Yuanji Food Group Digital Decision-Making Center Director Deng Xianping: Focus on core business, first optimize the most valuable points.

Ask AI · Why does Yuanji prioritize using AI technology in core business applications?

On March 25, the 2026 China Catering Industry Festival and the 35th HCC Global Catering Industry Expo, jointly hosted by the World Chinese Catering Industry Association and Hongcan.com, were held at the Hangzhou Convention and Exhibition Center. Among them, during the roundtable segment of the “2026 China Catering AI Development Forum,” Deng Xianping, head of the Digital Decision-Making Center of Yuanji Food Group, shared Yuanji’s practical experience in applying AI.

△ Deng Xianping, head of the Digital Decision-Making Center of Yuanji Food Group

Deng Xianping said that as a company’s scale expands, the problems it faces need more refined management. The old approach of quickly recouping costs and achieving profitability through rapid expansion and opening franchise stores is no longer applicable.

What companies need to do now is to look internally—across different stores—for those work steps that happen frequently but are inefficient, and try to combine those steps with technology to solve certain problems. If the experiments and verification within a limited scope show no issues, they can then further roll it out nationwide.

Taking Yuanji Food as an example, the earliest application of AI began through cooperation between stores and some vendors, mainly used for quality control, and for store management—to help stores solve certain food safety–related issues in operations.

In addition, within the company, they identify some high-frequency but inefficient points to improve costs. For example, improving takeaway (delivery) operations. Takeaway plays a relatively important role in Yuanji’s overall business. The ad-promotion traffic strategy and store operational efficiency directly affect business results. By introducing algorithmic analysis, Yuanji has started to gradually and automatically optimize the ad-promotion traffic strategies of each store. “We’ve already seen results in this scenario, and the ad-promotion traffic ROI can increase by about 15%,” Deng Xianping said.

Deng Xianping also emphasized that a company’s energy and resources are limited, so AI applications cannot be pushed in a scattershot manner. “We must allocate computing power to the most valuable core business departments.” For large chain operators, running it first in a high-frequency, quantifiable scenario to work out the approach, validate the results, and then consider extending it to other areas is a safer and more effective path.

Author: Hongcan Editorial Department