Abstract:
This study examines the role of AI-enabled e-business tools in transforming customer engagement within Pakistan’s fast-fashion e-retail sector. Grounded in the Social Exchange Theory, the research investigates the direct effect of AI-enabled tools on customer engagement, the mediating role of perceived personalization, and the moderating influence of customer trust in AI. A quantitative, positivist research philosophy with a causal and cross-sectional design was adopted. Primary data were collected through a structured questionnaire from 284 consumers who had experience purchasing from fast-fashion e-retail platforms in Pakistan. The collected data were analyzed using reliability testing, descriptive statistics, and regression-based hypothesis testing. The findings reveal that AI-enabled e-business tools significantly enhance perceived personalization and customer engagement. Perceived personalization was found to mediate the relationship between AI-enabled tools and customer engagement, indicating that customers are more likely to interact with online retailers when they perceive services and recommendations as tailored to their individual preferences. Moreover, customer trust in AI strengthened the positive relationship between perceived personalization and engagement, highlighting the importance of transparency, reliability, and data security in AI-driven retail environments. The study contributes to the existing literature by integrating AI-enabled e-business tools, perceived personalization, customer engagement, and trust in AI into a single framework within the context of a developing economy. It also extends the application of Social Exchange Theory to AI-powered digital retailing. Practically, the findings provide valuable insights for managers and marketers in Pakistan’s fast-fashion industry, emphasizing the need to invest in trustworthy and personalized AI solutions to enhance customer relationships, increase engagement, and achieve sustainable competitive advantage.
