世界经济论坛-印度的未来农业_扩大农业人工智能的剧本（英）-2025_55页_12mb

Future Farming in India: A Playbook for Scaling Artificial Intelligence in Agriculture

Core Content

This report, Future Farming in India: A Playbook for Scaling Artificial Intelligence in Agriculture, outlines a comprehensive strategy for integrating artificial intelligence (AI) into the agricultural sector in India, aiming to enhance productivity, profitability, and resilience for smallholder farmers. It is developed in collaboration with BCG X and the World Economic Forum, drawing on insights from policymakers, researchers, agribusiness leaders, and farmers themselves.

Main Viewpoints

The Role of AI in Agriculture

• AI is positioned as a transformative tool that can address systemic challenges in Indian agriculture, including low productivity, fragmented landholdings, limited financial access, and climate vulnerability.
• The global AI market is expected to grow significantly, reaching $1.8 trillion by 2030, indicating a growing opportunity for AI in agriculture.
• AI applications have already shown promising results in pilot projects, such as improved yields, higher unit prices, and reduced input costs.

Challenges in AI Adoption

• Less than 20% of Indian farmers use digital technologies, including AI-based solutions, due to low income, lack of digital literacy, and perceived risks.
• Smallholder farmers, who make up 85% of India's 150 million farmers, face additional barriers due to small and fragmented landholdings.
• The absence of institutional mechanisms for validating AI solutions before deployment increases the perceived risk for farmers.

Key Information

The Need for an AI Playbook

• The report emphasizes the need for a structured framework to guide the development of an AI ecosystem in agriculture.
• The playbook is designed to help policymakers, agribusinesses, agritech start-ups, and development organizations operationalize AI solutions effectively and at scale.

The IMPACT AI Framework

• The framework is built around three pillars: Enable, Create, and Deliver.
• Enable: Focuses on creating an enabling environment through supportive policies, digital infrastructure, and data-sharing frameworks.
• Create: Encourages innovation through collaboration between start-ups, researchers, and farmers to develop context-specific AI solutions.
• Deliver: Ensures that AI solutions reach the last mile by strengthening extension systems and farmer networks, and by establishing feedback loops for continuous improvement.

AI Use Cases

• AI-enabled crop planning: Helps farmers make data-driven decisions on crop selection and planting times.
• AI-enabled soil-health analysis: Provides rapid and accurate assessments of soil conditions to optimize fertilization and irrigation.
• AI-enabled pest prediction and control: Enables early detection and proactive management of pest infestations.
• AI-enabled smart marketplaces: Enhances market access and provides real-time pricing and demand insights.

Strategic Alignment

• The playbook aligns with ongoing initiatives in India such as the IndiaAI Mission, Agri Stack, and state-led AI programs.
• It aims to inspire coordinated action among governments, private enterprises, and civil society to build an inclusive and scalable AI ecosystem in agriculture.

Conclusion and Call to Action

• The report is not just a toolkit but a call to action for stakeholders to collaborate in building an AI-driven agricultural ecosystem.
• It highlights the importance of creating an enabling environment, fostering innovation, and ensuring the accessibility and affordability of AI solutions for farmers.
• The report encourages stakeholders to reflect on its insights and adapt its recommendations to their unique contexts, ensuring that AI's benefits reach every farmer and stakeholder.

Next Steps

• The report includes models and templates to guide the implementation of AI solutions.
• It also outlines a repository of AI use cases in agriculture and an assessment of critical datasets for AI in the sector.

Appendices

• Appendix 1: The Agriculture Expert Group
• Appendix 2: AI for India 2030 Advisory Council
• Appendix 3: The stakeholders matrix
• Appendix 4: A repository of AI use cases in agriculture
• Appendix 5: An assessment of critical datasets for AI in agriculture

Contributors and Endnotes

• The report is contributed by a diverse group of experts, including policymakers, researchers, and industry leaders.
• It includes endnotes and references to support the findings and recommendations presented.