The ride-hailing platform Cao Cao Travel recently announced the establishment of an independent AI business unit, fully accelerating the implementation of the company's AI strategy, and officially launched the position of "Chief AI Officer" on the recruitment platform, offering a comprehensive compensation package exceeding ten million yuan.

This move marks that Cao Cao Travel is trying to break away from the traditional positioning of ride-hailing platforms and accelerate the transformation into intelligent transportation service infrastructure in the AI era. It is reported that the Chief AI Officer will directly participate in the formulation of the company's AI transformation strategy and ecosystem collaboration, and be responsible for building a high-level AI algorithm and engineering team.

This strategic move is closely related to the breakthroughs in its autonomous driving business. In April this year, Cao Cao Travel was approved as the first company in Hangzhou to carry out robotaxi unmanned road testing. Recently, the company has also reached a strategic cooperation with the Shanghai International Automobile City, planning to deploy 100 robotaxis in Shanghai within the year and promote large-scale operations in core cities.

Currently, Cao Cao Travel has formed a three-in-one closed-loop ecosystem of "intelligent customized vehicles + intelligent driving technology + intelligent operations". In addition, the "Eva Cab", the first original development robotaxi prototype car in China, which was deeply involved in product definition and R&D by Cao Cao Travel, will make its debut at the 2026 Hong Kong Auto Show. According to the plan, this highly customized robotaxi will be mass-produced in 2027 and is planned to be deployed a total of 100,000 units by 2030.

Against the background of the accelerated integration of large models and autonomous driving technology, Cao Cao Travel, through organizational restructuring and the introduction of top talents, not only restructured its underlying technological assets, but also further accelerated the commercialization of intelligent driving in the ride-hailing industry, laying key organizational and ecological foundations for heavy-asset unmanned operations.