According to Inc42 & StarAgri’s Indian Agritech Market Landscape Report 2025, India’s agritech market is projected to grow from $9 Bn in 2025 to $28 Bn by 2030, as the sector moves beyond farm-level pilots into infrastructure-led models spanning storage, financing and market access
Market linkage is emerging as the largest agritech value pool, with post-harvest infrastructure, logistics and buyer access expected to contribute ~45% of agritech value by 2030; scaled platforms such as StarAgri, DeHaat, Ninjacart and Samunnati are consolidating control across the seed-to-shelf value chain
AI is becoming one of the fastest-growing agritech sub-segments, scaling from ~$900 Mn in 2025 to $5.6 Bn by 2030, with adoption concentrated in yield forecasting, water optimisation, credit underwriting, insurance and price discovery, improving predictability and decision-making in a sector shaped by volatility and thin margins
India’s economic momentum has few parallels globally. Even as major economies slow, India is expected to remain the fastest-growing large economy in FY26, with GDP growth projected at 6.6%. Much of the public conversation has stayed focused on digital-first sectors — fintech, SaaS, consumer internet, and now AI. But the country’s most consequential transformation is unfolding in Agritech, a sector far older and far larger.
Agriculture and allied activities still employ 46% of India’s workforce and underpin rural income, consumption, and export competitiveness. And while agriculture is often framed as a low-growth, low-innovation sector, the last few years tell a different story. Despite climate volatility and supply-chain disruptions, agriculture’s Gross Value Added rose to $290 Bn in FY25, up from $277 Bn a year earlier. Exports have continued to climb as well, touching nearly $49 Bn, driven by India’s leadership in staples such as rice, spices, marine products, sugar, tea, and coffee.
What is changing, however, is not the scale of agriculture; it is the structure. Formal credit is steadily replacing informal finance, data is beginning to shape on-farm decisions, and technology is embedding itself across production, storage, financing, and market access. Platforms such as DeHaat and AgroStar are formalising input access and advisory at the farm gate, while players like StarAgri and Arya.ag are institutionalising post-harvest storage and collateral-backed financing. Together, these shifts mark the transition of agritech from isolated tools to system-level infrastructure.
According to Inc42 and StarAgri’s Indian Agritech Market Landscape Report, 2025, India’s agritech market will grow from $9 Bn in 2025 to $28 Bn by 2030, expanding at a 25% CAGR. In a $452 Bn agricultural economy, that may appear incremental. But the number masks a deeper shift: agritech is moving from scattered pilots to system-level infrastructure.
Despite strong growth, agritech today accounts for just about 2% of India’s overall agriculture market — a share expected to rise to only 5% by the end of the decade. This is not because technology lacks relevance on the farm. It is because Indian agriculture is structurally difficult to digitise at scale.
Nearly 69% of Indian farmers operate on less than one hectare of land. Farm incomes are seasonal and volatile. Digital literacy varies sharply across regions. Connectivity remains inconsistent beyond large rural clusters. In such an environment, adoption risk is high and tolerance for experimentation is low. For most farmers, a wrong decision is a livelihood risk.
This is why agritech adoption has largely been concentrated among progressive, capital-ready farmers and organised institutions. Early adoption has been strongest among farmers linked to FPOs, organised supply chains, or platforms such as Samunnati and Jai Kisan, where credit, procurement, and market access are bundled. For the vast majority of smallholders operating outside these networks, the perceived risk of adopting new technology remains high.
At the same time, the foundations for broader adoption are quietly strengthening. Institutional credit penetration among farmers has nearly doubled over the past decade, rising from 37% in FY11 to 68% in FY24. This shift has enabled agri-fintech players such as Samunnati, Jai Kisan, and Arya.ag to design bundled offerings where credit, insurance, warehousing, and market access travel together — reducing risk for both farmers and lenders, and improving unit economics across the value chain.
The workforce itself is also changing. Women now account for 64% of agricultural employment, up from 57% in FY18, as male labour migrates toward construction, trade, and services. This demographic shift is reshaping how agricultural decisions are made at the household level — and will increasingly influence how agritech platforms design interfaces, delivery models, and trust mechanisms.
As agritech platforms scale across credit, storage and market linkage, AI is increasingly shaping how decisions are made across the farm value chain.
If formal credit is one pillar of this transformation, artificial intelligence is emerging as the sharpest catalyst. AI-led agritech is growing significantly faster than the rest of the sector, with market size projected to expand from $900 Mn in 2025 to $5.6 Bn by 2030 — a 44% CAGR, nearly double that of the broader agritech market. By the end of the decade, AI is expected to account for roughly 20% of total agritech value.
The sector is moving away from isolated digital tools toward integrated stacks that begin with data acquisition — through sensors, drones, satellite imagery, and connected devices — and flow into AI-driven analytics engines. Companies such as CropIn and Fasal are using satellite intelligence and farm-level data to power yield forecasting, crop health monitoring, and climate-risk assessment, while drone-focused platforms like Dhaksha Unmanned Systems and AquaConnect are enabling high-frequency field intelligence in aquaculture and agriculture alike.
The impact is already visible across verticals. Agri-fintech platforms are using satellite imagery and behavioural signals to offer alternative credit scoring, parametric insurance, and dynamic input pricing. Precision agriculture tools are achieving yield prediction accuracy of up to 90% while improving water efficiency by as much as 80%. Digital advisory platforms are deploying multilingual conversational AI to deliver personalised guidance at scale — filling gaps left by India’s overstretched extension systems.
Yet this AI-led acceleration also exposes a dual reality. While AI-native platforms are driving most of the innovation and attracting investor attention, nearly 80% of agritech adoption still relies on simpler digital tools, from soil mapping and weather APIs to basic input commerce. Advanced AI remains concentrated among larger or more organised farming clusters.
The next challenge is not building better models, but designing AI systems that are affordable, explainable, and usable for India’s most constrained farmers — without breaking unit economics.
India’s agritech ecosystem today is fragmented by design. Since 2014, startups in the sector have raised over $2.9 Bn, yet there are no agritech unicorns and only six soonicorns. Exits remain scarce. Agritech accounts for less than 1% of India’s total startup M&A activity, and no company from the sector has gone public so far.
Long gestation cycles, asset-heavy models and seasonal cash flows have made agritech exits structurally slower than consumer or SaaS startups.
This lack of exits has had a chilling effect on capital, even as the strategic relevance of agritech continues to rise. But fragmentation may be a phase rather than a permanent state.
Where value is likely to concentrate is becoming clearer. Market linkage — spanning warehousing, logistics, financing, and digital marketplaces — is expected to account for nearly 45% of agritech value by 2030. Platforms such as Ninjacart, Vegrow, StarAgri, and Arya.ag are already demonstrating how control over aggregation, storage, and buyer access directly improves farmer income and platform margins.
Startups that can control the full seed-to-shelf stack — integrating production intelligence, post-harvest infrastructure, financing, and demand access — will build the deepest moats. These platforms are better positioned to monetise data, smooth farmer cash flows, and defend margins in a low-frequency, seasonal market.
The next phase of Indian agritech will therefore be defined less by point solutions and more by integration. Winning platforms will look less like apps and more like infrastructure — AI-native at the core, financially embedded, and operationally grounded in the realities of Indian agriculture.
The hype cycle around agritech may have cooled, but the underlying shift is accelerating. As credit formalises, AI matures, and market linkages strengthen, agritech is moving toward a slower, deeper, and more durable transformation — one that is less about digitising farming, and more about rebuilding agriculture as an integrated economic system.