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EnglishOn April 24, the "Enterprise AI Digital Transformation Summit," co-hosted by the Qingdao Municipal Bureau of Industry and Information Technology and the Qingdao Enterprise Federation, organized by DingTalk, and supported by the Qingdao Artificial Intelligence Industry Association, was successfully held in Qingdao.
Qingdao Designates Artificial Intelligence as a Leading Industry
In his speech, Sun Jianwen, Deputy Secretary-General of the Qingdao Enterprise Federation, pointed out that Qingdao has included artificial intelligence among its key priority industries, with over 500 AI-related companies concentrated throughout the city. He encouraged the attending enterprises to actively embrace AI technology, seize the historic opportunities presented by the new wave of technological revolution and industrial transformation, integrate AI concepts and methodologies into their corporate strategies and daily operations, and collectively contribute to the high-quality development of Qingdao's AI industry.
Three Key Conditions for Successful Enterprise-Level AI Implementation
Shi Jiangfeng, General Manager of Alibaba’s Wukong Business Unit for East China, stated that more than 80% of Shandong Province’s listed companies and Fortune 500 enterprises are currently using DingTalk, with many having progressed from basic office collaboration to advanced AI applications.
He emphasized: “AI is a marathon, not a sprint.” For enterprises to successfully implement AI, they must meet three core requirements: organizational structure, enterprise data, and integration with business systems. Without an internal company directory, AI cannot define access permissions; without a proprietary knowledge base, it risks generating inaccurate information; and without connection to existing business systems, AI remains superficial. Wukong’s primary advantage lies in its “secure sandbox” mechanism, which automatically inherits existing organizational permissions, preventing unauthorized actions or accidental deletion of critical data—something consumer-grade AI tools struggle to match.
Stanley: Starting AI Adoption with High-Frequency Tasks
Founded in 1992 and listed on the Shenzhen Stock Exchange in 2011, Stanley operates 12 major production facilities nationwide, boasting an annual capacity of 6.5 million tons and a sales and service network spanning over 100,000 locations.
Ma Jingyuan, head of Stanley’s AI project, recalled that immediately after the 2023 Spring Festival, the chairman instructed all employees to learn about AI. By the following Spring Festival, the company further accelerated efforts to leverage AI in solving real-world business challenges. After evaluating numerous open-source and commercial solutions, Stanley ultimately chose DingTalk. He explained: “DingTalk seamlessly integrates with our existing office systems and organizational structure, offering precise and granular permission controls—perfectly aligned with our enterprise needs.”
At the application level, Stanley prioritized introducing AI to tasks that are highly repetitive, time-consuming, error-prone, and occur frequently.
Take marketing as an example: pricing compound fertilizers involves multiple factors, including distributors, shipping locations, and transportation methods, making the traditional ordering process take over a minute even for experienced staff. Now, sales reps simply say into their phones, “Place an order for 5 tons of SAN,” and Wukong instantly recognizes the product, quantity, and shipping details, completing the order in as little as twenty seconds.
In data analysis, previously one employee needed three minutes each day to compile trace element data. With Wukong’s AI-powered functionality, this now takes just ten seconds. Ma Jingyuan noted: “Saving three minutes per sheet, across 12 bases and multiple reports, we free up 24 work hours every day.”
On the supply chain side, raw material price monitors used to manually collect data at 4 p.m. daily. Now, Wukong handles this task automatically, gathering domestic and international raw material prices and inventory levels to generate comprehensive reports. Meanwhile, the shared finance center uses an AI assistant to route common reimbursement questions to dedicated service groups, allowing AI to provide instant answers while freeing financial reviewers to focus on core auditing tasks.
Ma Jingyuan likened driving an AI initiative to farming: “You must choose the right seeds, deeply till the soil, master the techniques, and select suitable tools.”
A Da™: AI Reshaping Production and Operations
Kaisheng Haofeng, a mixed-ownership enterprise under Kaisheng Technology Group—a subsidiary of China National Building Material Group, a Fortune Global 500 company—operates the brand “A Da™,” specializing in tomatoes and their processed products. On platforms like Tmall and Douyin, A Da™ consistently ranks among the top three in its category, with an e-commerce repurchase rate as high as 50%.
Liu Qing, head of A Da™’s digital technology department, explained that the company has been using DingTalk for over eight years. Currently, 1,109 users actively engage with AI Tables, achieving 100% coverage. Together, they have launched over 2,700 AI tables, deployed 200 digital employees, and accumulated more than 420,000 minutes of AI transcription time.
On the production floor, greenhouse biosecurity protocols prohibit mobile phones, forcing technicians to record data manually and later transcribe it into Excel—an approach prone to errors. Today, technicians can simply snap a photo, and AI automatically identifies and inputs the data, flagging anomalies in red and sending immediate review alerts. “Data transcription efficiency has improved by 90%, error rates have dropped by 90%, and problem-resolution speed has increased by over 50%,” Liu Qing noted.
For facility inspections, each base previously required a dedicated safety officer. Now, any employee can scan, photograph, and upload potential hazards, with AI automatically identifying issues, linking them to relevant regulations, and providing corrective guidance. When a specific risk emerges at one site, the system proactively retrieves similar cases and solutions from other bases.
The marketing team once had to manually track competitor pricing, new product launches, and brand sentiment across various platforms. Now, they simply issue commands to Wukong and receive consolidated reports within minutes. Legal contract reviews, which previously took 10 to 15 minutes per document, are now flagged by Wukong in just 2 to 3 minutes, highlighting key clauses and suggesting revisions. In recruitment, AI can screen thousands of resumes in 20 minutes; this year’s campus hiring, which traditionally required four weeks for initial screening, was completed in just a day and a half. AI interviewers for entry-level positions can handle basic candidate inquiries, reducing HR workload by 40%. Moreover, AI analyzes micro-expressions during interviews, helping detect potential resume or academic credential fraud.
Liu Qing remarked: “Over a decade ago, people said ‘software is eating the world.’ Today, AI is eating software. In the future, all software will be redefined by AI.”
From policy direction to technical support, from Stanley’s fertilizer plant to A Da™’s smart farm, Shandong-based enterprises are leveraging DingTalk and Wukong to build their own competitive AI advantages. This digital transformation is rapidly permeating every operational facet—production, marketing, finance, supply chain, and beyond. As more companies embed AI deeply into their daily operations, embracing AI is no longer just a slogan but has become a vital engine propelling Shandong businesses toward leapfrog growth in the new era.
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