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On 27 March 2025, over 200 experts convened for a Commission workshop focused on impactful AI-based solutions for agriculture. A key objective was to identify both established and emerging AI technologies that address sector-specific needs, as well as gaps in the current market.
Participants - including industry leaders, sectoral representatives, start-ups, scientists and policy-makers – also explored key challenges and enabling factors essential for integrating AI effectively within the agricultural sector. Insights from this workshop will directly contribute to the Commission’s ongoing initiatives, particularly on “Apply AI”.
CEOs presented their evolving AI use cases, highlighting critical aspects such as data requirements, model scalability, and socio-economic and environmental impacts. Experts, including representatives from manufacturing, agriculture, cooperatives, and European Digital Innovation Hubs, shared insights and practical experiences on how to fully unlock the potential of AI.
AI is already enhancing the sector’s competitiveness and environmental performance, while also reducing administrative burdens. In particular, AI applications in precision farming and decision-support systems are actively reshaping agricultural production. For instance, drone-based precision farming techniques can provide targeted solutions for specific agricultural problems. Multi-year and multi-layer field potential maps, derived from remote sensing, topography, and soil data, offer a comprehensive strategy. Both approaches have the potential to reduce agricultural inputs, such as herbicides, by around 30%. However, stakeholders along the agricultural value chain in other regions appear to be more advanced. Moreover, AI-based solutions tend to be predominantly adopted by larger farms or bigger enterprises within the supply chain.
Significant untapped potential was identified for AI applications in risk management, the development of digital twins, and the use of Generative AI (GenAI) to reduce administrative burdens, enhance farmer education and improve advisory services.
Challenges identified for AI in the sector include the handling of legislation at EU and national levels, limited capacities of end users to effectively adopt AI-based solutions and ensuring access to sufficient data – in terms of both quality and quantity. For example, the lack of consistent data formats across EU Member States was shown to increase the costs of service providers delivering data-driven solutions. It was further discussed that implementing an AI-based agricultural domain model could significantly reduce interface development efforts from 1,687 person years to just 46 person-months.
Trust emerged as a pivotal factor in agriculture AI, encompassing both confidence in AI systems and readiness to share data crucial for AI development. In this context also the potential of regulation in creating conditions that foster a reliable market of safe AI applications was highlighted.
To accelerate the development and adoption of AI-based solutions, specific actions were proposed, such as enhancing interoperability among geospatial datasets to reduce the productions costs of AI-driven services, establishing a digital Farm ID, and implementing the Common European Agricultural Data Space.
Next steps
A workshop report will be published soon. The results of the event will be considered in the development of the “Apply AI Strategy” expected in 2025.
Read further information in the documents below.