Future Farming Revolution in India through Artificial Intelligence

Introduction

Future Farming Revolution in India through Artificial Intelligence: The Office of the Principal Scientific Adviser (OPSA) has released a report titled ‘Future Farming in India: AI Playbook for Agriculture’ under the AI for India 2030 initiative. This initiative is led by the Centre for the Fourth Industrial Revolution (C4IR) India, in collaboration with the World Economic Forum (WEF). It aims to build a responsible and inclusive AI ecosystem that empowers Indian agriculture through innovation and scalability.

Vision of AI for India 2030

Launched under the guidance of OPSA and MeitY, the AI for India 2030 initiative envisions embedding responsible and human-centric AI into India’s digital economy. The project focuses on developing frameworks that ensure inclusivity, transparency, and ethical deployment of artificial intelligence in critical sectors like agriculture.

Static GK fact: The Office of the Principal Scientific Adviser (OPSA) was established in 1999 to advise the Government of India on science, technology, and innovation policies.

Key Focus Areas in Future Farming

The report identifies major AI-driven use cases that can revolutionize Indian agriculture:

• Intelligent Crop Planning: AI tools analyze soil health, weather trends, market prices, and import–export data to recommend optimal cropping patterns.
• Smart Farming: Technologies such as satellite monitoring, pest prediction, rapid soil analysis, and automated machinery improve efficiency and reduce input costs.
• Farm-to-Fork Solutions: These ensure traceability, improve supply chain management, and enhance fintech adoption for market linkage and price prediction.

Static GK Tip: India’s agriculture employs around 44% of the workforce but contributes only about 18% to GDP, highlighting the need for technological modernization.

IMPACT AI Framework

The report introduces the Inclusive Multistakeholder Pathway for the Accelerated Convergence of AI Technologies (IMPACT AI) Framework. This three-pillar model guides AI ecosystem development:

1. Enable: Building digital public infrastructure (DPI), formulating AI policies, and promoting AI skill development.
2. Create: Developing innovative AI products, establishing AI sandboxes, and supporting startups.
3. Deliver: Empowering frontline extension systems, creating an AI marketplace, and increasing farmer awareness.

Static GK fact: The concept of Digital Public Infrastructure (DPI) became central to India’s governance model after the success of Aadhaar, UPI, and DigiLocker systems.

Challenges in AI Adoption

Despite promising frameworks, several challenges persist:

• Limited Technology Exposure: Less than 20% of Indian farmers use digital tools, limiting awareness and adoption.
• Financial Constraints: Low farmer incomes restrict affordability of AI-driven solutions.
• Land Fragmentation: Over 85% of farmers are smallholders with an average landholding of 08 hectares, posing scalability issues.
• Low Investment: AI requires heavy investment in infrastructure and human resources.
• Perception of Risk: Lack of institutional validation mechanisms makes farmers cautious about new technologies.

Static GK Tip: India has over 150 million farmers, most of whom depend on monsoon-based agriculture, making digital solutions crucial for resilience.

Conclusion

The ‘Future Farming in India: AI Playbook for Agriculture’ sets a blueprint for transforming Indian agriculture using AI-enabled innovation. With coordinated efforts between government, industry, and academia, India can achieve sustainable, data-driven, and equitable farming practices by 2030.

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Future Farming Revolution in India through Artificial Intelligence: