Benefits versus Privacy Costs in AI-Driven Personalised Advertising: Examining Purchase Intention among Smartphone Users

Abstract

AI-driven personalised advertising allows businesses to deliver advertisements based on consumers’ interests, online activities, and preferences. Although such advertisements may help consumers find suitable products, they may also create concerns about the collection and use of personal information. This study examines the effect of perceived usefulness and privacy concerns on purchase intention among smartphone users. The study draws on Privacy Calculus Theory to explain how consumers balance the benefits of personalised advertising against its privacy-related costs. A quantitative and descriptive research design was adopted. Data were collected from adult smartphone users residing in the Union Territory of Jammu and Kashmir through random digit dialing. A total of 496 usable responses were analysed using structural equation modelling. The findings show that perceived usefulness has a positive and significant effect on purchase intention, whereas privacy concerns have a negative and significant effect. The results suggest that consumers are more likely to consider purchasing when personalised advertisements are useful. Still, their intention may decline when they are concerned about how their personal information is collected and used. The study highlights the need for advertisers to make personalised advertisements helpful while maintaining transparent and responsible data practices.