AI Agents in Payments: Applications, Risks and Regulations

Abstract

The integration of artificial intelligence (AI) agents into payment systems signals a profound shift in the architecture of financial transactions. Building on advances in large language models and autonomous systems, “agentic payments” refer to transactions initiated and completed by AI agents without direct human intervention. This article provides a conceptual and technical analysis of agent-enabled payment systems, examining their operational logic, defining features and emerging use cases across retail, e-commerce and decentralised finance. It distinguishes agentic payments from traditional automated systems by emphasising autonomy, contextual reasoning and adaptability. The article further identifies and categorises a range of technical, legal and societal risks, including cybersecurity vulnerabilities, liability gaps, regulatory non-compliance, and potential economic disruption. Through case studies and architectural illustrations, it highlights both the innovation potential and governance challenges posed by agentic systems. It argues that current regulatory frameworks-designed for human-intermediated payments-are ill-equipped to address the dynamic and decentralised nature of agent-led transactions. The article concludes by proposing a multi-layered governance framework combining core regulatory requirements with supporting ecosystem measures to ensure accountability, security, and transparency in the age of autonomous financial agency.