The Future of E Commerce with Agentic AI: Personalized, Task-Oriented AI for a smarter shopping experience

Agrawal, Keshav (2025) The Future of E Commerce with Agentic AI: Personalized, Task-Oriented AI for a smarter shopping experience. Open Access Research Journal of Engineering and Technology, 8 (2). pp. 103-113. ISSN 2783-0128

Agentic AI represents a paradigm shift in e-commerce, moving from basic recommendation algorithms to intelligent, task-oriented assistants with deep understanding of specific domains. Unlike traditional systems that rely on statistical correlations, agentic AI employs cognitive architectures capable of understanding contextual factors and long-term customer goals. The emergence of specialized agents focused on particular life domains - parenting, meal planning, home maintenance - enables personalized shopping experiences that adapt to individual lifestyles. These agents utilize sophisticated learning mechanisms to develop accurate customer models, incorporating both explicit preferences and observed behaviors while recognizing context-dependent variations. At the ecosystem's center, a Master Agent orchestrates multiple specialized agents, ensuring cohesive interactions across domains. While this architecture promises significant benefits in personalization and assistance, it also raises important considerations regarding privacy, algorithmic bias, consumer autonomy, and regulatory frameworks. Balancing convenience with user control becomes essential in creating systems that enhance rather than diminish customer agency in increasingly mediated shopping environments.