Example: In villages around the Yangiyul district, after news spread that one farmer had grown tomatoes intensively on 0.5 hectares of land and earned a good income through drip irrigation and a proper fertilization system, neighboring farmers also started applying the same model without analysis. However, since the agrotechnical characteristics of each plot of land were not taken into account, the system worked incorrectly in many places, crop quality decreased, and costs increased. As a result, competition in the market intensified, and many farmers experienced losses instead of the expected profit.
In this situation, the main problem is not the technology itself, but the culture of blindly copying it. Since imitation prevails over analysis in the decision-making process, high-quality, scientific, and long-term approaches are pushed into the background.
From an economic point of view, two types of decisions emerge in the market. The first type consists of high-quality decisions based on agronomic knowledge, soil analysis, and long-term investment. The second type consists of decisions based on copying a neighbor’s experience, expecting cheap and quick results, but having a weak scientific foundation. It is precisely this second group of decisions that spreads widely because of its simplicity and low cost. As a result, according to Gresham’s Law, such decisions push out high-quality ones.
The main causes of this problem include a lack of agricultural knowledge, a weak agronomic advisory system, the absence of a risk assessment culture, and the mistaken belief that “one result will be the same everywhere.”
At this point, modern technologies, especially artificial intelligence and digital agricultural platforms, can take the issue to a new level. AI-based agro-platforms make it possible to analyze each farmer’s situation individually by considering soil composition, water supply, weather forecasts, crop type, and market prices at the same time, then providing precise recommendations. This helps replace the blind approach of “it worked for my neighbor, so it will work for me too” with a culture of data-driven decision-making.
If AI-based platforms are widely introduced in the agricultural sector, farmers’ decisions will rely not on intuition and imitation, but on data and models. For example, a platform can accurately calculate which variety is suitable for a specific field, how much water is needed, and when fertilizer application will be most effective. This weakens the effect of Gresham’s Law because “cheap and wrong decisions” are pushed out by “high-quality decisions” based on digital analysis.
As a solution, it is important to introduce a standard agrotechnical checklist for each crop, make agronomic consulting a mandatory stage, test methods first through demo farms, encourage quality in the market, and develop a culture of analysis-based decision-making among farmers. At the same time, it is also essential to widely implement AI-based agro-platforms through cooperation between the public and private sectors.
In conclusion, the greatest risk in agriculture is not land or machinery, but a culture of making decisions without analysis. Real development becomes possible only when high-quality and scientifically grounded decisions prevail over blind imitation. In this process, artificial intelligence and digital agro-platforms will become the main drivers of the new agricultural economy.
Muhammadbobir Sultonov — Lead Specialist and Agro-Consultant at the UFarmer agro-platform, specialist in implementing digital agriculture and artificial intelligence technologies in the agricultural sector.
