Report Overview

A spurring demand for sustainable practices in agriculture, an increasing integration of innovative technologies like IoT, ML, cloud computing, and drones, and the government’s initiatives to promote the adoption of AI in agriculture are expected to drive the India AI in Agriculture Market during the forecast period between 2024 and 2030.

India AI in Agriculture Market – Industry Trends & Forecast Report, 2030

The India AI in Agriculture Market size was estimated at USD 466.95 million in 2023. During the forecast period between 2024 and 2030, the India AI in Agriculture Market size is projected to grow at a CAGR of 9.88% reaching a value of USD 1,918.29 million by 2030. A prominent driver of the market is the increasing integration of artificial intelligence (AI) into agriculture. AI enhances farming practices by employing cognitive technology to facilitate learning, reasoning, and interaction within the agricultural sector. This technology revolutionizes traditional farming methods, with farmers increasingly adopting advanced techniques such as drones, automated systems, and robots. The focus has shifted towards optimizing crop yields without compromising quality, leading to increased investment in automated farming systems to meet growing demand.

AI in Agriculture – Overview

Artificial Intelligence (AI) is transforming agriculture, enhancing efficiency, sustainability, and productivity. Through machine learning, computer vision, and robotics, AI optimizes farming operations by leveraging data-driven insights. It Aids in crop monitoring, disease detection, and yield prediction by analyzing satellite imagery, weather data, and sensors. Precision farming benefits from AI's targeted interventions, optimizing irrigation and pesticide use to reduce costs and environmental impact. Automation through AI-powered robots and drones streamlines tasks like planting and harvesting. Additionally, AI facilitates farm management, supply chain optimization, and market forecasting, empowering farmers to increase yields and profits. The ongoing advancement of AI holds vast promise for sustainable and efficient food production in agriculture.

India AI in Agriculture Market

Growth Drivers

Digitizing Indian Agriculture with AI, ML, and IoT

In the realm of Indian agriculture, a digital transformation is underway, spearheaded by the seamless integration of Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) technologies. This evolution is driven by a multifaceted approach Aiming to enhance agricultural efficiency, adapt to climate change, and meet global market demands. Initiatives such as ITCMAARS, in collaboration with ITC Infotech, bridge the gap by offering 'phygital' solutions, blending physical and digital interventions. These innovations empower farmers with personalized agricultural services, from pest identification to real-time expert consultations, thereby revolutionizing farming practices. With government support and private sector initiatives, India's agriculture sector is poised to set a global standard for sustainability and resilience, leveraging the transformative potential of AI, ML, and IoT.

Government’s Initiatives to Promote Adoption of AI in Agriculture

The agricultural sector faces unprecedented challenges amid a booming population, necessitating a 60% increase in food production by 2050 with minimal land expansion. India, with 54% cultivable land, anchors its economy and engages half its workforce in agriculture. Embracing advanced technologies like AI is crucial for digital transformation in agriculture, offering lifelines for productivity and sustainability. However, challenges persist, including lack of awareness, security concerns, trust issues, and infrastructure limitations. AI presents transformative opportunities through predictive analytics, agricultural robotics, and monitoring systems. Companies like Nuvento pioneer AI-driven solutions, driving the agricultural sector towards a sustainable and tech-driven future, ensuring a smarter and more efficient agri-value chain.

Challenges

Low Digital Literacy and Lack of Trust in Technology

The growth of the India AI in Agriculture Market faces hurdles due to low digital literacy levels and a prevailing lack of trust in technology among farmers. These challenges impede the adoption of advanced agricultural technologies, hindering the sector's potential for innovation and efficiency. Overcoming these barriers requires concerted efforts to enhance digital literacy through education and training programs tailored to rural communities. Additionally, building trust in technology solutions demands transparent communication, reliable support systems, and tangible demonstrations of the benefits AI can bring to farming practices. Addressing these concerns is pivotal for unlocking the full potential of AI in Indian agriculture.

Impact of Escalating Geopolitical Tensions on India AI in Agriculture Market

Geopolitical tensions can have a multifaceted impact on the India AI in Agriculture Market. Uncertainties arising from geopolitical conflicts can disrupt supply chains, impede technological collaborations, and deter foreign investments critical for advancing AI solutions in agriculture. Moreover, heightened tensions may lead to trade restrictions or embargoes, limiting access to essential resources and hindering the adoption of advanced technologies. Such disruptions not only hamper market growth but also undermine efforts to modernize and enhance agricultural productivity. Therefore, maintaining geopolitical stability and fostering international cooperation are imperative to mitigate adverse effects and sustain the momentum of innovation in India's agricultural sector.

India AI in Agriculture Market

Segmental Coverage

India AI in Agriculture Market – By Offerings

By offerings, the India AI in Agriculture Market is divided into Hardware, Software, AI-as-a-Service (AIaaS), and Services segments. The software segment holds the highest share in the India AI in Agriculture Market by offerings. AI software serves as the backbone for data processing, analytics, and decision-making in agriculture, facilitating the implementation of AI algorithms and models. Offering diverse functionalities such as crop monitoring, disease detection, yield prediction, and farm management, these solutions empower farmers to optimize their practices, boost efficiency, and maximize yields. The accessibility of user-friendly, customizable platforms has further eased the adoption of AI in agriculture. The prominence of the software segment underscores its pivotal role in driving the agricultural industry's transformation.

India AI in Agriculture Market – By Technology

By technology, the India AI in Agriculture Market is divided into Machine Learning (ML), Computer Vision, Predictive Analytics, and Natural Language Processing (NLP) segments. The machine learning (ML) segment holds the highest share in the India AI in Agriculture Market by technology. The growth is propelled by farmers' increasing adoption of cutting-edge technology in agriculture. Moreover, the global use of machine learning by farmers is expected to spur market expansion. ML enables farmers and agricultural enterprises to make informed decisions by analyzing real-time data on weather, temperature, crop conditions, and other factors. Its applications in these domains will fuel the expansion of artificial intelligence (AI) into agriculture. Additionally, the swift growth is attributed to farm managers and producers leveraging the capabilities of IoT devices for field mapping and irrigation system management.

India AI in Agriculture Market – By Deployment

Based on deployment, the India Ai in Agriculture Market is divided into Cloud, On-Premises, and Hybrid segments. The cloud segment holds the highest share in the India AI in Agriculture Market by deployment. Cloud-based solutions offer scalability, flexibility, and accessibility, making them ideal for agricultural applications. They facilitate efficient data storage, processing, and analysis, enabling farmers to access valuable insights from anywhere. Moreover, cloud platforms support seamless integration with other technologies like IoT and machine learning, enhancing their utility in agriculture. The widespread adoption of cloud solutions by agricultural enterprises underscores their significance in driving innovation and efficiency in the sector, positioning them as the preferred choice for AI deployment in Indian agriculture.

India AI in Agriculture Market – By Application

Based on application, the India AI in Agriculture Market is divided into Precision Farming, Livestock Monitoring, Drone Analytics, Agriculture Robots, Labor Management, Crop Management, and Irrigation Management segments. The precision farming segment holds the highest share in the India AI in Agriculture Market by application. It is primarily due to its profound impact on agricultural efficiency and resource management. By employing advanced technologies such as GPS, remote sensing, and variable rate technology, precision farming optimizes inputs like water, fertilizers, and pesticides, tailored to the specific needs of crops and soil conditions. This targeted approach not only maximizes yields but also minimizes waste and environmental impact, making it a preferred choice for farmers. Moreover, government initiatives and technological innovations have further propelled the adoption of precision farming, particularly in high-value crops. Despite being at a nascent stage, precision farming's potential to revolutionize Indian agriculture is evident, driving its dominance in the AI in Agriculture Market. Meanwhile, the agriculture robots segment is expected to witness the fastest growth rate during the forecast period. The key driver if the segment’s growth is the innovation and efficiency in Indian agriculture. Agricultural robots, including micro-spraying robots, drones, automatic tractors and ploughs, and automated harvesting systems, are revolutionizing farming practices by enhancing productivity, sustainability, and labor efficiency. These advanced technologies enable precise crop monitoring, targeted pest control, optimized cultivation, and efficient harvesting, addressing key challenges faced by Indian farmers. Platforms like agribazaar are further facilitating the adoption of agricultural robots by providing farmers with access to innovative solutions and fair market opportunities.

India AI in Agriculture Market – By End User

Based on end user, the India AI in Agriculture Market is divided into Farmers/Growers, Agriculture Cooperatives, and Food Processing Companies segments.

India AI in Agriculture Market – By Region

Geographically, the India AI in Agriculture Market is divided into North India, South India, East India, and West India regions. The North India region holds the highest share in the India AI in Agriculture Market and is expected to maintain its dominance throughout the forecast period. Recognizing the potential of modern technologies to transform the sector, especially given their rich agricultural history and extensive farming practices, the region is embracing advanced methods and digital innovations. The government's goal is to enhance productivity, promote sustainability, and tackle the evolving challenges in agriculture. AI adoption extends beyond crop monitoring and yield prediction to encompass soil analysis, pest management, irrigation optimization, and livestock monitoring. By integrating AI into these areas, farmers can make informed decisions based on data, allocate resources more efficiently, and enhance overall agricultural performance.

Competitive Landscape

Major players operating in India AI in Agriculture Market include Microsoft Corporation, IBM, Granular India Limited, John Deer India Private Limited, Fasal Farming Private Limited, Agrostar, Cropin, Intello Labs, Carbon Robotics, and Aibono. To further enhance their market share, these companies employ various strategies, including mergers and acquisitions, partnerships, joint ventures, license agreements, and new product launches.

Recent Developments

• In May 2024 - The Uttar Pradesh Government announced its aim to boost the rural economy by promoting agricultural startups and implementing artificial intelligence (AI) in farming practices.

• In May 2024 - Niqo Robotics, based in Bangalore, India, secured USD 13 million in Series B funding led by Bidra Innovation Ventures, with significant contributions from Fulcrum Global Capital and Omnivore. The investment, totaling USD 21 million, will support Niqo's AI-driven spot-spraying technology, which targets plants using deep learning and computer vision. By retrofitting existing farm equipment, such as sprayers, with its proprietary AI agriculture camera, Niqo aims to empower smallholder farmers in India, where over 90,000 acres were commercialized in 2023–2024, resulting in real-time chemical savings of up to 60%.

Scope of the Report

Attributes	Details
Years Considered	Historical Data – 2019–2030
	Base Year – 2023
	Estimated Year – 2024
	Forecast Period – 2024–2030
Facts Covered	Revenue in USD Million
Market Coverage	India
Product/ Service Segmentation	Offerings, Technology, Deployment, Application, End User, Region
Key Players	Microsoft Corporation, IBM, Granular India Limited, John Deer India Private Limited, Fasal Farming Private Limited, Agrostar, Cropin, Intello Labs, Carbon Robotics, Aibono

 

By Offerings

• Hardware

• Software

• AI-as-a-Service

• Services

By Technology

• Machine Learning

• Computer Vision

• Predictive Analytics

• Natural Language Processing

By Deployment

• Cloud

• On-Premises

• Hybrid

By Applications

• Precision Farming

• Livestock Monitoring

• Drone Analytics

• Agriculture Robots

• Labor Management

• Crop Management

• Irrigation Management

• Others

By End User

• Farmers/Growers

• Agriculture Cooperatives

• Food Processing Companies

• Others

By Region

• North India

• South India

• East India

• West India

1. Research Framework
   1. Research Objective
   2. Product Overview
   3. Market Segmentation
2. Executive Summary
3.  India AI in Agriculture Market Insights
   1. Industry Value Chain Analysis
   2. DROC Analysis
      1. Growth Drivers
         1. Government Initiatives to promote the adoption of AI in agriculture
         2. Increasing integration of technologies like IoT, ML, cloud computing
         3. Global demand for sustainable agriculture
      2. Restraints
         1. Limited of specialized AI and sectoral expertise in agriculture
         2. Poor data quality and lack of access to data
         3. Low digital literacy and lack of trust in technology
      3. Opportunities
         1. Growing demand for smart farming practices
         2. Expansion of AI applications
         3. Government support for agritech start-ups
      4. Challenges
         1. Integration with existing systems
         2. Regulatory and ethical issues
      5. Technological Advancements/Recent Developments
   3. Regulatory Framework
   4. Porter’s Five Forces Analysis
      1. Bargaining Power of Suppliers
      2. Bargaining Power of Buyers
      3. Threat of New Entrants
      4. Threat of Substitutes
      5. Intensity of Rivalry
4. India AI in Agriculture Market: Marketing Strategies
5. India AI in Agriculture Market: Pricing Analysis
6. India AI in Agriculture Market: Geography Analysis
   1. India AI in Agriculture Market, Geographical Analysis, 2023
   2. India AI in Agriculture, Market Attractiveness Analysis, 2024–2030
7. India AI in Agriculture Market Overview
   1. Market Size & Forecast, 2019–2030
      1. By Value (USD Million)
   2. Market Share and Forecast
      1. By Offerings
         1. Hardware
         2.  Software
         3.  AI-as-a-Service
         4. Service
      2. By Technology
         1. Machine Learning
         2. Computer Vision
         3. Predictive Analytics
         4. Natural Language Processing
      3. By Deployment
         1. Cloud
         2. On-Premises
         3.  Hybrid
      4. By Applications
         1. Precision Farming
         2. Livestock Monitoring
         3. Drone Analytics
         4. Agriculture Robots
         5. Labor Management
         6. Crop Management
         7. Irrigation Management
         8. Others
      5. By End User
         1. Farmers/Growers
         2. Agriculture Cooperatives
         3. Food Processing Companies
         4.  Others
      6. By Region
         1. North India
         2. South India
         3. East India
         4. West India

 

8. North India AI in Agriculture Market
   1. Market Size & Forecast, 2019–2030
      1. By Value (USD Million)
   2. Market Share & Forecast
      1. By Offerings
      2. By Technology
      3. By Deployment
      4. By Applications
      5. By End User
9. South India AI in Agriculture Market
   1. Market Size & Forecast, 2019–2030
      1. By Value (USD Million)
   2. Market Share & Forecast
      1. By Offerings
      2. By Technology
      3. By Deployment
      4. By Applications
      5. By End User
10. East India AI in Agriculture Market
    1. Market Size & Forecast, 2019–2030
       1. By Value (USD Million)
    2. Market Share & Forecast
       1. By Offerings
       2. By Technology
       3. By Deployment
       4. By Applications
       5. By End User
11. West India AI in Agriculture Market
    1. Market Size & Forecast, 2019–2030
       1. By Value (USD Million)
    2. Market Share & Forecast
       1. 1. By Offerings
          2. By Technology
          3. By Deployment
          4. By Applications
          5. By End User
12. Competitive Landscape
    1. List of Key Players and Their Applications
    2. India AI in Agriculture Company Market Share Analysis, 2023
    3. Competitive Benchmarking, By Operating Parameters
    4. Key Strategic Developments (Mergers, Acquisitions, Partnerships, etc.)
13. Impact of Escalating Geopolitical Tensions on India AI in Agriculture Market
14. Company Profiles (Company Overview, Financial Matrix, Competitive Landscape, Key Personnel, Key Competitors, Contact Address, Strategic Outlook, and SWOT Analysis)
    1. Microsoft Corporation
    2. IBM
    3. Granular India Limited
    4. John Deer India Private Limited
    5. Fasal Farming Private Limited
    6. Agrostar
    7. Cropin
    8. Intello Labs
    9. Carbon Robotics
    10. Aibono
    11. Other Prominent Players
15. Key Strategic Recommendations
16. Research Methodology
    1.    Qualitative Research
       1.  Primary & Secondary Research
    2.    Quantitative Research
    3.    Market Breakdown & Data Triangulation
       1.  Secondary Research
       2.  Primary Research
    4.    Breakdown of Primary Research Respondents, By Region
    5.    Assumptions & Limitations

*Financial information of non-listed companies can be provided as per availability.

**The segmentation and the companies are subject to modifications based on in-depth secondary research for the final deliverable

 

List of Figures

 

Figure 1       India AI in Agriculture Market Segmentation

Figure 2       India AI in Agriculture Market Value Chain Analysis

Figure 3       Company Market Share Analysis, 2023

Figure 4       India AI in Agriculture Market Size, By Value (USD Million), 2019−2030

Figure 5       India AI in Agriculture Market Share, By Offerings, By Value (USD Million), 2019−2030

Figure 6       India AI in Agriculture Market Share, By Technology, By Value (USD Million), 2019−2030

Figure 7       India AI in Agriculture Market Share, By Deployment, By Value (USD Million), 2019−2030

Figure 8       India AI in Agriculture Market Share, By Applications, By Value (USD Million), 2019−2030

Figure 9       India AI in Agriculture Market Share, By End User, By Value (USD Million), 2019−2030

Figure 10     India AI in Agriculture Market Share, By Region, By Value (USD Million), 2019−2030

Figure 11     North India AI in Agriculture Market Size, By Value (USD Million), 2019−2030

Figure 12     North India AI in Agriculture Market Share, By Offerings, By Value (USD Million), 2019−2030

Figure 13     North India AI in Agriculture Market Share, By Technology, By Value (USD Million), 2019−2030

Figure 14     North India AI in Agriculture Market Share, By Deployment, By Value (USD Million), 2019−2030

Figure 15     North India AI in Agriculture Market Share, By Applications, By Value (USD Million), 2019−2030

Figure 16     North India AI in Agriculture Market Share, By End User, By Value (USD Million), 2019−2030

Figure 17     North India AI in Agriculture Market Share, By Country, By Value (USD Million), 2019−2030

Figure 18     South India AI in Agriculture Market Size, By Value (USD Million), 2019−2030

Figure 19     South India AI in Agriculture Market Share, By Offerings, By Value (USD Million), 2019−2030

Figure 20     South India AI in Agriculture Market Share, By Technology, By Value (USD Million), 2019−2030

Figure 21     South India AI in Agriculture Market Share, By Deployment, By Value (USD Million), 2019−2030

Figure 22     South India AI in Agriculture Market Share, By Applications, By Value (USD Million), 2019−2030

Figure 23     South India AI in Agriculture Market Share, By End User, By Value (USD Million), 2019−2030

Figure 24     East India AI in Agriculture Market Size, By Value (USD Million), 2019−2030

Figure 25     East India AI in Agriculture Market Share, By Offerings, By Value (USD Million), 2019−2030

Figure 26     East India AI in Agriculture Market Share, By Technology, By Value (USD Million), 2019−2030

Figure 27     East India AI in Agriculture Market Share, By Deployment, By Value (USD Million), 2019−2030

Figure 28     East India AI in Agriculture Market Share, By Applications, By Value (USD Million), 2019−2030

Figure 29     East India AI in Agriculture Market Share, By End User, By Value (USD Million), 2019−2030

Figure 30     West India AI in Agriculture Market Size, By Value (USD Million), 2019−2030

Figure 31     West India AI in Agriculture Market Share, By Offerings, By Value (USD Million), 2019−2030

Figure 32     West India AI in Agriculture Market Share, By Technology, By Value (USD Million), 2019−2030

Figure 33     West India AI in Agriculture Market Share, By Deployment, By Value (USD Million), 2019−2030

Figure 34     West India AI in Agriculture Market Share, By Applications, By Value (USD Million), 2019−2030

Figure 35     West India AI in Agriculture Market Share, By End User, By Value (USD Million), 2019−2030

Figure 36     West India AI in Agriculture Market Share, By Country, By Value (USD Million), 2019−2030

 

List of Tables

 

Table 1        India AI in Agriculture Market Size, By Offerings, By Value (USD Million), 2019−2030

Table 2        India AI in Agriculture Market Size, By Technology, By Value (USD Million), 2019−2030

Table 3        India AI in Agriculture Market Size, By Deployment, By Value (USD Million), 2019−2030

Table 4        India AI in Agriculture Market Size, By Applications, By Value (USD Million), 2019−2030

Table 5        India AI in Agriculture Market Size, By End User, By Value (USD Million), 2019−2030

Table 6        India AI in Agriculture Market Size, By Region, By Value (USD Million), 2019−2030

Table 7        North India AI in Agriculture Market Size, By Offerings, By Value (USD Million), 2019−2030

Table 8        North India AI in Agriculture Market Size, By Technology, By Value (USD Million), 2019−2030

Table 9        North India AI in Agriculture Market Size, By Applications, By Value (USD Million), 2019−2030

Table 10      North India AI in Agriculture Market Size, By End User, By Value (USD Million), 2019−2030

Table 11      North India AI in Agriculture Market Size, By Country, By Value (USD Million), 2019−2030

Table 12      South India AI in Agriculture Market Size, By Offerings, By Value (USD Million), 2019−2030

Table 13      South India AI in Agriculture Market Size, By Technology, By Value (USD Million), 2019−2030

Table 14      South India AI in Agriculture Market Size, By Deployment, By Value (USD Million), 2019−2030

Table 15      South India AI in Agriculture Market Size, By End User, By Value (USD Million), 2019−2030

Table 16      East India AI in Agriculture Market Size, By Offerings, By Value (USD Million), 2019−2030

Table 17      East India AI in Agriculture Market Size, By Technology, By Value (USD Million), 2019−2030

Table 18      East India AI in Agriculture Market Size, By Deployment, By Value (USD Million), 2019−2030

Table 19      East India AI in Agriculture Market Size, By Applications, By Value (USD Million), 2019−2030

Table 20      East India AI in Agriculture Market Size, By End User, By Value (USD Million), 2019−2030

Table 21      West India AI in Agriculture Market Size, By Offerings, By Value (USD Million), 2019−2030

Table 22      West India AI in Agriculture Market Size, By Technology, By Value (USD Million), 2019−2030

Table 23      West India AI in Agriculture Market Size, By Deployment, By Value (USD Million), 2019−2030

Table 24      West India AI in Agriculture Market Size, By Applications, By Value (USD Million), 2019−2030

Table 25      West India AI in Agriculture Market Size, By End User, By Value (USD Million), 2019−2030

Table 26      West India AI in Agriculture Market Size, By Country, By Value (USD Million), 2019−2030

Table 27      Microsoft Corporation Company Overview

Table 28      Microsoft Corporation Financial Overview

Table 29      IBM Company Overview

Table 30      IBM Financial Overview

Table 31      Granular India Limited Company Overview

Table 32      Granular India Limited Financial Overview

Table 33      John Deer India Private Limited Company Overview

Table 34      John Deer India Private Limited Financial Overview

Table 35      Fasal Farming Private Limited Company Overview

Table 36      Fasal Farming Private Limited Financial Overview

Table 37      Agrostar Company Overview

Table 38      Agrostar Financial Overview

Table 39      Cropin Company Overview

Table 40      Cropin Financial Overview

Table 41      Intello Labs Company Overview

Table 42      Intello Labs Financial Overview

Table 43      Carbon Robotics Company Overview

Table 44      Carbon Robotics Financial Overview

Table 45      Aibono Company Overview

Table 46      Aibono Financial Overview