Digital platforms such as Amazon and Alibaba orchestrate e-commerce transactions between merchants and consumers, thereby amassing a vast reservoir of real-time granular transaction data. Analyzing this data with advanced AI technology, these platforms can discern unmet customer demand and provide this market intelligence to merchants. Such a platform strategy has the potential to benefit all parties involved—consumers can purchase desired products that were previously unavailable; merchants can increase revenue by offering desired items; and the platform can take a larger commission from the increase in transactions. Despite the growing traction this strategy has gained in practice, little academic research has explored the performance impacts and the processes at play. As an initial attempt to fill this research gap, we provide empirical evidence based on a field experiment involving 146,892 merchants that was conducted at one of the leading digital platforms in the world. Our findings shed new light on the role of AI in improving platform design and shaping industry evolution.