India AI in Agriculture Market By Technology (Machine Learning, Predictive Analytics, Computer Vision), By Offering (Hardware, Software, AI-As-A-Service), By Application (Precision Farming, Livestock Monitoring, Others), By Region, Competition, Forecast & Opportunities, 2020-2030F
Published Date: August - 2024 | Publisher: MIR | No of Pages: 320 | Industry: Agriculture | Format: Report available in PDF / Excel Format
View Details Buy Now 2890 Download Sample Ask for Discount Request CustomizationIndia AI in Agriculture Market By Technology (Machine Learning, Predictive Analytics, Computer Vision), By Offering (Hardware, Software, AI-As-A-Service), By Application (Precision Farming, Livestock Monitoring, Others), By Region, Competition, Forecast & Opportunities, 2020-2030F
| Forecast Period | 2026-2030 |
| Market Size (2024) | USD 55.17 Million |
| Market Size (2030) | USD 109.30 Million |
| CAGR (2025-2030) | 12.24% |
| Fastest Growing Segment | Predictive Analytics |
| Largest Market | North India |
Market Overview
India AI in Agriculture Market was valued at USD 55.17 Million in 2024 and is anticipated to reach USD 109.30 Million with a CAGR of 12.24% during the
In India, the market for AI in agriculture is witnessing considerable growth. The integration of AI technologies into the agriculture sector has initiated a new era of farming known as 'precision farming'. Indian farmers are increasingly using AI-driven tools for tasks such as weather prediction, crop monitoring, and supply chain optimization. As the government of India continues to encourage digital agriculture, the AI in agriculture market is poised for further expansion.
Key Market Drivers
Increasing Population Pressure & Food Security Concerns
One of the primary drivers propelling the growth of the AI in agriculture market in India is the increasing population pressure and the associated concerns about food security. With a rapidly growing population, there is a heightened demand for food production to ensure an adequate and sustainable food supply. AI technologies offer transformative solutions to address the challenges of increasing agricultural productivity, optimizing resource utilization, and ensuring food security in the face of evolving demographic trends.
Expanding Technological Advancements and Improvements
The ongoing technological advancements and improvements in connectivity infrastructure contribute significantly to the growth of AI in agriculture in India. The availability of high-speed internet, the proliferation of smartphones, and the expansion of network coverage in rural areas enable the seamless integration of AI technologies into agricultural practices.
Farmers can access AI-driven applications and services through mobile devices, making it easier to deploy and utilize AI tools on the field. Cloud computing facilitates the storage and analysis of vast amounts of agricultural data, enabling real-time decision-making. The development of low-cost sensors and Internet of Things (IoT) devices enhances the data collection capabilities essential for AI applications in agriculture. The synergy between technological advancements and connectivity infrastructure creates an environment conducive to the widespread adoption of AI in Indian agriculture, fostering a more digitally connected and technologically empowered farming community.
Increased Climate Change & Weather Variability
The increasing impact of climate change and the resulting weather variability pose significant challenges to agriculture in India. Erratic rainfall patterns, temperature fluctuations, and extreme weather events can have profound effects on crop yields and overall agricultural productivity. This not only affects the livelihoods of farmers but also threatens food security in the country. In response to these challenges, AI technologies are playing a crucial role in mitigating the impact of climate change by providing farmers with advanced tools and solutions to adapt to changing environmental conditions. AI-driven predictive analytics and modeling help farmers anticipate weather patterns, identify optimal planting times, and make informed decisions about crop management practices. By analyzing vast amounts of historical weather data, machine learning algorithms can accurately predict future conditions, enabling farmers to implement adaptive strategies for climate-resilient agriculture.
AI offers actionable insights that can help farmers optimize resource utilization, reduce input costs, and minimize environmental impacts. For instance, AI-powered systems can optimize irrigation scheduling based on soil moisture levels, weather forecasts, and crop water requirements, thus conserving water resources and improving water-use efficiency. The ability of AI to offer these detailed and precise insights in the face of climate uncertainty positions it as a vital driver in enhancing the resilience of Indian agriculture. By empowering farmers with knowledge, AI is helping them navigate the challenges posed by climate change and work towards sustainable and productive agricultural practices.
Key Market Challenges
Farmer Awareness & Adoption
One of the primary challenges facing the AI in agriculture market in India is the limited awareness and adoption among farmers. Many farmers, particularly in rural areas, may not be familiar with AI technologies and their potential applications in agriculture. The complex nature of AI systems can pose a barrier to adoption, as farmers may perceive these technologies as unfamiliar and challenging to integrate into their traditional farming practices.
Affordability & Accessibility of AI Technologies
The affordability and accessibility of AI technologies present significant challenges in the Indian agriculture sector. Many farmers, especially smallholder farmers with limited resources, may find the upfront costs associated with acquiring and implementing AI solutions prohibitive. The high initial investment in AI hardware, software, and training can act as a deterrent to widespread adoption.
Key Market Trends
Automation & Robotics in Farming Operations
The adoption of automation and robotics in farming operations is a notable and transformative trend in the AI in agriculture market in India. With the integration of AI-powered robotics and automation systems, farmers are witnessing a revolution in the way tasks are performed across various stages of farming - from planting and harvesting to weed control and pest management.
Rising Smart Irrigation Systems & Water Management
Smart irrigation systems powered by AI are gaining significant traction in the Indian agriculture sector, particularly in regions grappling with water scarcity challenges. These advanced systems leverage AI algorithms to analyze crucial data points such as soil moisture levels, weather forecasts, and crop water requirements. By doing so, they optimize irrigation scheduling and ensure precise water application, thereby curbing water wastage and enhancing overall water-use efficiency.
Segmental Insights
Technology Insights
Based on the Technology, in the realm of Artificial Intelligence (AI) in India's agriculture sector, Predictive Analytics holds a dominant position due to its remarkable capabilities. This cutting-edge technology is being extensively adopted for forecasting weather conditions, analyzing crop yield predictions, and gaining insights into soil health. By leveraging historical data, Predictive Analytics empowers farmers and agricultural experts with actionable insights that help optimize decision-making processes. Its ability to handle the intricacies and challenges of the agriculture sector has led to its increasing prevalence, surpassing even Machine Learning and Computer Vision in this domain. With its potential to revolutionize agricultural practices, Predictive Analytics is poised to drive significant advancements and improvements in India's agriculture sector.
Offering Insights
Based on Offering, in the AI (Artificial Intelligence) in Agriculture market in India, it has been observed that AI-As-A-Service is the dominating segment. This can be attributed to the increasing adoption of cloud-based services, which provide farmers with the opportunity to access sophisticated AI solutions without the need for a substantial upfront investment. By leveraging this service model, even small-scale farmers are able to harness the power of advanced analytics and machine learning models to optimize their farming practices. This not only enhances productivity and efficiency but also contributes to the overall growth and success of the agricultural industry in India. As a result, the popularity of AI-As-A-Service continues to soar in this market, revolutionizing the way farmers approach their agricultural operations.
Regional Insights
The northern region of India, particularly the states of Punjab and Haryana, has emerged as a frontrunner in the adoption of Artificial Intelligence (AI) in agriculture. With its rich agricultural heritage and vast farming practices, the region has recognized the potential of modern technologies to revolutionize the sector. By embracing advanced farming methods and leveraging digital innovation, the government aims to boost productivity, ensure sustainability, and address the evolving challenges faced by the agricultural community. The adoption of AI in agriculture is not just limited to crop monitoring or yield prediction. It encompasses a wide range of applications, including soil analysis, pest management, irrigation optimization, and livestock monitoring. By integrating AI into these various aspects, farmers in the region are able to make data-driven decisions, optimize resource allocation, and improve overall efficiency.
Recent Developments
- In
July 2024, Google launched an AI-powered agricultural information tool for
India, designed to offer insights into drought preparedness and irrigation. The
tool, named Agricultural Landscape Understanding (ALU), aims to enhance
agricultural practices and boost crop yields by providing valuable data to
farmers. Initially available in limited regions, the tool is designed to make
agricultural practices more data-driven. According to Google, the new AI
platform will deliver detailed, granular information tailored to the unique
agricultural landscape of India. It will leverage high-resolution satellite
imagery and machine learning to define field boundaries and provide essential
data on drought management, irrigation, market access, and more.
- In September 2024, the Central Government announced an investment of ₹6,000 crore to promote smart farming using AI, drones, and data analytics to enhance crop yields. The Union Ministry of Agriculture introduced the Smart Precision Horticulture Programme as part of the Mission for Integrated Development of Horticulture (MIDH) scheme. This five-year initiative, spanning from 2024-25 to 2028-29, aims to cover 15,000 acres of land and benefit approximately 60,000 farmers. Additionally, the government has established 22 Precision Farming Development Centres (PFDCs) nationwide to test advanced technologies and adapt them to suit local agricultural conditions.
Key Market Players
- IBM India Private Limited
- Granular India Limited
- Microsoft Corporation (I)
Private Limited
- John Deere India Private
Limited
- Intel Technology India Private
Limited
- Climate Agrobotix India
Private Limited
- Fasal Farming Private Limited
- Aibono Smart Farming Private
Limited
- Intello Labs Private Limited
- CropIn Technology Solutions Private Limited
|
By Technology |
By Offering |
By Application |
By Region |
|
|
|
|
|
|
FAQ'S
For a single, multi and corporate client license, the report will be available in PDF format. Sample report would be given you in excel format. For more questions please contact:
Within 24 to 48 hrs.
You can contact Sales team (sales@marketinsightsresearch.com) and they will direct you on email
You can order a report by selecting payment methods, which is bank wire or online payment through any Debit/Credit card, Razor pay or PayPal.
Discounts are available.
Hard Copy