At Henan Pangdonglai, an employee returning home late receives a Feishu notification precisely thirty minutes after clocking out—a consistent safety check-in following every night shift. In Tokyo's Aeon Supermarket, a biscuit sampler logs tasting data into multi-dimensional tables. This retail giant, coordinating 9,000 stores and 1,200 samplers, once planned a 100-million-yen custom system investment before embracing Lark Base, Feishu's overseas multidimensional table solution, as its complete replacement.
Yongzhuo Holding in Zhangjiagang, Jiangsu—a Fortune 500 firm with over 10,000 staff—grappled with soaring tire costs for years. After Feishu consultants pinpointed waste sources through deep analysis, the company now anticipates saving 3 million yuan annually from what was once a 10-million-yuan expenditure.
In the beverage sector, five out of six publicly listed tea brands—including Mixue Bingcheng, Bawang Chaji, and Chabaidao—leverage Feishu at varying levels. Among China's top 10 cosmetics brands like Proya, Botanee, Giant Biogene, and MGP, adoption hits 70%. Automotive manufacturing sees over 60% of core collaborations among sales-leading automakers occurring on Feishu, extending to suppliers like Desay SV, Inovance Technology, and Eve Energy. AI innovators including Deepseek, Horizon Robotics, and Zhiyuan Robotics adopted Feishu from their startup phases.
Why this surge? At Feishu's recent launch event, XPeng Inc. founder He Xiaopeng emphasized, "I’m not here to advertise, but Feishu has genuinely transformed my work and XPeng’s operations." Observers note Feishu’s logo-covered walls showcase China’s most ambitious companies—firms pursuing efficiency revolutions and deploying Feishu to combat "AI hype."
While 2025’s generative AI ignited consumer excitement, B2B sectors faced a chasm between flashy AI demos and practical implementation. Core challenges emerged: First, fragmented enterprise data trapped in personal drives or paper notes can't fuel AI engines. Feishu CEO Xie Xin starkly illustrated: "If your tools mainly track attendance, AI might only predict which employees will arrive late tomorrow." Second, an "AI demo versus reality" gap plagues the industry—marketing claims of omnipotent functions crumble during actual use.
Xie Xin framed solutions plainly: "Digitization anchors AI advancement—B2B AI adoption is a marathon." Feishu’s approach harnesses routine collaboration to silently accumulate data assets, converting them into intelligent productivity. The core logic? Collaboration builds repositories; repositories enable intelligence. For users, simplicity reigns: consistent tool usage breeds richer data.
XPeng Inc. exemplifies this: Beyond AI-enhanced meetings, Feishu Docs drove 630,000 AI-generated minutes in H1 2025, slashed non-essential meetings by 30% year-over-year, and achieved 72% cloud document penetration.
To combat industry ambiguity, Feishu unveiled an AI maturity model on July 9—mirroring autonomous driving’s L1-L4 tiers—with four stages: M1 (internal demos), M2 (early adopters), M3 (scalable deployment), and M4 (universal application). Xie Xin asserted this standards-driven approach counters tech bubbles: "We’ll label every AI feature’s maturity transparently—a vital industry responsibility. Realistic expectations prevent unnecessary anxiety."