AI in Agriculture Market to Reach $20.96 Billion by 2035 at 23.06% CAGR | IBM, Microsoft, Bayer Among Key Players

The global AI in agriculture market, valued at USD 2.14 billion in 2024, will climb to USD 20.96 billion by 2035, advancing at a compound annual growth rate of 23.06% over the forecast period. The scale of that growth reflects how urgently the sector needs technology-driven solutions: the Food and Agriculture Organization reported in 2023 that more than 259 million people faced acute hunger globally, and conventional farming methods simply cannot close that gap alone.

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Market Overview: Feeding a Growing World with Smarter Farming
Artificial intelligence is moving from an experimental add-on to a core operational layer across the agriculture value chain. Machine vision systems inspect crops for disease in real time, predictive models optimize irrigation schedules down to individual field zones, and autonomous robots handle planting and harvesting tasks that chronic labor shortages have made difficult to staff. The economic case for adoption is no longer speculative; it is measurable in reduced input costs, higher yields, and lower post-harvest losses.

Momentum from the private sector is accelerating this shift. In May 2024, Agritech startup Fyllo raised USD 4 million, led by IndiaQuotient and SIDBI Ventures, to build out its AI-powered precision agriculture platform. That same month, Niqo Robotics of Bangalore secured USD 13 million in Series B funding to scale its AI-driven spot-spraying technology for smallholder farmers. Bayer reinforced that commercial direction in March 2024, releasing a generative AI tool that delivers rapid agronomic guidance to farmers and field advisors, a development that signals how mature the technology has become for practical, farm-level deployment.

Key Growth Drivers
Rising food demand and a shrinking resource base. The global population continues to grow while arable land, freshwater, and labor supply face increasing strain. AI systems give farmers the analytical tools to produce more output from the same acreage by optimizing every variable from seed selection to harvest timing.

Machine learning maturity and data availability. Satellite imagery, IoT soil sensors, and weather data streams now feed machine learning models that can predict crop stress weeks before it becomes visible. The machine learning segment held approximately 40% of the AI in agriculture market share in 2024 and is projected to grow at a 26% CAGR, the fastest rate among all technology categories, reflecting how central these analytical capabilities have become to next-generation farm management.

Robotics and automation filling labor gaps. Autonomous agriculture robots capable of targeted spraying, fruit picking, and soil sampling are moving from pilot programs into commercial deployment. Advancements in computer vision and embedded AI are making these systems accurate enough to operate at scale, and the agriculture robot application segment is on track to expand at a 25.28% CAGR through 2035.

Strategic investment and startup activity. Venture capital, government grants, and corporate R&D budgets are flowing into agricultural AI at a pace not seen in prior decades. Garuda Aerospace's September 2024 partnership with Agrowing, focused on AI-guided drone surveillance for Indian crop fields, illustrates how public-private collaborations are translating investment into deployed solutions.
Government initiatives accelerating digital agriculture. Google introduced its Agricultural Landscape Understanding tool in July 2024, providing farmers in India with granular data on drought exposure, irrigation options, and crop planning. National programs across North America and Asia are co-funding similar efforts, lowering the adoption cost for smallholder operators who would otherwise be priced out of enterprise-grade technology.

Market Segmentation: Software Leads, Hardware Grows Fastest
By component, software accounts for nearly 48% of current market share, a position earned through its role in enabling data-driven crop management, yield forecasting, and resource allocation across large and small operations alike. The hardware segment, which includes sensors, drones, and robotic platforms, is forecast to outpace software on a CAGR basis through 2035, as falling unit costs for embedded AI chips and actuators bring automation within reach of mid-scale operators.

By application, precision farming commands 25% of the market and continues to anchor spending decisions at large agribusiness firms. Agriculture robotics, though currently smaller by revenue, is growing at 25.28% annually and is expected to be the fastest-expanding application category by the end of the forecast window. By enterprise size, large companies hold 65% of the market and are expected to maintain the highest growth rate, given their capacity to finance complex deployments and capture scale efficiencies.

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Regional Insights: North America Leads, Asia Moves Fastest
North America controls approximately 40% of the global AI in agriculture market, a position built on three durable advantages: the presence of major technology incumbents such as IBM, Google, and Microsoft; substantial government funding for agricultural innovation programs; and a dense ecosystem of research universities that supply both talent and commercially transferable IP. The United States, Canada, and Mexico together represent a mature demand base that is now moving from pilot adoption to enterprise-wide deployment.

Asia is the market's fastest-growing region. China and India are both scaling AI agriculture programs at the national level, backed by government mandates to modernize food systems and reduce dependence on chemical inputs. The Niqo Robotics funding round and Google's ALU tool deployment in India are concrete examples of the capital flowing into the region. As smallholder digitization programs gain traction across Southeast Asia and South Asia, Asia's share of total market revenue will narrow the gap with North America through 2035.

Competitive Landscape: Large Incumbents and Agile Startups
The AI in agriculture market includes AgEagle Aerial Systems, Bayer, Cisco Systems, Corteva, Deere & Company, Descartes Labs, Farmers Edge, Gamaya, Google, Granular, IBM, KUBOTA, Microsoft, OpenAI, Oracle, PrecisionHawk, Taranis, and Valmont Industries.

Large multinational firms currently dominate by revenue, using their balance sheets to fund R&D and negotiate data-sharing agreements with major agricultural cooperatives. At the same time, well-funded startups are carving out specialized positions in autonomous spraying, crop analytics, and livestock monitoring, areas where speed of iteration gives them an edge over slower-moving enterprises. The main competitive battlegrounds are proprietary datasets, hardware-software integration capability, and geographic reach in high-growth emerging markets.

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Contact Details
Gaurav Chaudhary
Email: Gaurav.chaudhary@rootsanalysis.com or sales@rootsanalysis.com
Website: https://www.rootsanalysis.com

About Roots Analysis
Roots Analysis is a global leader in the pharma / biotech market research. Having worked with over 750 clients worldwide, including Fortune 500 companies, start-ups, academia, venture capitalists and strategic investors for more than a decade, we offer a highly analytical / data-driven perspective to a network of over 450,000 senior industry stakeholders looking for credible market insights. All reports provided by us are structured in a way that enables the reader to develop a thorough perspective on the given subject. Apart from writing reports on identified areas, we provide bespoke research / consulting services dedicated to serve our clients in the best possible way.

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