The Challenge and Optimization of Personalized Pricing Driven by Generative AI Taking Ctrip as an Example

With the rise of generative artificial intelligence, its application in the business field is expanding, particularly in personalized pricing strategies for online travel platforms (OTAs) like Ctrip. This paper focuses on the systematic optimization of generative artificial intelligence for online travel platforms (OTAs) like Ctrip, examining its technical realization, commercial value and ethical challenges. This paper also discusses the challenges and future trends of personalized pricing in the online travel platform industry taking Ctrip as an example, and summarizes the problems encountered and future prospects after the application of artificial intelligence in the business field. The study reveals that Ctrip builds a multimodal pricing engine based on generative AI to generate the optimal pricing mix by integrating user behavior data, risk appetite, real-time supply and demand information and external environment variables. Therefore, the application of generative AI in the business field can greatly improve customer satisfaction and order conversion rate.