Rohit Yadav
The Integration of AI With IoT for Personalized In-Store Experiences in the Experience Economy
Yadav, Rohit; Huzooree, Geshwaree; Yadav, Mohit
Authors
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 |
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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 |
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