Agentic Commerce Applications: How Autonomous AI Is Redefining the Retail & E-Commerce Industry

Abstract

Retail and e-commerce have steadily evolved from manual operations and rule-based automation to data-driven analytics and, more recently, generative AI systems that assist human decision-making. The next inflection point in this trajectory is agentic artificial intelligence—systems that can interpret goals, plan multi-step actions, coordinate with other agents, and autonomously execute commercial workflows within defined constraints. This paper introduces the concept of agentic commerce, where autonomous AI agents move beyond recommendation and insight generation to actively manage end-to-end retail processes across customer experience, merchandising, operations, and governance.Drawing on recent advances in large language models, multimodal reasoning, and enterprise AI architectures, the paper synthesizes academic literature and industry practices to propose a structured framework for deploying agentic systems in modern retail ecosystems. We examine how agentic capabilities enable continuous demand sensing, dynamic assortment and pricing decisions, conversational and anticipatory shopping experiences, and real-time operational orchestration across omnichannel environments. Beyond technical architecture, the paper addresses organizational, ethical, and governance considerations required to safely operationalize autonomy at scale.By distinguishing assistive AI from truly agentic systems and outlining progressive levels of autonomy in retail decision-making, this work provides both researchers and practitioners with a foundation for understanding how autonomous AI reshapes value creation, competitive advantage, and human roles in digital commerce. The paper concludes by identifying open research challenges and future directions for responsible adoption of agentic commerce in high-frequency retail environments.