Food security to income security

India stands at an inflection point in its agricultural trajectory. The well-known practices during the Green Revolution, which involved more fertilisers, deeper tube wells, and expansion of cultivated land, are giving diminishing returns. At the same time, the pressures on the agricultural sector are increasing to account for 52 per cent of our country’s employment. Unpredictable weather, depleted groundwater, and increased water demand result in inconsistent yields. As a result, climate change-induced agricultural losses will impact India's GDP every year. This will not only weaken rural consumption but increase inflation volatility. The economic consequences are flowing far beyond the farms, as other industries heavily depend on the agricultural sector.

It is in this context that NITI Aayog’s report, ‘Reimagining Agriculture: Roadmap for Frontier Technology-Led Transformation,’ is strategically relevant. The report not only discusses the applications of drones and sensors in the sector but focuses on the economic aspects of agriculture. From now on, productivity can be improved not through intense use of the inputs but through their intelligent and more efficient use.

This directs us to think differently about the issues, and not in terms of ‘business-as-usual’ like during the Green Revolution. The earlier transformation focused on scaling volume, i.e., producing more using more inputs of fertilisers, irrigation, and seed varieties to ensure food security. In contrast, a new ‘Digital Green Revolution’ focuses on precision, anticipation, and efficiency. Its purpose is to reduce waste, stabilise incomes, and build resilience while maintaining yields. Put simply, where the first farm revolution expanded quantity, the next and forthcoming must expand certainty and sustainability.

The economic argument for fertiliser subsidies is well known, yet marginal yield gains are stagnating. Groundwater extraction without much recharge, and fiscal pressure because of subsidies to pump water are pressing issues we cannot afford to ignore. These are the classic indications of diminishing marginal returns. Adding more similar agricultural inputs provides a smaller incremental benefit. The present model leads to a low-efficiency trap.

Frontier technologies, however, operate not at the margin, but at the frontier. Artificial Intelligence, predictive weather analytics, precision irrigation, sensor-driven soil diagnostics, and drone-based nutrient assessment, when combined, can yield better results. Cost-effective cultivation, and timely use will ensure better yields and quality, supporting the sustainable use of biotic and abiotic agri resources. They increase the efficiency of inputs simultaneously. Precision agriculture approaches that tailor fertiliser application to local conditions have been shown to reduce losses, cut costs, and sustain yields. In economic terms, this is productivity through intelligence, not volume. There are many stakeholders, which include agri-business, NGOs, agriculture departments, researchers, academicians, and politicians, who need to play specific and crucial roles in the new ‘Digital Green Revolution’.

Digital agriculture is not costless, and digital tools by themselves cannot transform farming systems. Hardware, connectivity, data infrastructure, maintenance, digital literacy, and service delivery create real economic costs, especially for the smallholders. A technology-first approach risks exclusion and under-utilisation. Digitisation must therefore be sequenced according to need, value, and local feasibility. Innovative business models such as pay-as-you-go, rental, community ownership, and others can come into play. Intelligence only produces impact when embedded in institutional capacity, farmer capability, extension reach, and trust networks. Only technology is necessary, but not sufficient. Without a supportive ecosystem, it becomes an expensive layer over old inefficiencies.

This logic highlights the Digital Agriculture Mission 2.0, focusing on three objectives: Enhancing information availability; reimagining resource use through technology, and; converging data systems. Each one of these focuses on a different economic inefficiency. Farmers face information asymmetry regarding soils, weather, pests, and markets. Correcting these failures has disproportionately high returns, reducing cost of cultivation. With customised advisory and real-time information, farmers can be empowered to make accurate and timely decisions with less agri-input resources.

This shift matters beyond the farms. Agriculture continues to employ nearly half of India’s workforce, and this reduced risk across the agri-value chain has an impact on the macroeconomy. Procurement costs, volatility in rural credit, and depressed consumption will be positively handled. In this sense, climate-smart agriculture is not merely a sectoral reform; it is a macroeconomic stabilisation policy. It strengthens inflation management, rural purchasing power, and the enabling environment for investments.

However, we need subsidies that reward optimum consumption. They should not promote soil degradation, groundwater depletion beyond permissible levels, or the mainly unsuitable use of resources. That means rewarding verified improvements in water-use efficiency, soil health, nutrient-use efficiency, regenerative practices, and climate-risk reduction can show promising results. The shift toward outcome-based incentives rather than input-based approaches is the key.

Financing and business models will be some of the drivers of success. A technology transition fails if farmers bear capital risks alone. Smallholders require reduced-risk pathways to adopt innovations. This includes climate-tech credit lines, rental, and subscription models. India’s experience in expanding solar adoption demonstrates how financial architecture can determine technological outcomes.

The NITI Aayog roadmap also calls for the creation of a unified National Agricultural Data Layer. Today, the data architecture around agriculture is fragmented: Soil information in one silo, land records in another, satellite intelligence in a third, and mandi prices elsewhere. The integration of this information is the key. Stakeholders like agricultural universities, startups, FPOs, cooperatives, and state agencies can play their roles to make it happen. India has done this before. The UPI model demonstrates how a public digital infrastructure can democratise access to digital transactions and support governance. Agriculture can experience a similar innovation wave if a suitable ecosystem is in place.

None of this is to downplay the institutional challenge. The adoption of frontier technologies must avoid repeating the mistakes of the Green Revolution. Instead, digital agriculture must accommodate regional differences, traditional knowledge systems, and socio-cultural contexts. The Digital Green Revolution can convert unpredictability into manageable situations. Its aim is intelligent, stable, climate-resilient farming.

India cannot achieve sustainable development if its farm economy remains structurally fragile. Also, we cannot eliminate the consumer-driven market in agriculture, such as traceability using blockchain technology. The world is moving from data-driven agriculture (Agriculture 4.0) to AI- and robotics-based agriculture (Agriculture 5.0), and India cannot stay away from this progress. A digitally empowered agriculture sector supported by socio-economic constraints is the way forward. The first Green Revolution delivered food security, which was crucial for the country’s survival. The second in the form of the Digital Green Revolution needs to effectively and efficiently deliver income security, which is the need of the day.

Saruparia is Director, Centre for Economics, Law and Public Policy, National Law University; Wadghane is Assistant Professor, Symbiosis Institute of Operations Management; views are personal