Agentic Commerce: A Survey of Emerging Landscape

Abstract: The rapid development of artificial intelligence (AI) has moved electronic commerce from using traditional algorithmic recommendations to relying on autonomous agentic systems. In this new approach, referred to as agentic commerce, large language model (LLM)-powered agents are able to independently discover, assess, negotiate, and carry out financial transactions on behalf of human users. The present survey offers a thorough overview of the developing agentic commerce environment. It looks at the basic architecture and the interoperability protocols that allow smooth machine-to-machine transactions, examines the change in the user experience going from manual browsing to intent- driven delegation, and systematically reviews the existing evaluation frameworks, pointing out the gap between shopping scenarios in simulation and actual real-world performance. The study also investigates the security, privacy, and economic issues specific to this system, such as intent misinterpretation, adversarial manipulation of the marketplace, risks associated with dynamic pricing, and the need for dynamic trust governance. Finally, it identifies the major open challenges and the key research areas that are needed if secure, transparent, and user-aligned agentic commerce platforms are to be developed. This work acts as a fundamental reference for researchers, developers, and industry professionals who are dealing with the next generation of automated digital trade.

Keywords: Agentic commerce, LLM agents, Autonomous transactions, E-commerce protocols, AI security and trust, Agent evaluation frameworks