-time inference are adding a new cost layer for payment companies.
- The eventual test will be whether these investments translate into better conversion, lower fraud, reduced costs or significant operational efficiencies.
Unlike many other technology businesses, payments leave little room for experimentation gone wrong.
- With money, sensitive data and regulation involved, companies must ensure that AI improves the ecosystem without weakening its safeguards.
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