Retailer information sharing with upstream AI-enabled quality control

Demand uncertainty hinders upstream investment in AI-enabled quality control technologies that could mitigate yield uncertainty, as low demand makes AI investment unprofitable while high demand drives substantial returns. Retailers, closer to consumers, often have detailed demand information inaccessible to manufacturers. This study investigates the interplay of upstream AI investment and downstream information sharing, showing that information sharing can incentivize manufacturers to adopt AI technologies to address yield uncertainty. Interestingly, despite high AI investment costs suppressing sales volume, manufacturers can still benefit from the adoption of AI technologies, as the amplified information effect can offset potential sales losses. Furthermore, retailers are incentivized to voluntarily disclose private demand signals when the manufacturer’s technology level is low and AI investment costs are high or moderate, as such disclosure encourages AI adoption and ultimately benefits the retailer. This study is the first to propose that uncertainty over upstream AI adoption can serve as a strategic incentive for downstream information disclosure. In addition, it finds that a social planner aiming to maximise social welfare favours information sharing more strongly than retailers. Introducing a proper information fee can realign incentives and lead to mutually beneficial outcomes for both firms.