AI-Powered Customer Service in Online Retail: Product-Type Differences, Information Asymmetry, and Seller Interventions

The rapid integration of AI customer service in e-commerce raises an important managerial question: Can AI effectively reduce product-related information asymmetry and improve sales performance across different product types? While prior research highlights both the uncertainty-reducing benefits of information and the risks of algorithm aversion, little is known about how AI customer service performs under varying levels of product uncertainty and information asymmetry. Using a difference-in-differences design with fixed effects across time, products, shops, and categories, we examine the impact of replacing customer service with AI on sales outcomes, distinguishing between search and experience goods. We further test how the depth and breadth of product information moderate these effects. Our findings indicate that AI customer service reduces sales for experience goods but not for search goods, unless accompanied by sufficient informational depth and breadth. We argue that this effect arises because AI technically inherits and amplifies the information asymmetry inherent in experience products, while greater informational depth and breadth of product information can mitigate this amplified asymmetry. Additionally, we find that this mitigating effect is more pronounced among products with high return rate. These findings clarify when AI-generated information mitigates product uncertainty and when it exacerbates it. Our results provide actionable guidance for firms seeking to deploy AI strategically in digital commerce environments.