The 2025 World Economic Forum (WEF) report, “Future Farming in India: A Playbook for Scaling Artificial Intelligence in Agriculture”, under the AI for India 2030 initiative, presents a transformative roadmap.

• It positions Artificial Intelligence (AI) as a practical enabler for inclusive, sustainable, and data-driven agricultural growth.

Why India Needs an AI Playbook for Agriculture?

• Agriculture’s Economic Role: Agriculture remains the backbone of India’s economic and social stability, employing nearly 45% of the workforce and contributing about 18% to GDP.
• Key Challenges: India’s agriculture faces low productivity, fragmented landholdings, financial stress, and climate vulnerabilities—systemic bottlenecks that conventional reforms alone cannot resolve.
  • Low Technological Penetration: Less than 20% of farmers use digital tools for crop management or market access.
  • Fragmented Landholdings: Nearly 85% of the 150 million farmers are smallholders, with average land size barely 1.08 hectares, making precision technologies difficult to scale.
  • Data Silos: Agricultural data remain fragmented across ministries, states, and schemes, impeding interoperability.
  • Climate Volatility: Unpredictable rainfall, soil degradation, and pest outbreaks intensify income uncertainty.
  • Financial Limitations: Limited access to affordable credit and risk capital hampers adoption of innovative tools.
    • These challenges necessitate an integrated, multi-stakeholder approach—one that converges technology, data, and governance to empower smallholders through responsible AI.

Key Highlights of the WEF Report

• The report identifies three major domains where AI can reshape Indian agriculture:
• Intelligent Crop Planning: AI-driven systems analyse soil health, weather patterns, historical yields, and market data to recommend optimal cropping choices. 
  • This minimises resource waste and enhances climate resilience.
• Smart Farming: Includes satellite crop monitoring, decision-support dashboards, real-time soil and pest diagnostics, hyperlocal weather forecasting, yield prediction, and AI-guided farm machinery. 
  • Together, these innovations enable precise input use and predictive risk management.
• Farm-to-Fork Solutions: AI tools strengthen traceability, quality assurance, and market intelligence—forecasting demand, optimising supply chains, and improving price discovery. 
  • FinTech integration facilitates digital credit, insurance, and payments for smallholders.
  • Collectively, these innovations aim to build a farm-to-market AI ecosystem, integrating production, processing, and trade.

Guided by principles of public trust, inclusion, transparency, and safety, IMPACT AI operationalises “Impact AI”—measurable progress in productivity, income, and sustainability.

Methodology: From Research to Action

• The Playbook was co-developed by the Centre for the Fourth Industrial Revolution (C4IR) India, under the guidance of the Office of the Principal Scientific Adviser (PSA) and MeitY, with participation from NITI Aayog, ICAR, state governments, agritech start-ups, and academia.
• It followed a three-step approach:
  • Design Thinking: Mapping recurring farm challenges and ideating scalable AI interventions.
  • Expert Consultations: Gathering perspectives from agronomists, FPO leaders, and technology developers.
  • Contextual Analysis: Aligning solutions with smallholder realities—land size, credit access, local languages, and climate zones.
    • This participatory design ensures that AI adoption remains farmer-centric, ethical, and feasible.

Opportunities and Expected Impact

• Productivity Gains: AI-based advisories could enhance yields by 15–25% in pilot districts.
• Cost Reduction: Optimised fertiliser, pesticide, and irrigation use can reduce input costs by up to 20%.
• Income Stability: Data-backed credit scoring and insurance models reduce risk and improve access to finance.
• Climate Resilience: Predictive analytics strengthen adaptive farming and resource efficiency.
• Transparency: Blockchain and AI-driven traceability improve consumer confidence and export readiness.

Challenges in AI Adoption for Agriculture

• Despite progress, five major barriers constrain AI mainstreaming in Indian agriculture:
• Limited Exposure to Technology: Fewer than 1 in 5 farmers regularly access digital platforms or advisory apps.
• Financial Capability: The low and variable incomes of smallholders limit their ability to invest in AI tools.
• Land Fragmentation: The small average holding size prevents economies of scale in deploying AI-based machinery.
• Investment Deficit: AI infrastructure—data hubs, cloud services, broadband—requires heavy capital and policy continuity.
• Perception of Risk: Lack of validated, government-recognised sandboxes creates uncertainty for both innovators and users.
  • These barriers necessitate risk-sharing models, credit support, and a dedicated AI validation ecosystem for agriculture.

Institutional Alignment and National Initiatives

• The Playbook complements India’s broader digital and innovation ecosystem:
• IndiaAI Mission (2024): ₹10,300 crore initiative to expand computer infrastructure (10,000–38,000 GPUs), establish AIKosh (data repository), and support indigenous foundation models like BharatGen.
• Digital Agriculture Mission (2021–25): Enables integration of AI with AgriStack, improving farmer databases, precision farming, and policy targeting.
• PM-Kisan & PM Fasal Bima Yojana: Create data pipelines for predictive analytics and smart insurance design.
• Atmanirbhar Bharat & Startup India: Empower rural innovators and agritech start-ups to develop context-specific AI solutions.
• Krishi Vigyan Kendras & FPOs: Act as local nodes for awareness, field trials, and adoption of AI tools.

Global and Comparative Perspective

• China’s Smart Agriculture Program: Integrates AI, IoT, and drone technology for precision farming and supply-chain transparency.
• European Union’s CAP Digital Transition: Encourages AI-led monitoring and compliance using satellite data and predictive analytics.
• Africa’s Digital Agriculture Agenda: Uses AI to strengthen climate resilience and crop insurance for smallholders.
  • India’s IMPACT AI aligns with these global movements but emphasises a bottom-up, inclusion-first approach, focusing on smallholders and public trust rather than corporate consolidation.

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Way Forward

• Establish a National AI Governance Authority for Agriculture to standardise ethics, liability, and validation.
• Invest in AI Literacy: Integrate digital and data science modules in rural education and extension training.
• Encourage Public–Private Partnerships: Leverage agritech start-ups, cooperatives, and CSR investments.
• Create Interoperable Data Standards: Ensure privacy-preserving, consent-based sharing through AIKosh.
• Expand Sandbox Testing: De-risk innovation by allowing pilot experimentation under regulatory oversight.
• Promote Global Collaboration: Share best practices through the Global Partnership on AI (GPAI) and G20 Digital Agriculture Working Group.

Conclusion

The Future Farming in India Playbook signals a shift toward smart, sustainable, and inclusive agriculture. Responsible AI can empower 150 million farmers with insights, resilience, and market access, augmenting—not replacing—their knowledge and dignity.

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