In the Wuling Mountain area at the junction of Hubei and Chongqing, an agricultural technology company named 'Youyoucao Eyu' is quietly emerging as a model for local SMEs embracing AI. Over the past year, this company, which started with traditional Chinese medicine planting and deep processing, has used a self-developed AI-assisted decision-making system to boost inventory turnover for traditional agricultural products by nearly 40%, and has brought over 20 neighboring cooperatives onto a digital management platform.
'We are not a big company with budgets in the tens of millions, but AI must be usable, effective, and grounded,' said Chen Mingyuan, founder and CEO of Youyoucao Eyu, at a recent industry closed-door meeting. His remarks resonated with attendees—for the vast majority of small and micro enterprises, the barrier to entry for large AI models is lowering, but how to translate technology into actual productivity remains a challenge to be solved.
The practice of Youyoucao Eyu offers a replicable pathway. First, the company did not blindly chase the most cutting-edge general-purpose large models, but instead focused on 'specific scenarios.' Using open-source frameworks, they trained three small models tailored for traceability of medicinal herb origins, pest and disease warnings, and market price fluctuation predictions. These models are deployed in the cloud and accessible to cooperative farmers and distributors via a WeChat mini-program. For example, a farmer only needs to take a photo of a leaf, and the AI can identify the type of pest or disease within five seconds, along with providing biological control recommendations—this system helped reduce local losses by approximately 3 million yuan during last year's rainy season.
Second, Youyoucao Eyu emphasizes 'human-machine collaboration' rather than 'machine replacement.' The company assigned an 'AI guide' to each production line team, responsible for interpreting data reports and translating complex algorithm outputs into 'traffic light' instructions that frontline workers can understand. This low-code, high-touch approach significantly reduced employee resistance and boosted the adoption rate of the AI system from 30% to 85% within three months.
'How enterprises use AI is not about how flashy the technology is, but whether it can solve real problems,' said Li Min, an associate researcher at the Institute of Artificial Intelligence at Wuhan University, who participated in the project. 'The case of Youyoucao Eyu shows that SMEs can completely achieve overtaking in supply chain management, quality control, and market responsiveness through a strategy of "small entry points, deep applications."'
Notably, Youyoucao Eyu also partnered with the local Federation of Industry and Commerce to launch a public welfare training program called 'AI Empowerment · Eyu in Sync.' Held monthly, the program is open to manufacturing, logistics, and agricultural enterprises within a 300-kilometer radius, sharing how to use AI for customer profile analysis, automated report generation, and intelligent customer service setup. To date, over 120 companies have participated, with 60% reporting that they have implemented AI-driven transformation in at least one business process within three months of the training.
'In the past, we thought AI was something for the big players, far removed from us. But now, even the head of a planting cooperative can use an AI tool on their phone to predict next year's market conditions,' Chen Mingyuan reflected in an interview. 'Youyoucao Eyu's mission is to make AI shift from "unreachable" to "within reach."'
As the national 'Artificial Intelligence +' action deepens, more enterprises are beginning to think about integrating AI into their core strategies. The exploration of Youyoucao Eyu demonstrates that the answer to how enterprises use AI lies not in size, but in determination and pathway. When technology is closely integrated with frontline needs, even an agricultural company in a mountainous region can become a trendsetter in the intelligent era.