"China has already taken a head start (already has a head start)."
In a technology report this month, the American consumer news and business channel (CNBC) wrote this.
According to this leading American business media, it is not only the tariff issue that constantly reminds American companies how dependent they are on Chinese factories; the entry of new technologies such as artificial intelligence and robotics is also continuously amplifying the advantages of Chinese enterprises. "As more and more factories turn to technologies such as artificial intelligence (AI) and robotics to cut costs and control quality, the Chinese supply chain is becoming more attractive."
“Artificial intelligence brings greater advantages to China's supply chain” - Media screenshot
That artificial intelligence makes Chinese manufacturing and supply chains stronger has become a consensus among many people.
Oshri Cohen, CEO of startup Cybord, said that Chinese enterprises are eager for new technologies, and the company's AI-based quality control tools will find big buyers in China. In the view of this former vice president of NVIDIA supply chain, geopolitical pressures will make the supply chain more diversified, ultimately enhancing the competitiveness of Chinese factories. "Factories will return to China," Cohen said, "China will become a model of high quality."
"When you think deeply about digital transformation and the automated digital analysis of manufacturing, you will find that Chinese enterprises are a real force in the world." Karel Eloot, senior partner at McKinsey in Shenzhen, exclaimed. Eloot mentioned that since 2018, when the World Economic Forum and McKinsey began tracking the digitalization process of factories, typical application cases have risen to 189, with 41% located in China.
"For example, people use AI to reduce time spent on inefficient meetings and use it to guide the next shift of workers to handle urgent issues."
Proportion of digitalized factories, China leads far ahead - McKinsey report screenshot
In May this year, the Ministry of Commerce and eight other departments issued the "Action Plan for Accelerating the Development of Digital Intelligent Supply Chains". The plan proposes that by 2030, a replicable and promotable mode of building and developing digital intelligent supply chains will be formed, and in important industries and key areas, a deep-integrated, smart, efficient, and self-controlled digital intelligent supply chain system will be basically established, cultivating about 100 national digital intelligent supply chain leading enterprises.
According to CNBC, this plan undoubtedly demonstrates China's further ambition to promote factory digitalization.
Facts show that major changes are happening throughout China's manufacturing sector: Yule Magnets, when entering the term "magnets" in the manufacturing version, the AI system can recommend all industries needing to purchase magnets, and list relevant downstream manufacturers and recommendation reasons in detail; in the cold rolling plant of Guangxi Liuzhi Steel Group, DingTalk digital humans and intelligent interaction platforms are turning the entire production line into a "transparent glass house", allowing employees to check production progress, production costs, and equipment status in real time through their phones...
While foreigners are still discussing computing power and algorithms, artificial intelligence may be changing Chinese factories and Chinese workers.
The "island" state of traditional supply chains is being broken by artificial intelligence
"We once served a company that produces plastic raw materials and chemical raw materials. Their boss has been in the industry for 30 years and is very familiar with the industry, he thought the main customers were those buying floor mats. But later, we found through artificial intelligence technology that their materials could also be used for mouse pads - our artificial intelligence tool can warehouse all the manufacturing components of products and clean the data, and as long as the customer has a need, we can find the corresponding components."
When talking about his "most memorable" supply chain case, Chen Xiaofeng, partner and sales VP of Tantech, recalled.
In Chen Xiaofeng's view, AI brings a possibility of "knowing the customer better than the customer" for the upgrading of China's supply chain. Chen Xiaofeng told Observers Network that human experience often has limitations, and industry experts are also limited by the boundaries of their own cognition, but AI has an extraordinary ability to break through barriers - Tantech SalesGPT includes 2 billion product data and 40 trillion product relationships, which are decomposed into a "material composition-function-application scenario" relationship network, redefining the supply-demand logic from the perspective of physical properties.
Chen Xiaofeng used to be the head of the South China ecological cooperation at Alibaba Cloud and has been rooted in the industry for many years. In his view, traditional supply chain supply-demand matching is like "looking for a needle in a haystack", with supply and demand information scattered across countless channels (exhibitions, yellow pages, door-to-door visits, etc.), and companies rely on personal connections and experience to screen, which is inefficient and prone to missing opportunities. Traditional supply chain searching for customers or partners requires separately visiting official websites, recruitment software, bidding announcements, etc., and each "data island" responds relatively slowly, resulting in high collaboration costs and low efficiency. This is a traditional pain point in China's supply chain supply-demand matching.
To solve this problem, the Tantech team built a global business knowledge graph of more than 300 million market entities through AI and big data technology, deeply integrating massive supply chain upstream and downstream data, replacing the "static information puzzle" with a dynamic, interconnected "global map".
Chen Xiaofeng said that through Tantech's global business knowledge graph, it is possible to achieve intelligent identification of multi-level upstream and downstream in the industrial chain. After the enterprise inputs its main product, the system automatically recommends potential customers/suppliers and gives the reasons for the material level and product level recommendations (such as "a certain downstream manufacturer needs specific raw materials"), significantly reducing the cost of manual screening; traditional supply chain relies on limited industry experience to expand customers, while Tantech's graph can integrate dynamic data such as business registration, bidding, and patents, combined with 2 billion product data and over 40 trillion product relationships, providing cross-industry and cross-regional supply-demand clues for enterprises.
The entry of artificial intelligence solves not only the problems of traditional supply chains such as "fuzzy target customer profiles" and "saturated regional markets", but also has advantages in eliminating data islands and improving collaboration efficiency - for example, artificial intelligence knowledge graphs can integrate data from different sources, giving enterprises a 360-degree view, making qualifications, needs, and cooperation networks clear at a glance, replacing the fragmented mode of traditional reliance on Excel (spreadsheets) and email communication, solving the problems of low collaboration efficiency and non-interoperable data.
Additionally, AI can realize dynamic response to market changes. By updating enterprise data in real time (such as new tenders, capacity changes), the data graph brought by AI achieves minute-level data update capabilities, ensuring the timeliness of supply and demand information, responding to uncertainties such as "changing policies" and "demand fluctuations" - this is something that traditional spreadsheet and email office work cannot achieve.
Does the transformation of the supply chain by AI differ for enterprises of different sizes? In Chen Xiaofeng's view, large enterprises and small and micro enterprises have obvious differences in their pain points: large enterprises have serious data island problems and have a strong demand for cross-system data integration; while small and micro enterprises are most troubled by high marketing costs and inaccurate customer positioning. Different enterprises have different paths to upgrade their supply chains with AI.
Chen Xiaofeng believes that for large enterprises, it is mainly to provide technical infrastructure support and promote their intelligent process. Under the current wave of digital transformation, large central enterprises and listed companies have increasingly prominent demands for private domain large models. These enterprises generally face the problem of low system efficiency caused by scattered technical infrastructures. Tantech's attempt is to use the Taigeng platform, utilizing advanced industry technologies such as semi-structured big data storage architecture and multimodal generative large models, to solve the problems of enterprise system data islands and low development efficiency of multiple software, accelerating the process of enterprise digitalization and intelligence.
Screen capture of the Taigeng platform official website
For small and micro enterprises, an AI + big data intelligent sales platform can help them reduce the digitalization threshold and cost. Chen Xiaofeng introduced that on one hand, based on massive data sources and precise algorithm models, it can quickly locate customers with matching procurement preferences, replacing the traditional "broad casting" model, significantly reducing marketing costs, solving the dilemma of "limited budget but poor results". On the other hand, by using "small-scale and rapid" applications (such as automatically generating marketing copy), it can cope with the challenges of "lack of technology and talent", filling the technology gap.
These practices align with academic judgments. "The essence of digital supply chain does not lie in the application of certain specific technologies or the launch of certain specific tasks, but in building the capability for digital end-to-end integration and innovation." Professor Zhao Xiande, who holds the chair of JD.com operations and supply chain management at CEIBS and is the director of the CEIBS Institute of Supply Chain Innovation, said to domestic media.
In Zhao Xiande's view, the future improvement of supply chain capabilities depends on deeper data integration and analysis. On one hand, it is necessary to connect data across the entire supply chain, extending from within the enterprise to the industry ecosystem; on the other hand, it is necessary to integrate operations research models with AI technology, where the former is used for structured problem optimization and the latter helps convert unstructured problems. For example, the application of AI in scenarios such as demand forecasting and logistics optimization is driving supply chain decision-making from experience-driven to intelligent-driven.
A vast market is also unfolding before people's eyes. Data from institutions such as iResearch shows that the scale of China's manufacturing digital transformation reached 1.55 trillion yuan in 2024, and is expected to grow to 1.76 trillion yuan in 2025, with an average annual compound growth rate of about 14% over the next five years. In this process, manufacturing powerhouses such as Guangdong, Jiangsu, Zhejiang, and Shandong have become pioneers in digital transformation, while discrete manufacturing, especially high-tech industries, has become the most promising field for transformation.
Technological revolution is moving from laboratories to production lines, and AI is empowering ordinary Chinese people
"China focuses more on pushing artificial intelligence into market applications."
In a report on China's AI development, Shawn Kim, the Asia technology research head at Morgan Stanley, explained his observations in this way.
Currently, AI development abroad has entered a stage of intense competition for computing power, with large models such as OpenAI spending heavily on computing power. During the Spring Festival, the Chinese AI large model DeepSeek, which spends less on computing power than foreign counterparts, made a surprising breakthrough and caught up globally. Even more surprisingly, Chinese AI applications are emerging like mushrooms after rain, putting AI into practical market applications, even reaching rural areas.
From industry to agriculture, more and more industries are being changed.
Tencent Yuanbao's "down-to-earth" slogan - social media screenshot
The AI-assisted Chinese workers described by Wall Street banks, improving meeting efficiency, are happening constantly.
According to Xinhua News Agency, recently, Liuzhi Steel Group launched a company-wide AI enthusiast exchange competition. Workers in the cold rolling workshop used AI to build an equipment management system, which can inspect and maintain equipment, and forecast spare parts management; workers in the environmental protection business line used AI to reshape wastewater treatment, advancing from "experience-based water governance" to "algorithm-driven water control"; the sales center group used AI to link inside and outside the factory, capturing customer needs accurately with data... Some proposed ideas, some added suggestions, and thinking sparks kept colliding.
Tao Xin, a technical expert in the cold rolling plant, gave an example. On the acid rolling production line, a 4mm thick raw steel strip needs to be transformed into a 1.5mm thin steel plate, going through more than ten processes involving over 100 parameters. It was previously difficult to determine the specific cost of producing the steel strip. Now, through the "Digital Steel Coil AI Assistant", it can accurately identify that the production cost of a 0.8mm thick steel plate on the second acid rolling line is 13 yuan lower than other specifications; it is more cost-effective to schedule the production of steel strips below 1.2mm on the second acid rolling line.
Fire in the factory - Guangxi government official website
At the bottom of the supply chain, the presence of AI also builds a vast and harmonious "neural network" for Chinese retail stores.
China's shoe and clothing giant Bally Fashion Group is one of the earliest manufacturing enterprises to embrace artificial intelligence. As a large fashion shoe and clothing group, Bally Fashion has over 8,000 directly operated stores in more than 300 cities in China and tens of thousands of store staff, with 20 core brand portfolios and cooperative brands. From design to manufacturing, from retail to management... Bally Fashion is one of the earliest digital transformation shoe and clothing enterprises in the industry.
Through cooperation with DingTalk, Bally once quickly used its artificial intelligence technology to help transform supply chain management processes. This year, the group has accelerated the application of new AI tools to the front end, such as the pilot promotion of Bailian AI: previously, the training content for salespeople was cold videos, now it is an always-online "AI tutor". Salespeople just need to upload their training videos to the AI assistant to get professional guidance from this 24-hour teacher.
AI becomes a "24-hour tutor" for retail salespeople
Newcomers can become top sellers, and any salesperson can secretly practice, quickly uncovering the potential on the market side. Bally found that after a period of trial operation, comparing the Tianjin pilot area with the North China region for the same brand, six brands using Bailian AI had significant improvements in sales contribution rates compared to the same brand in North China; one brand even had a two-digit monthly increase in sales contribution rate.
Similar examples are numerous. Artificial intelligence is providing China's supply chain with a new possibility of self-renewal.
On June 18, the U.S. financial service platform AInvest wrote in its latest article, "The global supply chain is quietly undergoing a transformation, and the center of this transformation is China. In the context of trade tensions and geopolitical changes, China is using artificial intelligence and industrial automation to consolidate its position as a high-quality, cost-effective manufacturing center."
"Investors should pay attention to companies that connect China's automation ambitions with the global supply chain," the institution advised its clients, stating that in the era of fragmented supply chains, China's AI-driven factories are the key bonding agents. "Don't miss the train (Don't miss the train)."
Original: https://www.toutiao.com/article/7519046975732515380/
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