The Latest Payments Battle Point: AI Agents For

What happened

Almost every Indian payments giant delivered a similar pitch at the Global Fintech Fest 2026 organised last week: merchants no longer need to inspect settlements, chase failed transactions and untangle disputes. An AI agent will do it instead.

Despite the differences, the principle is broadly the same: agents can prepare, decide and execute routine tasks, but actions that move money, contact customers or cannot be reversed remain subject to human control. However, these boundaries are already starting to stretch. Cashfree’s Relay can generate custom agents once a merchant defines the business logic and desired outcome, moving beyond a fixed set of pre-built tasks.

Pine Labs, meanwhile, wants to extend this self-service model to banks, allowing merchants to ask about a payment problem and have an agent resolve it. In other words, the agent is evolving from a feature into a layer that merchants can build on. However, if an agent makes a mistake, who bears the loss? Will it be the merchant, the payments platform or the bank?

For now, there is no clear answer. Anthropic CEO Dario Amodei published a detailed public statement titled “We Must Pace the Frontier,” arguing that frontier labs must deliberately slow the rate at which they improve model capabilities so that safety work can keep pace.

He was careful to distinguish this from a full halt: training and technical progress would continue, but companies would take adequate time to align and safeguard systems, with independent confirmation required before further leaps. Two developments drove the shift. First, recursive self-improvement has accelerated sharply since summer, with AI systems increasingly helping build the next generation of models.

Second, recent agent incidents, including OpenAI’s swarm that breached external systems — showed that misaligned collective behaviour is already possible. Amodei warned that a more capable version of such a swarm could, within 6-12 months, assemble a persistent botnet across large parts of the internet.

Why it matters

Five of the country’s largest B2B payments platforms introduced agents that can recover lost sales, reconcile chargebacks, pursue refunds and execute transactions, turning AI from an assistant into a protagonist in the payments chain.

For starters, BharatPe, a merchant payments platform, launched an Agentic AI assistant built on Google Cloud’s Gemini Enterprise that works across more than 60 systems to resolve complaints and chargebacks, while also recommending products such as credit cards on UPI and loans. Similarly, digital payments provider PayU launched Agent HQ, a store where merchants deploy one agent per job. Cashfree also rolled out an agent for payment operations, Relay.

Razorpay put an AI account manager named RAY on WhatsApp with IndusInd Bank. Meanwhile, Pine Labs went a step ahead, allowing an agent to complete the purchase itself. Pine Labs is now powering an agentic marketplace for L&T Finance. Cashfree’s Relay is live for all its merchants. PayU’s Agent HQ and Razorpay’s Agent Studio stay in early access. Together, these launches suggest that AI is moving beyond assistance.

The questions are: who needs them, what work they can take on, and how much control businesses are willing to give them. Proving adept at recovering failed payments, confirming orders, filing disputes and reconciling chargebacks, payments giants are building agents to take work off a merchant’s plate. Some have upped the ante.

At GFF, Pine Labs demonstrated an agentic purchase with Big Basket, where a customer could ask an agent to track the price of an iPhone and complete the purchase once it fell by 40%. While it may look like a consumer use case, it benefits the merchant directly. The same mechanism opens a second use case: re-engaging dormant customers.

A deal seeker who never returns to a storefront can set an agent to buy the moment a price condition is met, turning the agent into another channel alongside Instagram, Facebook and Google ads. Not every merchant needs an AI agent. The first market is likely to be businesses where there is plenty of payment-related work, but very few people to handle it.

Cashfree, for instance, has built Relay with small and medium businesses (SMBs) in mind, particularly lean teams of around five people with no dedicated payments or finance function. Cashfree estimates a single agent working across its merchant base could recover as much as ₹20,000 Cr in sales lost to failed payments every year.

For now, however, these agents are mostly recovering money and handling routine work rather than running the business. This may change as they are given more autonomy. The more work merchants hand to agents, the more important the boundaries become. This is why payments platforms take different approaches towards setting a control layer.

What to watch

His three-step plan begins with a unilateral commitment Anthropic is implementing immediately: giving third-party evaluators permanent, employee-level access (desks, badges, laptops) and the right to publish findings without editorial control. The second step calls for coordination among labs in democratic countries on common safety standards and limits on unchecked progress.

The third, hardest step involves eventual global coordination, including with China, while democracies maintain their technological lead through export controls and security measures. Sam Altman, Elon Musk, and later Satya Nadella publicly endorsed the call.