How AI-Generated Summaries of Reviews are Reshaping E-Commerce With Competing Retailers?

With the rapid advancement of generative AI (Gen AI), e-commerce platforms like Amazon and Newegg are adopting AI-generated summaries (AIGS) to synthesize online reviews. We analytically study the transformative impact of AIGS one commerce with competing retailers by examining its two key effects: the convenience effect, which reduces consumers' reading costs to access review information, and the filtering effect, which aids consumers in making more informed purchase decisions. Retailers differ in their market reputation (MR), and not all consumers in the market trust AIGS. Our findings suggest that the convenience effect and the filtering effect influence competition in opposite ways. When consumer trust in AIGS is high, its adoption may intensify price competition. We further show that moderately high consumer trust in AIGS enables its adoption to create an all-win outcome for both the platform and competing retailers. Surprisingly, we find that while high trust in AIGS can reinforce high-MR retailers' advantages (a Matthew effect), the adoption of AIGS under low trust may instead reshape market competition by narrowing these advantages. Interestingly, when AIGS is fully trusted and adoption costs are moderate, it improves social welfare but may lower consumer surplus due to elevated prices.