AI technology has become a key means to improve product quality information disclosure, alleviating information asymmetry in supply chains. This study investigates a two-echelon supply chain in which a single supplier interacts with two competing retailers that are differentiated in terms of product quality. Four AI adoption strategies are considered, including non-adoption of AI by both retailers (NN), AI adoption only by the high-quality retailer (AN), AI adoption only by the low-quality retailer (NA), and AI adoption by both retailers (AA). We further analyze how key factors, such as quality competition intensity, AI efficiency coefficient, AI investment level and information asymmetry degree, affect supply chain decisions and optimal AI adoption strategies of all supply chain members. The results reveal that the high-quality retailer always benefits from AI adoption and gains the highest price premium under the AA strategy. In contrast, the low-quality retailer can achieve positive profits only when the fixed cost of AI platforms is below a critical threshold. The supplier achieves optimal profits under the AA strategy with moderate competition and under the NA strategy with intense competition. Core parameters such as the AI efficiency coefficient and information asymmetry jointly influence corporate AI adoption decisions, and the NN strategy is preferred amid severe information asymmetry.