Xiamen Hosts DingTalk Summit: How Fujian Enterprises Leverage AI to Solve Real-World Challenges from Smart Technology to Advanced Manufacturing

On July 8, the 2026 DingTalk Summit Xiamen Station, themed "The Way of Work in the AI Era," was successfully held. Organized by DingTalk and guided by the Xiamen Software Industry Association, the summit brought together hundreds of enterprise representatives from fields such as intelligent technology, biomedicine, and advanced manufacturing. The event focused on practical pathways for implementing AI in real business scenarios and explored methodologies for transforming from "tool-driven efficiency" to "organizational transformation."

Policy Support Drives Deep Integration of AI and Industries

In his opening remarks, Yuan Wei, DingTalk's regional director for Fujian and Jiangxi, mentioned that Fujian Province and Xiamen City are sending strong signals for AI development through a series of industrial policies.

In February 2025, the Fujian provincial government clearly proposed an interim goal: by the end of 2026, the added value of the digital economy should account for 57% of GDP. As a pioneer in artificial intelligence industry development within the province, Xiamen released its "Artificial Intelligence Industry Development Plan (2025–2027)" at the end of the same year. The plan stipulates that by 2027, Xiamen’s core AI industry scale will exceed 60 billion yuan, with no fewer than 500 core enterprises.

DingTalk Builds an End-to-End Closed Loop of AI Capabilities

In response to policy opportunities, Alibaba Group is accelerating its strategic focus on AI. "Alibaba has established a full-stack closed-loop capability—from underlying computing power and foundational models to upper-layer application ecosystems," said Yuan Wei. "As a key platform serving B2B enterprise users, DingTalk has a clear mission: to make AI truly operational within enterprises and shape the way of work in the AI era."

DingTalk AI Capability Landscape and Transformation Methodology

Wang Junbo, DingTalk AI solutions expert, elaborated on DingTalk’s comprehensive AI capabilities blueprint. Using manufacturing scheduling as an example, he explained that a production planning process that previously required hours of collaboration between order followers and engineers can now be completed in just five to ten minutes—simply by submitting a multilingual, unstructured order to AI, which automatically handles data extraction, BOM matching, inventory checks, and outputting production plans. Additionally, AI-powered spreadsheets can quickly convert various data formats into structured information, while the Yida platform enables business personnel to generate executable business systems using natural language.

Beyond technical capabilities, Wang also emphasized strategies for enterprise AI transformation. He suggested that the role of corporate IT departments will shift from "developing systems" to "selecting tools, empowering frontline teams, and ensuring security"—that is, choosing appropriate tools, training staff, and maintaining safety standards. To measure maturity in transformation, he highlighted three dimensions: whether employees are genuinely using AI, whether industry experience is being accumulated into reusable skills, and how fast ideas can turn into implemented systems.

Enterprise Case Studies

At the summit, representatives from three companies shared their practical experiences with AI implementation across multiple dimensions.

Luo Yaying, Director of the Information Center at SDIC Intelligence, stated that her company pioneered an integrated management loop connecting "meeting recording → intelligent transcription → task assignment → supervision and tracking." They have deeply embedded AI into their corporate training system, enabling intelligent iterative upgrades in lecturer evaluations and teaching quality optimization, comprehensively enhancing internal management efficiency and effectiveness.

In the field of intelligent agents, SDIC Intelligence independently developed two demonstration applications—"Digital Avatar" and "Meeting Assistant"—closely integrated with DingTalk’s AI ecosystem. "AI is no longer just a futuristic technological concept; it has become a tangible productive force today. Our central goal is to transform artificial intelligence from a single auxiliary tool into core infrastructure for enterprise digital transformation," said Luo Yaying.

Chen Minjun, head of informatization at Bestar Biotechnology, noted that the company's R&D centers are located across four regions, resulting in fragmented institutional documents. Moreover, repetitive inquiries have long consumed significant manpower. To address this, the company built an enterprise-level AI assistant named "Ai Bao" on DingTalk, integrating thousands of SOPs and policy documents so employees can now "ask Ai Bao instead of asking people." Beyond backend Q&A, Bestar’s AI applications are gradually extending into operational workflows: due to strict compliance requirements for medical devices, AI assists employees in reviewing documentation and intercepting content issues proactively.

Next, Bestar is collaborating with DingTalk to extend AI capabilities into business data analytics to support decision-making. "AI does not replace employees—it empowers them," said Chen Minjun. "Our vision is to provide every Bestar employee with a personal 'intelligent advisor'."

Xu Wanshun, CIO of Aien Technology, pointed out that by integrating DingTalk Teambition with the PLM system, the company broke down its IPD R&D process into A/B/C-level templates and over 200 standardized tasks. With one click, these tasks are automatically assigned to employees, improving project initiation efficiency by more than 60%. A more significant change occurred at the performance level: based on Teambition task completion data, the system automatically calculates performance coefficients linked directly to compensation, allowing 20% of performance-based pay to be processed without manual intervention. Furthermore, adopting DingTalk AI enables intelligent analysis of meeting minutes and collaboration behaviors, shifting performance evaluations from a pure "results-only" approach to one where contributions are quantifiable and processes are traceable.

Deepening Regional Services to Accelerate Enterprise Intelligence Transformation

This DingTalk Summit marks another step in engaging deeply with regional industrial clusters and reflects DingTalk’s ongoing efforts in localizing services. Committed to solving real-world problems, DingTalk will continue to deepen its engagement with Fujian’s industrial ecosystem. By combining AI tools with long-term accompanying support, DingTalk aims to help more local enterprises identify suitable entry points for AI adoption, striving to transform intelligent ways of working from early adopters’ experiments into everyday practices for every business.

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