"AI and IoT can transform Indian agriculture only if they are farmer-centric and interoperable." Discuss, with reference to recent global and national initiatives.

India's farm sector is made up mostly of smallholders, and it is now entering an AI phase. The AI advisory Bharat-VISTAAR was launched in 2026 [3]. New Delhi then hosted the second meeting of the UN's Global Initiative on AI for Agri-Food Systems (GI-AI4FS), which ITU coordinates with FAO, IFAD and WFP [1]. Technology will change farming only when it reaches the smallest cultivator and works across systems.

Transformative potential

• Precision farming: sensors, weather stations, drones and satellites linked to AI analytics can detect crop disease early and cut input costs [1].
• Supply chains: better traceability and fewer post-harvest losses [1].
• Advice at scale: Bharat-VISTAAR combines AgriStack, ICAR knowledge and IMD forecasts in one multilingual helpline [3].

Why farmer-centricity is decisive

• Inequality risk: FAO's "No Farmer Left Behind" agenda warns that AI used without regard to inequality can widen it [2].
• Exclusion: AgriStack has issued over 10.31 crore Farmer IDs, all built on digitised land records [4]. Tenants, sharecroppers and many women cultivators may stay invisible.
• Data rights: AgriStack follows the DPDP Act, 2023 and DPDP Rules, 2025. Data is shared only with consent, and each state owns its farmers' data in a federated registry [4]. However, consent from farmers with low literacy can be a formality.

Why interoperability is decisive

• Without common standards, apps, devices and state databases cannot exchange data. Farmers can also get locked into one vendor's equipment, which raises their costs.
• GI-AI4FS has set up Working Groups and priority work streams, and ITU's Standardization Bureau takes part [1]. Standards written early bind the countries that join late.
• The Digital Agriculture Mission (₹2,817 crore) is building shared digital public infrastructure: AgriStack, Krishi Decision Support System and soil maps. It covers tenant farmers where state policy allows [5].

Necessary, not sufficient

• Connectivity: rural internet access in developing countries lags well behind urban access [6]. IoT does not work without a signal.
• Soft governance: GI-AI4FS is voluntary and has no binding rules, so measurable results are still awaited [1].

Farmer-centric design and interoperability are therefore core conditions, but they also need rural connectivity and land data that includes every cultivator. India should offer its federated, consent-based model as a reference design in GI-AI4FS. It should also extend Farmer IDs to tenant farmers and pair AI pilots with rural broadband. That would advance SDG 2 (Zero Hunger) and make "No Farmer Left Behind" real.