Mastercard’s ‘Agentic Commerce’ is ready for Indian requirements, says Nitendra Rajput

During the India AI Impact Summit 2026, Mastercard introduced its innovative Agentic Commerce framework, which harnesses the power of AI agents. This cutting-edge ecosystem is designed to go beyond mere product suggestions, enabling users to find, negotiate, and finalize transactions autonomously. In a discussion with Business Today, Nitendra Rajput, the Senior Vice President and Head of Mastercard AI Garage, elaborated on how the company has customized its AI solutions to meet the distinct needs of Indian consumers. He highlighted the importance of building foundational trust layers within autonomous systems like Agentic Commerce, especially as the Indian government intensifies its focus on the IndiaAI Mission. Rajput pointed out that for Mastercard, localization is key. He stated, "The initial interaction in the agentic commerce demo asks users to select their preferred language. With advances in technology, the system can manage interactions in several Indian languages, including voice support." The demonstration took place at the Bharat Mandapam exhibition zone, showcasing the system's adherence to Indian regulations, particularly regarding data storage, privacy, and financial compliance. Rajput emphasized, "Mastercard has a longstanding presence in India. We understand the principles of data localization, which are fundamental to the development of agentic commerce." One of the primary concerns surrounding agentic AI is unauthorized spending. Rajput reassured users that Mastercard's ecosystem is built with secure automation and fraud prevention at its core. He explained, "Mastercard Agent Pay integrates tokenization and passkeys, which are essential features of the system. Users must explicitly grant permission for these tokens and passkeys to be utilized." Additionally, he introduced the company’s Decision Intelligence platform, which employs behavioral analysis to identify suspicious activities. Rajput noted, "This platform assesses historical consumer patterns. If a transaction deviates from typical behavior, it flags it for review." Utilizing recurrent neural network (RNN) models, the system analyzes user behavior, allowing it to detect anomalies, such as unusual gambling transactions. It also employs graph-based technology to track connections across the network, aiding in the identification of synthetic identities and complex fraud schemes. While Agentic AI has traditionally been confined to enterprise applications, it is now capable of autonomously managing real financial transactions. When discussing the implications for employment in the fintech sector, Rajput acknowledged the potential for job displacement but stressed that this transition would be more about evolving roles than outright job losses.