世界银行-利用人工智能进行农业转型（英）

Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedTable of Contents1. Why Artificial Intelligence for Agriculture Sector 2. Foundational Domains for AI in Agriculture: Conditions, Challenges, and Opportunities Connectivity and Energy Infrastructure: The Physical Backbone Data Ecosystems: Fueling AI with Local Intelligence Human Capital and Digital Literacy: Equipping the Frontline Governance and Policy: Building a Framework for Trust and Scale Public-Private Ecosystems: Scaling Sustainably 3. Applications of AI in Agriculture Crop and Livestock Discovery Advisory and Farm Management Inclusive Finance and Risk Mitigation Markets, Distribution, and Logistics Cross-Cutting Applications 4. Investment Priorities Agriculture-Specific AI Models and Capacity Foundational Data Investments Compute Infrastructure Investments Policy and Governance Investments Forward Look: Advancing Agrifood Transformation through Responsible AI Call to action AppendixSelected Case Studies12 202123 232526293135414551575860626768692List of AcronymsACREAgriculture and Climate Risk EnterpriseADENsAgricultural Data Exchange NodesADTAgricultural Development TrustAEZAgro-Ecological ZonesAIArtificial IntelligenceAICCRAAccelerating CGIAR Climate Research in AfricaAIEPAgricultural Information Exchange ProgramAGROVOCAgricultural Vocabulary (by FAO)AGRISInternational System for Agricultural Science and TechnologyAPIApplication Programming InterfaceBLSBrown Leaf Sp