According to reports from Business Standard, PayU has outlined a comprehensive AI strategy across four key focus areas. The company's approach encompasses helping consumers and merchants navigate the shift to agentic commerce rails, democratising access to AI and generative AI technologies for banking and merchant customers, building AI-native products to address emerging fraud patterns and consumer behavior trends, and improving efficiency across all organisational functions including product, engineering, operations, legal, and financial operations.
As reported by Business Standard, PayU is developing systems designed for users who provide explicit consent, with all products and processes built around this framework. The company is currently conducting pilots for agentic flows that are one-on-one and tightly coupled, addressing critical questions of trust, traceability, accountability, audits, and interoperable protocols. According to PayU's Chief Product Officer Manas Mishra, the transition from agentic commerce to agentic payments presents challenges where human intervention is necessary to complete payments, requiring mandate execution capabilities across different merchants.
According to Business Standard, PayU is building what it describes as one of its large bets - an agent marketplace for merchants. This platform will enable merchants to download specific agents for various use cases, including productivity agents for automating reconciliation and gateway integration, and recommendation agents to power commerce. The company believes value will primarily come from merchants rather than users, who may view agentic as a convenience play rather than a premium service justifying additional costs.
As reported by Business Standard, different functions within PayU track various AI productivity metrics depending on their specific outputs. The company is automating parts of the product development lifecycle, from design and requirements documentation through code review and quality control, with some processes now completing within few hours to a few days compared to traditional timelines. Additionally, metrics include merchant onboarding turnaround times and query resolution speeds, reflecting the company's focus on operational efficiency improvements.
The AI agent sector faces escalating security challenges, with vulnerabilities affecting popular frameworks like Langflow, LangGraph, and LangChain being actively exploited, impacting thousands of servers. Microsoft has detailed the 'AutoJack' exploit chain, which targets AI agents through web browsing, highlighting the urgent need for robust security measures. In response to these growing risks, Google DeepMind is adopting a strategy that treats autonomous AI agents as potential insider threats, representing a significant shift from traditional software security approaches. This security focus aligns with PayU's emphasis on building trustworthy agentic systems that address critical questions of traceability and accountability.
