From Chatbot To Agent: Designing Agentic AI For Autonomous Customer Journeys In Digital Commerce

Abstract

The paper will present the development of agentic AI systems in digital commerce that began as the traditional chatbots. The suggested framework has the capability of autonomous, adaptive, and emotionally intelligent customer engagement through the integration of large language models (LLMs), multi-agent planning, perception layers, and API orchestration. Their use cases can be found in product discovery, checkout optimization, B2B procurement, post-sale support. According to the study, such systems can decrease Tier 1 support by more than 60 percent and increase the speed of conversions as well as customer satisfaction. Results present business results, ethical factors, and design arrangements of a system level. This piece of work provides a basis to the scale, self-learning agents that writes a novel that will use to change how enterprises relate to users on digital touchpoints.