China’s CaoCao Launches AI Ride-Hailing Service With ByteDance’s Doubao(Yicai) Sept. 10 -- CaoCao Mobility, a leading Chinese ride-hailing platform, has launched an artificial intelligence-assisted service relying on Doubao, an AI app from TikTok owner ByteDance.
The new AI service is available in Beijing, Hangzhou, and Suzhou, CaoCao announced yesterday. Users can request a car and enter their destinations through text or voice on Doubao, which will immediately plan routes and offer various vehicles and prices to choose from, with payments made in the app.
Beijing is the headquarters of ByteDance and Suzhou of CaoCao, while Hangzhou is the registration location of Ugo Tech, the operator of CaoCao, so the three cities were picked for the pilot, a person familiar with the matter told Yicai. The service will launch in more cities, the person said, noting that the platform will likely collaborate with other online AI super gateways as well, such as AI agents and phone assistants.
By adding AI-assisted services, CaoCao can provide differentiated experiences to users, likely gaining new orders from AI channels and reducing its dependence on traditional ride-hailing aggregators, Chen Liteng, a senior analyst at 100EC.CN, said to Yicai.
In addition, CaoCao can also take advantage of the new service to collect user demand data in AI mobility scenarios to optimize vehicle scheduling and cultivate users for future autonomous services through this new model of requesting cars via AI apps, Chen pointed out.
However, AI-assisted ride-hailing services are still in the exploratory phase and need to provide more value to build user habits, Chen stressed, noting that reaching the destination via optimal routes at the lowest price is the most desirable feature for users, but no such service is available yet.
CaoCao launched in 20 new cities in the first half of this year, bringing its total to 215, according to the company’s latest financial report. The average number of its active drivers per month jumped 37 percent to 758,000 from a year earlier.
Editors: Tang Shihua, Martin Kadiev
