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The Integration of AI With IoT for Personalized In-Store Experiences in the Experience Economy

Yadav, Rohit; Huzooree, Geshwaree; Yadav, Mohit

Authors

Rohit Yadav

Mohit Yadav



Contributors

Rhytheema Dulloo
Editor

Anand Kurian
Editor

Minja Bolesnikov
Editor

Ilse Struweg
Editor

Kaliyan Mathiyazhagan
Editor

Abstract

This chapter explores the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in retail, collectively referred to as AIoT, and its transformative impact on in-store customer experiences. By combining AI's ability to personalize customer interactions with IoT's capacity to connect and optimize physical environments, retailers can enhance engagement, improve operational efficiency, and create seamless, data-driven shopping experiences. The chapter examines AIoT's role in driving personalized retail experiences, its impact on customer behavior, and the technological innovations shaping future trends. It also discusses challenges and ethical considerations, including data privacy, cybersecurity, and algorithmic fairness. Ultimately, AIoT is positioned to revolutionize retail in the Experience Economy, offering significant opportunities for innovation and competitive advantage. The chapter concludes with recommendations for retailers to leverage AIoT responsibly while fostering customer trust.

Citation

Yadav, R., Huzooree, G., & Yadav, M. (2025). The Integration of AI With IoT for Personalized In-Store Experiences in the Experience Economy. In R. Dulloo, A. Kurian, M. Bolesnikov, I. Struweg, & K. Mathiyazhagan (Eds.), Leveraging AI-Powered Marketing in the Experience-Driven Economy (259-278). IGI Global. https://doi.org/10.4018/979-8-3693-9561-5.ch009

Online Publication Date Apr 18, 2025
Publication Date 2025
Deposit Date Apr 22, 2025
Publisher IGI Global
Pages 259-278
Book Title Leveraging AI-Powered Marketing in the Experience-Driven Economy
Chapter Number 9
ISBN 9798369395615, 9798369395622
DOI https://doi.org/10.4018/979-8-3693-9561-5.ch009
Public URL http://researchrepository.napier.ac.uk/Output/4242643