AI transformation in enterprises is essentially an organizational-level change; to drive employee transformation, management must lead by example.
CEO Personally "Submits Deliverables"
Wang Shoucheng, CEO of Yonghui Superstores, used Feishu to build an AI store-inspection assistant and participated in the company’s AI Pioneer Competition. Through concrete action, he demonstrated that enterprise AI transformation should begin with changes within the management team.
At the finals of Yonghui's AI Pioneer Competition, after ten teams had completed their presentations, the host announced the appearance of "Contestant No. 11"—to everyone’s surprise, it was CEO Wang Shoucheng. Unlike his traditional role sitting on the judging panel, he stepped onto the contestant stage to personally present his AI project as a participant.
Yonghui fully adopted Feishu in January 2026, launched the AI Pioneer Competition at the end of April, with a total of 237 candidates entering the preliminary rounds, and ultimately ten teams advancing to the finals. Although Wang did not participate in scoring, he set an example for the entire company by participating as a competitor.
This enterprise, which originated in Fuzhou, once broke through challenges with its fresh-food business model and expanded nationwide amid competition among large retailers. In the past, managers excelled in strategy, expansion, and supply chain construction. But facing this new wave of transformation, existing experience urgently needs updating.
"Whether it's corporate transformation or industry evolution, it cannot be achieved by slogans alone," admitted Wang Shoucheng. "True transformation requires action from top to bottom. Leaders are not just responsible for setting agendas—they must also solve problems firsthand."
Digital Empowerment for Store Inspections
Wang Shoucheng’s AI project originated from his most familiar task—store inspections. Over the past year, he spent 305 days on the road, visiting the vast majority of Yonghui stores.
He enjoys reviewing maps, where hundreds of stores form an operational network. Yet maps cannot reflect store managers’ conditions, customer behavior drivers, or how well stores adapt to new operational models.
"Many issues are invisible unless you visit the site in person," he noted. Relying solely on office blueprints and reports makes it difficult to grasp real changes in products, teams, and services.
Now, e-commerce, instant retail, membership stores, and discount formats continue to fragment the market, gradually weakening the traditional advantages of large-format stores. The number of stores no longer equates to growth—single-store operational quality has become more critical.
Since 2024, Yonghui has been learning from Pangdonglai to shift toward quality-focused retail, adjusting procurement models, operational standards, and deeply optimizing employee benefits, product mix, and store layouts. Now entering its second phase, the focus is on deepening operations, transforming initial momentum into sustainable capabilities.
During his inspections, Wang doesn’t just observe product displays—he also visits staff canteens and rest areas to understand team morale and surrounding customer demographics. However, traditional store inspections have clear limitations: they take about two hours per store, rely heavily on memory, require repeated reminders for issues, make knowledge accumulation difficult, and slow down case replication.
This is a management challenge brought by scale: when managing hundreds of stores, how can information be effectively communicated, standards enforced, and experiences shared?
Wang summarized four major pain points of traditional store inspections: information remembered manually, issues chased repeatedly, difficulty accumulating experience, and slow replication of best practices. To address these, the intelligent agent "Xiaohui Store Visit" was developed on Feishu.
Before inspection, inputting the store location retrieves team,商圈 (business district), and operational data, generating a pre-briefing report to clarify key focus areas.
During the inspection, the Anker-Feishu co-developed audio recorder captures conversations in real time, generates meeting minutes, and uploads photos and videos instantly. "Xiaohui Store Visit" integrates internal knowledge bases such as food safety, customer service, and operations to automatically identify issues.
After the inspection, the system automatically generates a diagnostic report, pushes rectification tasks to responsible parties, and promotes outstanding practices across other stores.
"Xiaohui Store Visit" is still being refined. Its goal is not to reduce the frequency of inspections, but to empower the entire organization with insights from each individual visit.
Management Leads by Example—Only Then Do Employees Believe
"Today, I’m setting an example myself," said Wang Shoucheng, explaining his motivation for joining the competition. "I hope that by next year’s competition, supervisors from our frontline departments will also participate."
Learning AI requires time investment and tolerance for trial and error. Employees watch closely to see if this is just a short-term initiative. Compared to motivational meetings, the CEO personally showcasing an AI project carries far greater credibility.
But the highlights of the competition weren't limited to leadership demonstrations—many innovations came from frontline employees. They proposed diverse AI solutions addressing practical issues such as delivery safety, risk control boundaries, customer service, food safety, and human resource management.
Although only ten projects made it to the finals, post-event review revealed 28 additional projects with application potential, spanning 17 business departments.
Many previously low-profile frontline employees gained recognition through this event. Wang discovered that frontline staff who deeply understand day-to-day operations demonstrated remarkable creativity when applying AI.
On the day of the competition, employees spontaneously created a Feishu AI discussion group. Wang immediately supported the HR team in organizing expert training sessions and offline exchanges on a regular basis.
"Let more people take the first step," he said. He hopes that early AI practitioners won’t just complete projects, but also inspire and uplift their colleagues.
Yonghui’s push for AI is not merely about mastering tools—it’s about shaping the future direction of its teams. Wang believes Yonghui does not suffer from labor surplus, but rather a shortage of roles capable of delivering high-quality human service. Excessive energy is consumed by data sorting, information synchronization, and cross-departmental communication.
"What I aim for isn’t simply reducing headcount, but redeploying human resources to more valuable work." AI should take over repetitive tasks, allowing employees to return to the frontlines and focus on operations and customer service.
This philosophy continues the management logic learned from Pangdonglai: employees are not costs to be cut, but the starting point of products, services, and experiences. When companies invest in employees, their growth feeds back into improved operational quality.
"We want Yonghui people to be more than tools—we want them to be craftsmen," said Wang. The core advantage of physical retail lies in human interaction and warmth. AI can manage processes and standards, but cannot replace the subtle, human-to-human perception.
In this process, Feishu does more than provide features—it serves as an integrated platform for data, knowledge, communication, and tasks, enabling non-technical staff to build AI assistants tailored to their own challenges.
Wang has a clear goal: in the future, every Yonghui employee will have a personalized AI assistant, freeing them to focus on creative work.
Management’s active participation convinces the organization that transformation is sustainable; meanwhile, frontline employees determine which real-world problems AI should solve. Feishu bridges problems, knowledge, and practice, enabling collaborative innovation across all levels.