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Submitted at the end of 2025 to the Ministry of Agriculture, Food and Sovereignty, a report from the General Council for Food, Agriculture and Rural Areas (CGAAER) presents a clear finding: artificial intelligence is set to play a structuring role in the future of French agriculture and agri-food. In a sector under significant pressure – generational renewal, adaptation to climate change, increased sustainability demands – AI appears as a lever capable of reconciling economic performance, agroecological transition, and maintaining food sovereignty.
Titled Artificial Intelligence in Service of Agriculture and Agri-food, the report adopts a resolutely pragmatic approach. It does not aim to promote an abstract innovation, but to identify concrete uses likely to transform the daily lives of farms. Among them, reducing administrative burdens occupies a central place. Regulatory declarations, reporting required by downstream sectors, technical-economic monitoring: all time-consuming tasks that AI technologies can automate or simplify, allowing farmers to refocus on their core business.
Beyond these operational gains, the report highlights a broader strategic issue. France has solid assets to structure a range of digital solutions tailored to its sectors and territories: abundant public data, a recognized research ecosystem, a network of startups and engaged agricultural actors. However, this opportunity comes with a clearly identified risk: an increasing dependence on technologies and models designed from foreign data, potentially disconnected from French agronomic, economic, and territorial realities.
The report does not limit itself to diagnosis. It proposes a series of concrete measures to initiate a genuine scaling-up. Among the key recommendations is the launch of a National Grand Challenge "AI for Agriculture", inspired by public initiatives that have already proven effective. The goal is to finance and accelerate decision-support solutions that combine economic and environmental performance, reduce administrative paperwork, and modernize agricultural equipment through embedded intelligence.
Another key lever: the priority opening of public agricultural data via a government reference platform, to enable the training of algorithms and the development of solutions truly adapted to the French context. The report also emphasizes the need to territorialize the deployment of digital tools, through the creation of a network of local support centers, particularly linked to agricultural high schools and coordinated with existing initiatives. These places would aim to test tools in the field, share feedback, and train future operators through attractive formats, such as interactive workshops or "AI cafés".
Finally, training appears as a central pillar of the proposed strategy. The integration of digital tools into agricultural curricula, the upskilling of advisors, and the strengthening of links between public research, education, and startups are identified as essential conditions for effective and controlled dissemination of uses.
For investors, the report sends a clear message: the integration of artificial intelligence technologies into agricultural systems is entering a structured acceleration phase, but is still largely open on the entrepreneurial front. The sector benefits from both enhanced public support and a growing demand from farmers for simple, robust, and immediately operational tools. In other words, the market is no longer emerging, but it is not yet saturated.
The report explicitly cites several actors illustrating the growing maturity of the French ecosystem. This is notably the case of Dilepix, whose computer vision solutions applied to livestock allow for continuous monitoring of animals and early detection of pathologies, or Chouette, specialized in the early detection of vine diseases and supported by public funding. These examples demonstrate already operational uses integrated into the field.
Beyond these references, the report highlights a favorable context for the emergence and structuring of agritech startups focused on robotics, data collection, decision support, or technical-economic management of farms. French actors in the ecosystem illustrate this entrepreneurial dynamic by developing solutions that combine agronomic, climatic, and economic data to assist operators in their strategic choices.
The challenge for these companies is no longer solely technological. Value creation now relies on their ability to integrate into existing ecosystems – cooperatives, chambers of agriculture, advisory networks – and to offer interoperable, ergonomic solutions compatible with French and European regulatory frameworks. In this perspective, public action, through initiatives like the National Grand Challenge "AI for Agriculture", plays a role in seeding and risk reduction, supporting experimentation and scaling without replacing economic models.
In a context of enhanced food sovereignty and increased attention to data control, agritech startups thus appear as key players in the competitiveness of French agriculture, offering investors medium-term return prospects on sustainable, localized solutions aligned with public priorities.
Internationally, strategies diverge significantly. The United States favors a very structured approach around data infrastructure and the role of major tech players. China is advancing rapidly with centralized state plans integrating AI on a large scale to secure its food supply. India, for its part, focuses on inclusive and low-cost tools, primarily targeting smallholders and climate adaptation.
In the face of these models, the French trajectory outlines an intermediate path. More balanced, more territorial, and clearly human-centered, it is technologically ambitious but deeply rooted in the realities of farms and sectors. Without explicitly elevating European sovereignty as a political objective, the report lays the groundwork for agricultural competitiveness based on data mastery, tools, and uses. An essential condition for French agriculture to remain in control of its digital transformation.
