In recent years, AI has been hot, triggering widespread technological anxiety. Especially for FMCG business owners, facing high-intensity external information exchange, there is always an illusion that there is a huge gap between the advanced nature of technological development and the traditional nature of the industry, and that the industry is about to be disrupted by technology. Once they use AI tools, they find them highly efficient—searching for information, writing copy, analyzing and summarizing—feeling that their way of working is about to change. But when they return to actual business, they find they don't know how to apply it on the ground, still anxious in the growth dilemma of channel games and product penetration. This contrast further triggers anxiety, fearing being left behind by competitors. Business is already competitive; if technology efficiency doesn't keep up, in the end, there will be no business to do. This is probably the true mindset of FMCG business owners, especially small and medium-sized enterprise owners. AI Will Not Change the FMCG Business It Will Only Change the Way Information Is Processed This anxiety is typical ineffective anxiety caused by information overload. Whether it's AI or not, no matter how technology changes, the FMCG business has never changed. FMCG is essentially a goods-selling business. From raw material procurement, production processing, product design, to distribution and shelf placement, the entire process is a physical-world activity. AI does not change the physical world; consumers ultimately need to eat, wear, and use things. This means that providing consumers with better, more cost-effective products that meet their needs is the never-changing core competitiveness of the FMCG industry. Since the core competitiveness of FMCG enterprises hasn't changed, any change is a secondary aspect of the contradiction, and AI is no exception. Unless one day enterprises can develop products based on AI guidance and be recognized by the market, the above situation will never change. If we define the change brought by AI technology as a secondary aspect of the contradiction, we need to objectively view what changes AI technology can bring to FMCG enterprises. Frankly speaking, although AI cannot disrupt the FMCG business, it is indeed penetrating the daily operations of enterprises at an incredible development speed. Performance of AI penetrating daily operations of enterprises, Excerpted from New Distribution's "AI Applications in the FMCG Industry: The Key Lies in the Frontline Market!" From actual implementation, AI has changed the way information is processed and handled, and even has simple reasoning and summarization capabilities. As a result:

  1. Handling trivial and mechanical desk work has become convenient;
  2. The threshold for accessing information and knowledge has been lowered. AI has indeed helped many FMCG positions greatly shorten the time to handle simple problems, allowing them to focus on solving key complex problems. It is precisely for this reason that a large amount of basic work in the FMCG industry is being penetrated by AI. There Are Still Many Difficulties in AI Implementation in the FMCG Industry For AI to play a greater role, especially to truly solve specific problems, there are still many obstacles to implementation. The biggest problem is that even if AI has reasoning abilities, even complex reasoning, it still needs to reason based on information. As Wang Xing mentioned at Meituan's internal meeting earlier this year, the digitalization of the physical world is a very important foundation for AI. Wang Xing's judgment on AI at the internal meeting in early 2026 But for the FMCG industry, incomplete digitalization has always been a persistent problem, and this is the biggest crux causing the slow implementation of AI. However, the phenomenon of "extremely poor data completeness" is closely related to the business model of this industry.
  3. Multi-level information loss and loss in the FMCG industry FMCG is a typical long-chain business. From raw materials, production, distributors to terminals, the chain is long and dispersed. Each link retains some information, making it impossible to fully piece together information. Some links even lack data accumulation. For example, among millions of traditional "mom-and-pop stores" in China, the vast majority of transactions lack even basic ERP systems, making it impossible to capture basic data.
  4. Extremely fragmented terminals: high "digitalization costs" The core battlefield of FMCG is offline, and China's offline channels are arguably the most complex retail network globally. To achieve data completeness, it is possible to solve, but it requires installing "eyes" (POS machines, barcode scanners, DMP systems) on terminals. Not to mention the difficulty and economic cost of implementing this, even if different retail terminals have information systems, if the data ports of each system are not connected, the technical and communication costs to fully solve this are extremely high.
  5. "Data redundancy and garbage" in traditional industries Many times, FMCG enterprises do not lack data, but have a pile of "dirty data" that cannot be cleaned or aligned. Taking a single company as an example, various departments (marketing, sales, e-commerce, etc.) each have their own internal Excel sheets with different formats and inconsistent standards, and information granularity varies greatly. To connect them requires cleaning a large amount of data. Not to mention the data redundancy across so many companies in the industry; to unify effective data, the cleaning difficulty is enormous. Data bottlenecks at multiple levels prevent AI from ever mastering massive amounts of real and effective data to make accurate and effective judgments. Final Thoughts Although AI still has many challenges to overcome in solving industry problems, it does not mean AI cannot have a huge impact on the FMCG industry in other aspects. From a tool perspective, AI can assist in many things. Therefore, from a work efficiency perspective, AI undoubtedly has great potential to be unleashed. Drawing on the book "Rewired 2.0" published by the well-known consulting firm McKinsey, which addresses the question "When AI technology is no longer mysterious, how should enterprises rely on it to reshape business?", the judgment is that "AI leadership" will be key in the future. "Rewired 2.0" emphasizes that talent transformation is the key Because with AI tools, the quality and speed of junior business output can rival that of senior veterans, greatly alleviating enterprise talent anxiety. And the talent problem—the lack of middle and senior managers with strong business capabilities and high professional quality—is another persistent problem that FMCG enterprises cannot avoid. It is not hard to imagine that AI's assistance in many matters can help FMCG enterprises eliminate the negative impact of many talent shortages. Looking to the future, "human-machine collaboration" will become a new required course for FMCG enterprises, almost becoming a standard for positions. Enterprises not only need to introduce technical experts who understand algorithms, but also need to cultivate "AI application talents" who understand business. Therefore, for FMCG enterprises, what really needs to be discussed today is not whether AI will disrupt the industry, but how AI can enter real operations. AI will not sell goods for enterprises, nor will it change the basic logic of products, channels, terminals, and sales promotion. But it will change the way enterprises process information, analyze data, accumulate experience, and coordinate organizations. The future gap lies not in who chases the trend earlier, but in who can truly put AI into sales management, channel operations, business analysis, and frontline execution. On May 27-28, in Hangzhou, the "2026 China FMCG Conference AI Application Forum" , we will discuss with the industry: how FMCG enterprises can truly turn AI from a tool into a truly implementable operational capability.