-数字农业与人工智能创新路线图 助力全球农业粮食系统转型

微信扫码，打开到小程序

I Digital agriculture and AI innovation roadmap for global agrifood systems transformation Digital Agriculture and AI Innovation Roadmap For the Global Agrifood Systems Transformation II Required citation: FAO. 2025. Digital agriculture and AI innovation roadmap – For the global agrifood systems transformation. Rome. https://doi.org/10.4060/cd5956en The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or Products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. ISBN 978-92-5-139932-3 © FAO, 2025 © FAO, 2025 Some rights reserved. This work is made available under the Creative Commons Attribution- 4.0 International licence (CC BY 4.0: https://creativecommons.org/licenses/by/4.0/legalcode.en). Under the terms of this license, this work may be copied, redistributed and adapted, provided that the work is appropriately cited. In any use of this work, there should be no suggestion that FAO endorses any specific organization, products or services. The use of the FAO logo is not permitted. If a translation or adaptation of this work is created, it must include the following disclaimer along with the required citation: “This translation [or adaptation] was not created by the Food and Agriculture Organization of the United Nations (FAO). FAO is not responsible for the content or accuracy of this translation [or adaptation]. The original English edition shall be the authoritative edition.” Any dispute arising under this licence that cannot be settled amicably shall be referred to arbitration in accordance with the Arbitration Rules of the United Nations Commission on International Trade Law (UNCITRAL). The parties shall be bound by any arbitration award rendered as a result of such arbitration as the final adjudication of such a dispute. Third-party materials. This Creative Commons license CC BY 4.0 does not apply to non-FAO copyright materials included in this publication. Users wishing to reuse material from this work that is attributed to a third party, such as tables, figures or images, are responsible for determining whether permission is needed for that reuse and for obtaining permission from the copyright holder. The risk of claims resulting from infringement of any third-party-owned component in the work rests solely with the user. FAO photographs. FAO photographs that may appear in this work are not subject to the above-mentioned Creative Commons licence. Queries for the use of any FAO photographs should be submitted to: photo- library@fao.org. Sales, rights and licensing. FAO information products are available on the FAO website (www.fao.org/ publications) and print copies can be purchased through the distributors listed there. For general enquiries about FAO publications please contact: publications@fao.org. Queries regarding rights and licensing of publications should be submitted to: copyright@fao.org. III Acknowledgements The Food and Agriculture Organization of the United Nations (FAO) and the Office of Innovation would like to express its appreciation to the many people who provided advice and guidance during the preparation of this document. The development process of the document was coordinated by Erik van Ingen under the overall guidance of Henry van Burgsteden, Harinda Katugaha, Alessia Correani and Vincent Martin from FAO, following the Digital Agriculture & AI Innovation Dialogue with 96 participants. It was authored by Tristan Wiessalla and Anouk Habermacher from FAO, and Aymeric Thoillet and Eric Salobir from the Human Technology Foundation. Technical Inputs and revision have been provided by the Digital Agriculture & AI Innovation Working Group in FAO. Additional review and comments were provided by the Dialogue participants. IV Foreword Harnessing innovation to transform agrifood systems is now a necessity as the world approaches a critical juncture. Climate shocks, geopolitical volatility, natural-resource depletion and unstable markets are converging, just as the world must prepare to feed 9.7 billion people by 2050. Fortunately, this decade has also delivered exponential technological progress. The leap from traditional machine learning to powerful, affordable artificial intelligence (AI), especially generative models such as large language models (LLMs), has unlocked technology to non-technical and offline users and set adoption records. In agriculture, this progress can empower all stakeholders, from farmers and agronomists to extension workers, researchers and policymakers. AI can be used to enable precision-farming, expand access to data and markets, help address climate-change related crises, and gather data and exchange regional know-how for the benefit of their communities. Recent gains in model accuracy, the falling cost of cloud computing and the ubiquitous use of smartphones, satellites and edge devices have moved AI from specialized, large-scale laboratories into handheld devices in the field. Hyper-local weather alerts, crop-specific input optimization and real-time market intelligence are already possible, even with sparse or noisy data, and are accessible to farmers through voice interfaces in local dialects. Yet these benefits can only materialize where robust governance, secure data stewardship, interoperable standards and continuous capacity development are built into AI enabled services. Designing AI for diverse cultural, linguistic and agrifood settings offers a unique chance to create solutions that generate lasting value, but success will depend on data policies that earn trust, on partnerships that share risk and reward equitably, and on demand-driven innovations that address actual local needs of farmers and governments. Lessons from earlier digital agriculture investments underscore the need to escape data silos, design with users in mind, strengthen infrastructure, build digital skills, work through multilateral frameworks and leverage open standards (e.g. findable, accessible, interoperable and reusable [FAIR] data principles [FAIR Process Framework]). To effectively tackle these challenges, the FAO’s Office of Innovation convened the Digital Agriculture and AI Innovation Dialogue in Rome from 28 to 30 April 2025. This event brought together more than 90 experts from various sectors, including public and private sectors, research and academia, development partners, investors and civil society. Insights from the dialogue have been distilled into this Digital agriculture and AI innovation roadmap (hereafter “AI roadmap” or “roadmap”). This document delivers two core concepts. The first is an inclusive platform whose architecture delivers value through its four elements, namely, missions and use cases, an innovation methodology, the community of people and partners, and a streamlined set of services. The second core concept guiding the roadmap’s implementation are the principles which ensure that impact is not single-sided but rather a holistic practice that brightens the community we aim to serve and the planet. These concepts are meant to truly improve the success rate of these initiatives and maximize the value creation and the reusability of digital assets whilst adopting common technical standards. The AI roadmap is a hands-on guide for moving from centralized agrifood systems to local needs-based, safe, interoperable, scalable and inclusive innovation initiatives and approaches. This work was presented at the Science and Innovation Forum during the World Food Forum in October 2025. Turn intent into impact by joining the community, supporting our initiatives, requesting one of our