In recent years, the impact of climate change, such as extreme heat and guerrilla rainstorms, has made crop growth unstable, leading to continued surges in market prices. Even veteran producers with years of experience and intuition are frequently facing extreme weather that cannot be handled by conventional know-how alone. Furthermore, the average age of agricultural workers at production sites has reached approximately 68.7 years, leading to a serious shortage of successors and labor. AI agriculture (smart agriculture), which utilizes AI, IoT, and robotics, is expected to be the trump card for solving the dual challenges of harsh natural environmental changes and labor shortages, and for building a stable food supply system.
Currently, AI agriculture has moved beyond demonstration experiments and is producing concrete results in fields and facility horticulture across the country.
(1) Refinement of predictions through data analysis and precision cultivation management
For example, systems that use AI to analyze vast amounts of information obtained from weather data and soil sensors to predict harvest yields up to several weeks in advance with high precision have been put into practical use. This enables planned shipments that anticipate the balance between supply and demand, contributing significantly to the reduction of stockouts, excess inventory, and food loss. In addition, technology that instantly identifies pests and diseases from images taken with smartphones or drones and sprays pesticides only where necessary is becoming widespread, making it possible to maintain quality while significantly reducing the amount of pesticides used.
(2) Substitution of harsh labor through robotics
In facility horticulture, where labor shortages are particularly acute, the introduction of robots that recognize fruit ripeness and obstacles with cameras and harvest fruit 24 hours a day without damaging it is progressing.
(3) Visualization and succession of skilled farmers’ know-how
By digitizing the work of veterans using smart glasses and AI cameras, even new farmers can judge the appropriate timing for fertilization and watering, significantly shortening the time required for human resource development.
Although AI agriculture brings innovative benefits, according to a survey by the Japan Finance Corporation, the adoption rate remains at about 45%, and there are still high hurdles to full-scale nationwide adoption.
The biggest barrier is the economic burden and the lack of a clear outlook on return on investment. Introducing systems and large smart agricultural machinery requires significant initial costs, and according to data from smart agriculture demonstration projects, it takes an average of 5.2 years to recover the investment. There are still not many farmers who can draw up a clear business plan that does not rely on subsidies and can recover profits within the useful life of the machinery.
In addition, the delay in infrastructure development caused by Japan’s complex terrain is also serious. Unlike countries like the Netherlands, where flat and large-scale environment-controlled agriculture has developed, Japan has many hilly and mountainous areas, and the shape and climatic conditions of each farmland vary, making standardization of systems difficult. In fact, the development rate of agricultural communication infrastructure in hilly and mountainous areas remains at about 23.7%, and there is a risk that cloud linkage and automatic driving will stop functioning if communication is interrupted.
Furthermore, there are new challenges that arise from increased reliance on technology. In addition to the lack of IT literacy in aging workplaces, there are concerns about BCP (Business Continuity Plan) risks where systems stop and operations completely halt in the event of power outages or communication failures due to extreme weather. In addition, security risks such as the leakage of accumulated valuable agricultural data due to cyberattacks and safety risks such as malfunctions of autonomous agricultural machinery have emerged, making the training of personnel who can correctly understand and manage technology an urgent task.
To overcome these challenges and evolve Japanese agriculture into a more resilient industry, efforts involving the government, local municipalities, and private companies are accelerating.
(A) Legal development and strong financial support by the government
With the Act on Promotion of Utilization of Smart Agriculture Technology enacted in October 2024, generous preferential measures such as tax incentives, long-term low-interest loans, and one-stop procedures for drone flights have begun for producers and development companies whose plans have been certified by the government. This is creating an environment where even small and medium-sized farmers can easily introduce the latest technology while suppressing economic risks through leasing and joint use.
(B) Utilization of AI breeding and promotion of environment-friendly agriculture
Linked with the government’s Strategy for Sustainable Food Systems (MIDORI), autonomous weeding robots using AI support the expansion of labor-intensive organic farming. Furthermore, technology has emerged that develops new varieties resistant to climate change (such as extreme heat) about five times faster than before using only AI data analysis without relying on genome editing, making the stable supply of crops that can adapt to extreme weather a reality.
(C) Shift to market-in (customer-oriented) agriculture
Not only weather and growth data, but also POS (sales performance) data held by retailers such as supermarkets is fed back to producers, and AI analyzes ‘what kind of crops are in demand at what price range now.’ This allows producers to perform waste-free planting that matches market demand, contributing to the optimization of the supply chain for the entire society.
AI agriculture is not about excluding humans from agriculture, but about freeing producers from unpredictable climate change and harsh physical labor, allowing humans to concentrate on higher value-added management decisions and unique brand building. Although challenges such as the weight of initial investment and undeveloped infrastructure remain, the barriers are steadily lowering due to policy support and industry-academia-government collaboration. When AI’s advanced analytical power is combined with the insights that producers have cultivated through years of facing agriculture, Japanese agriculture will leap into a sustainable and attractive industry that will be passed on to the next generation. Among major companies, Kagome’s tomato cultivation and Calbee’s potato cultivation are famous, and they are taking the lead in utilizing AI agriculture to stably supply materials for their flagship products. Currently, most are large companies with financial power due to introduction costs, but if the government provides preferential treatment such as subsidies, there is no doubt that Japanese agriculture will move forward if it can be expanded to general farmers. I hope the government will pay more attention to agriculture than it does now to protect domestic producers and reduce dependence on imports.
