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A. Angelin Stefi is affiliated with the Department of Electrical and Electronics Engineering at Meenakshi Sundararajan Engineering College, Chennai, Tamil Nadu, India. Her academic interests include electrical and electronics engineering and emerging intelligent technologies. She contributes to the exploration of Agentic AI applications in intelligent shopping and consumer behaviour analysis.
The swift expansion of e-commerce has altered consumer shopping habits, generating a need for sophisticated systems that can comprehend customer inclinations, buying behaviours, online activities, and decision-making processes. Agentic Artificial Intelligence (Agentic AI) offers a sophisticated method by allowing intelligent agents to observe consumer engagements, evaluate behavioural trends, deduce preferences, and deliver tailored shopping support. Agentic systems, in contrast to traditional recommendation systems, possess the capability to dynamically orchestrate product exploration, tailored suggestions, pricing evaluations, review assessments, shopping support, and post-purchase assistance. This chapter explores the utilisation of Agentic AI in intelligent shopping and the analysis of consumer behaviour, emphasising customer profiling, behavioural forecasting, tailored recommendations, conversational commerce, sentiment evaluation, purchase-intent forecasting, and enhancement of customer experience. It also examines multi-agent frameworks that encompass customer, suggestion, product, price, and shopping-assistant agents. Privacy, cybersecurity, equity, transparency, and human supervision are deemed crucial for reliable intelligent buying. Evaluation methodologies and novel research trajectories, encompassing multimodal agents, federated personalisation, digital twins, and autonomous shopping ecosystems, are likewise discussed.