This year's Spring Festival, a war without gunfire changed China. Doubao, Yuanbao, and Qianwen flooded the Spring Festival Gala, elevators, and social media, bringing AI to every family's New Year's Eve dinner table with billions of red packets. This Spring Festival, AI is no longer a tech-circle term; it has become a national topic. Data shows that in March 2025, domestic AI app downloads exceeded 160 million, with about 200 million people using AI applications daily. Doubao's daily token calls surpassed 50 trillion, a tenfold increase year-over-year. 2025 is undoubtedly the year of AI's explosive growth in the consumer sector. Then, in Q1 2026, OpenClaw (lobster) emerged, and AI agents broke through previous limitations—they no longer just answer questions; they start doing things for you. This time, people began seriously discussing: Will AI replace my job? And business managers finally started thinking seriously: Can AI help me manage my company? But in the FMCG industry, the explosive growth of AI in the consumer sector and its sluggishness in the B2B sector have formed a huge gap.

AI's B2B Applications Are Still Stagnant

Today's FMCG industry is under immense growth pressure: new product success rates continue to decline, sell-through data is increasingly poor, costs rise annually, and operational efficiency has hit a ceiling. AI could be a game-changer, but the harsh reality is that most FMCG companies' AI usage is still at the stage of occasional employee use. Sell-through prediction, marketing customer acquisition, product distribution, supply chain optimization—these critical operational areas have yet to see AI integration. There are three main reasons for the slow B2B adoption of AI in FMCG.

First, Complexity Is Not on the Same Scale

Consumer AI solves one person's problem: search, think, answer—clear, immediate, and closed-loop. One person asks, one AI answers, that's enough. Enterprise AI implementation is ten thousand times more complex than personal AI use—it requires organizational adjustment, process reengineering, and has extremely low fault tolerance. The difficulty is not on the same scale. For example, an AI model for sell-through prediction needs to integrate sales system data, understand channel structure logic, match supply chain inventory rhythms, and align business teams, IT departments, and management. From individual to organization, from Q&A to processes, complexity rises exponentially, not linearly.

Second, Most Companies Lack Proper AI Thinking

Consumer users don't need "AI thinking"; it just needs to work. But for a company's managers, without clear AI awareness, they cannot lead transformation or drive implementation. Many FMCG managers still can't distinguish between AI and digitalization, don't understand the difference between large models and agents, and are confused by terms like token, computing power, and RAG. But this isn't the problem. With rapid AI iterations, even tech professionals struggle to keep up, so how can FMCG people? The problem is that FMCG managers fall into a trap: if they don't understand, they wait; waiting leads to falling behind; falling behind causes panic; the more panic, the less they know where to start.

Third, Industry Knowledge Has Not Yet Become AI-Readable Language

General large models know everything but don't understand FMCG. They don't know what "sell-through rate" means, don't understand distributor payment terms, or the channel structure differences between county-level markets and first-tier cities. These decades of industry knowledge accumulated in brands, distributors, and retail terminals remain fragmented and haven't formed a standardized knowledge system that AI can deeply utilize. The result: AI is smart, but in the FMCG context, it still "doesn't understand" the industry. These three reasons make AI's B2B adoption seem slow compared to consumer AI. But past eras tell us that AI is definitely not a technological wave we can wait to see; it can't even be defined as a "epoch-making tool." It is the new era itself.

AI Is the New Era Itself

"AI is the new era itself"—we are not exaggerating. Looking back over the past thirty years, the competitive rules of the FMCG industry were clear: Demographic dividends brought growth, channel expansion brought coverage, and classic marketing theories like the 4Ps, STP model, and positioning could explain almost all successes and failures. But competition in the AI era is entirely new. It fundamentally differs from the past in several dimensions:

  • Economies of scale will be rewritten. In the past, large companies crushed small ones with manpower. In the AI era, a 100-person FMCG company, with AI deeply embedded in operations, can match the analytical and response capabilities of former thousand-person competitors.
  • Consumer insights will be completely reconstructed. AI can analyze massive consumer behavior data in real time, compressing product development cycles from "years" to "months" or even "weeks." Whoever understands consumers faster will seize the next opportunity.
  • Channel management will enter the intelligent era. AI-driven sell-through prediction, distribution path optimization, and customer tiering will make "experience-based" channel operations history. Manufacturers with AI capabilities will gain visible efficiency advantages in terminal control.
  • First-mover advantages will be unprecedented in this era. AI needs data feeding, industry knowledge accumulation, and organizational alignment. Early movers accumulate not just tool experience but data assets and cognitive moats that competitors find hard to replicate. Past FMCG competition was about who had deeper channels, more teams, and bigger marketing budgets. Future FMCG competition will be about the depth of integration between AI capabilities and industry knowledge. Old winners may not be the new winners.

Why Hold This AI Application Forum?

New Distribution has been founded for ten years, and we've always done one thing: help FMCG professionals see industry trends and find the next step. Today, we believe that AI is the most important variable for the FMCG industry in the next thirty years. Its impact is no less than the shift from offline to online channels, and even more profound—because it changes not just sales channels but the underlying logic of the entire business. We also clearly see that the FMCG industry's understanding of AI is severely insufficient. Not because practitioners aren't smart, but because there's a lack of an AI practice platform that FMCG people can understand, see, and take back to use. That's the original intention behind our "First China FMCG Conference AI Application Forum." Dividends wait for no one; pioneers seize opportunities, and observers will become chasers.

What Highlights Can We Expect from This Forum?

May 27–28, 2026, Hangzhou. This will be the first industry conference in China's FMCG sector truly centered on AI, hosted by New Distribution, co-hosted by Baidu AI Cloud, and supported by Turing AI Research Institute, Qingtu Data, and FMCG Insider.

  1. Major: Baidu Nara Agent Global Launch On May 27, Baidu AI Cloud will officially hold the global launch of Nara Agent at the forum. Nara Agent is China's first true AI agent specifically for the FMCG industry, transforming core business scenarios like sell-through prediction, distribution optimization, and customer management into operational AI capabilities. Nara is not a general AI tool but an agent that truly understands FMCG.
  2. China FMCG Industry Officially Initiates KBS Initiative New Distribution, together with Turing AI Research Institute, Qingtu Data, and Baidu AI Cloud, will jointly launch the "FMCG Industry KBS (Knowledge Based Sharing) Initiative" at the conference—promoting systematic accumulation and sharing of industry knowledge to build the knowledge infrastructure for FMCG AI applications. The implementation of the KBS initiative in the FMCG industry is a major event that can change the industry's future landscape.
  3. Real Implementation Cases, Not PPT AI The forum will invite top research institutions, leading large models, brand decision-makers, and industry experts to bring AI application cases and discussions on sell-through prediction, marketing insights, product development, supply chain optimization, organizational change, and production intelligence. Actual cases, not just text in PPTs, with numbers, lessons, and replicability.
  4. VIP Deep Discussions/Large Classes: Take Methods Home On the second day, there will be multiple VIP-exclusive discussions/practical classes in two directions: brand manager direction and distributor-specific direction.
  • The brand session focuses on real paths and obstacles to internal AI implementation;
  • The distributor session covers data analysis to tool practice, with all-day immersive drills to take away usable methods. Today, AI changes too fast, information is too much, and truth is hard to distinguish. But correctly understanding AI and establishing proper AI thinking are the foundation for winning in the AI era. Now, we are still in the window of AI-era dividends, but that window narrows every day. The First China FMCG Conference AI Application Forum is a grand gathering for AI pioneers. May 27, Hangzhou, we'll be waiting for you here.