AI in Agriculture 2025–2026: Market Growth, Government Initiatives, and Future Scope

 The content has been updated with the latest available data as of early 2026, incorporating recent market projections, government initiative developments, and refined emphasis on ongoing trends. Revisions include adjusted market figures based on prominent reports (e.g., from BCC Research, Grand View Research, and Mordor Intelligence), updated details on Indian initiatives, and enhanced clarity on drivers and implications.

Artificial Intelligence (AI) is rapidly reshaping the agriculture sector worldwide. Between 2025 and 2026, AI-driven technologies have become essential tools for improving productivity, sustainability, and profitability in farming.

The global AI in agriculture market is projected to grow from approximately USD 2.8 billion in 2025 to USD 8.5 billion by 2030, reflecting a compound annual growth rate (CAGR) of around 25.1%. Alternative estimates range from USD 2.55 billion in 2025 to USD 8.39 billion by 2031 (CAGR of 21.97%), or higher figures such as USD 9.55 billion by 2030 (CAGR of 25.5% from 2024 base). This robust growth is driven by advancements in precision farming, predictive analytics, climate-resilient practices, and the imperative for sustainable food systems amid population growth and resource constraints.

AI in Indian Agriculture

India continues to emerge as a significant adopter of agri-AI solutions. Key government-led initiatives include the Digital Agriculture Mission (with ongoing implementation, including the Krishi Decision Support System launched in 2024 and AgriStack for integrated farmer data), the IndiaAI Mission (with a total outlay of ₹10,372 crore over five years and ₹2,000 crore allocated for 2025-26), and dedicated Centres of Excellence in AI for agriculture (alongside health, sustainable cities, and education). These programs focus on digitizing farm data, enhancing evidence-based decision-making, and supporting small and marginal farmers through scalable innovations.

AI technologies—such as satellite imagery, drones, IoT sensors, and machine learning models—are increasingly deployed to predict crop yields, enable early disease detection, optimize irrigation, minimize input costs, and improve overall farm management. India's AI in agriculture market, though smaller in absolute terms (e.g., estimates around USD 55-70 million in 2024, with projections to USD 109-350 million by 2030-2033 at CAGRs of 12-19.5%), benefits from rapid policy support and localized applications tailored to smallholder contexts.

Why AI Matters for the Future

With escalating population pressures, climate variability, and resource limitations, traditional farming methods are insufficient on their own. AI facilitates data-driven decision-making while integrating seamlessly with indigenous agricultural knowledge, fostering a hybrid model that enhances resilience and efficiency. This approach is poised to define the future of agriculture in India and globally, promoting higher yields, reduced environmental impact, and greater economic viability for farmers. Continued investment in infrastructure, data ecosystems, and inclusive deployment will be critical to realizing this potential at scale.