On-Demand versus Subscription: The Optimal Pricing Strategies for Artificial Intelligence Generated Content Service Operations

Artificial intelligence (AI) can be used to create high-quality materials (e.g., digital designs). This AI-generated content (AIGC) can now be created via services (e.g., ChatGPT) offered by AIGC firms (e.g., OpenAI). To commercialise their services, AIGC firms commonly charge clients through two pricing schemes, including subscription and on-demand pricing schemes. However, there is growing consumer concern about the potential exposure of private information. Motivated by real-world AIGC service operations, we analyse the optimal pricing strategies of an AIGC firm in the presence of consumers’ privacy concerns. We find that the optimal pricing scheme is driven by the usage value of AIGC services and consumers’ privacy concern level. Specifically, the AIGC firm prefers the on-demand pricing scheme when either (i) usage value is significantly high or (ii) usage value is moderate and consumers’ privacy concern level is low. Otherwise, the AIGC firm prefers the subscription pricing scheme. We also explore the government’s preference and find that win–win situations can be achieved for the government and the AIGC firm. However, conflict may arise when usage value and consumers’ privacy concern level are both moderate. Our major findings remain robust when considering consumers’ learning ability.