# India Applied Ai In Agriculture Market

> India Applied AI in Agriculture Market Research Report By Technology (Machine Learning, Computer Vision, Predictive Analytics), By Offering (Software, AI-as-a-Service), and By Application (Drone Analytics, Precision Farming)-Forecast to 2035

- **Forecast Period:** 2025 - 2035
- **CAGR:** 29.32%
- **2024:** $ 205.68 Million
- **2025:** $ 265.99 Million
- **2035:** $ 3,480 Million
- **Key Players:** Bayer AG (DE), Corteva Agriscience (US), Syngenta AG (CH), John Deere (US), Trimble Inc. (US), AG Leader Technology (US), Taranis (IL), Farmers Edge (CA), Aker Solutions (NO)

**Report ID:** MRFR/ICT/60451-HCR · **Pages:** 200 · **Author:** Nirmit Biswas & Aarti Dhapte · **Last Updated:** May 02, 2026

**URL:** https://www.marketresearchfuture.com/reports/india-applied-ai-in-agriculture-market-62287

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## Market Summary

## **India Applied****AI****in Agriculture Market Overview**

As per MRFR analysis, the India Applied AI in Agriculture Market Size was estimated at 135.8 (USD Million) in 2023.The India Applied AI in Agriculture Market is expected to grow from 175.7(USD Million) in 2024 to 5,205 (USD Million) by 2035. The India Applied AI in Agriculture Market CAGR (growth rate) is expected to be around 36.077% during the forecast period (2025 - 2035).

**Key India Applied****AI****in Agriculture Market Trends Highlighted**

Due to a number of important market factors, the applied AI in agriculture market in India is expanding significantly. The need for food security in a population that is expanding quickly is one of the main causes. The use of AI technologies aids in improving crop yields and resource management, as India is one of the world's biggest producers of agricultural products.

Through programs like the Digital India campaign, which encourages the use of cutting-edge technologies in agriculture, the Indian government has supported these kinds of advances. The improved application of AI algorithms for predictive analytics targeted at disease and pest management is one of the opportunities to be investigated in this sector.

Agritech businesses and farmers are realizing how AI can offer insights based on soil health and weather trends. Given India's emphasis on sustainable farming methods, integrating AI could result in more effective use of fertilizer and water, which would support the government's objective of sustainable development and raising farmer incomes.

Public-private collaborations to promote AI use in agriculture are on the rise in India, according to recent trends. While traditional farming methods are rapidly incorporating technology, startups are constantly creating AI-based tools to help farmers make informed decisions.

A move toward data-driven agriculture operations is also being signaled by growing awareness of precision farming methods. The synergy between technology and agriculture is anticipated to increase as India's digital ecosystem develops, opening the door for improvements in worker training, knowledge exchange, and agricultural productivity as a whole.

Source: Primary Research, Secondary Research, _Market Research Future_ Database and Analyst Review

**India Applied****AI****in Agriculture Market Drivers**

**Government Initiatives and Support**

The Indian government has been actively promoting the adoption of artificial intelligence in agriculture through various initiatives and funding programs. For instance, the Digital India initiative aims to transform the country into a digitally empowered society and knowledge economy, which is crucial for integrating advanced technologies in agriculture.

The Ministry of Agriculture and Farmers Welfare has also been working towards launching schemes like the Pradhan Mantri Krishi Sinchai Yojana, which encourages the use of technology for better farming practices. These initiatives are significant as the Indian agricultural sector contributes about 17-18% of the country's Gross Domestic Product (GDP) and employs nearly half of the country's workforce.

The accelerated push for modernization represents a fertile ground for the India Applied AI in Agriculture Market to thrive. Moreover, the National Agricultural Innovation Project has highlighted the importance of research and development in the agricultural sector, further driving the incorporation of AI technologies to enhance productivity and sustainability.

**Rising Demand for Food Security**

With a population projected to reach 1.7 billion by 2050, India faces growing pressure to ensure food security. The agricultural sector must adapt to meet this increasing demand, and Artificial Intelligence presents innovative solutions to optimize crop yields, manage resources, and minimize losses.

The Indian Council of Agricultural Research reported that the country's food grain production needs to increase significantly to meet projected food demands. AI technologies, such as predictive analytics and machine learning algorithms, allow farmers to make data-driven decisions to improve crop productivity.

As established organizations like the Indian Space Research Organisation tap into satellite data to deliver precision farming solutions, the importance of AI in agriculture becomes pivotal for achieving food security.

**Technological Advancements and Innovation**

The rapid advancement in communication technologies plays a crucial role in the growth of the India Applied AI in Agriculture Market. With over 800 million mobile phone users in India, many farmers now have access to real-time data and insights.

This connectivity enables them to utilize AI-based applications for crop management, pest detection, and soil health monitoring. Organizations such as the National Association of Software and Service Companies have highlighted the need for technological advancements to boost agricultural productivity.

Enhanced access to big data and artificial intelligence analytics empowers farmers to make informed decisions, driving the integration of AI solutions in agriculture.

As per the Department of Telecommunications, the overall internet penetration in rural areas has reached approximately 30%, presenting a significant opportunity for farmers to leverage technological innovations to optimize their yields.

**Adoption of Sustainable Farming Practices**

Sustainability has become a crucial focus area in Indian agriculture, driving interest in AI applications. The Indian government has set ambitious targets to reduce chemical fertilizer usage by 30% and promote organic farming practices. AI technologies can help monitor crop conditions, optimize input usage, and minimize environmental impact.

According to the Ministry of Environment, Forest and Climate Change, over 30% of rural households are now adopting organic farming methods, underscoring the shift towards sustainability.

Established organizations such as the Food and Agriculture Organisation are promoting sustainable practices to counter the adverse effects of climate change. These trends indicate a growing market for AI technologies that can facilitate sustainable agricultural practices.

**India Applied****AI****in Agriculture Market Segment Insights**

**Applied****AI****in Agriculture Market Technology Insights**

The Technology segment within the India Applied AI in Agriculture Market plays a crucial role in shaping the future of agricultural practices, contributing to improved efficiency and productivity in farming operations. This segment is characterized by the integration of advanced technologies such as Machine Learning, Computer Vision, and Predictive Analytics, each serving distinct yet complementary functions.

Machine Learning, for instance, empowers agronomists to analyze large datasets related to weather patterns, soil conditions, and crop health, enabling more informed decision-making and timely interventions.

Computer Vision allows for real-time monitoring of crops through drone imaging and automated systems, significantly enhancing crop management and disease detection processes. This technology is critical in improving yield and reducing wastage, which is increasingly important given India's diverse agro-climatic zones.

Predictive Analytics further supports farmers by offering forecasts on crop yields, pest outbreaks, and market trends, allowing them to optimize resource allocation and maximize their returns. The diversification of crops in India, supported by these technological advancements, holds the potential to increase food security and contribute to the growing demand for sustainable agriculture.

The ongoing digital transformation within the sector is aligned with government initiatives aimed at enhancing agricultural productivity and farmer income. With the Indian agriculture market being one of the largest sectors employing a significant portion of the population, the adoption of AI-driven technologies becomes not just beneficial but necessary.

Each of these technologies fosters connectivity and accessibility, allowing farmers to leverage data-driven insights for decision-making that ultimately leads to sustainable agricultural practices. The India Applied AI in Agriculture Market is expected to witness ongoing growth driven by these innovations, as farmers increasingly recognize the importance of technology in overcoming traditional challenges.

As such, the Technology segment plays a vital role, positioning India to enhance its agricultural framework and elevate the overall economy by empowering its agricultural base through intelligent systems and innovative solutions.

Through the continuous evolution of these technologies, farmers in India will be better equipped to face various environmental and market challenges, thereby improving resilience and productivity in the long run.

Source: Primary Research, Secondary Research, _Market Research Future_ Database and Analyst Review

**Applied****AI****in Agriculture Market Offering Insights**

The India Applied AI in Agriculture Market is experiencing notable growth, driven by segment offerings that encompass advanced technologies like Software and AI-as-a-Service. Software solutions in agriculture enhance operational efficiencies, enabling farmers to apply precision agriculture techniques, optimize resource use, and improve crop yield.

Meanwhile, AI-as-a-Service provides scalable and cost-effective access to AI tools, empowering farmers and agribusinesses, particularly in data analysis and predictive modeling. This model allows users to harness AI capabilities without significant upfront investment, making advanced technology more accessible.

As the government in India continues to promote digital initiatives in agriculture, these segments are positioned to play a significant role in transforming agricultural practices across the country.

The evolving landscape of the agriculture industry presents tremendous opportunities for these offerings, driving innovation and improving productivity while addressing the challenges posed by climate change and food security. Overall, the segment dedicated to Offering is crucial for growth in the India Applied AI in Agriculture Market, allowing stakeholders to leverage technology for sustainable farming practices.

**Applied****AI****in Agriculture Market Application Insights**

The Application segment of the India Applied AI in Agriculture Market is experiencing significant growth, driven by innovations and technological advancements. Among the various applications, Drone Analytics and Precision Farming are notably impactful.

Drone Analytics utilizes aerial imagery and data analytics to enhance crop monitoring and management, allowing farmers to optimize resource usage and improve yield. This method is gaining traction as it reduces labor costs and increases efficiency, aligning with India’s push towards digitization in agriculture.

Precision Farming leverages AI technologies to collect and analyze data, enabling farmers to make data-driven decisions. This approach not only enhances productivity but also promotes sustainable farming practices by minimizing waste and environmental impact.

With India's agrarian economy heavily reliant on efficient production methods, both Drone Analytics and Precision Farming play crucial roles in transforming traditional agricultural practices. The focus on these applications aligns with government initiatives aimed at boosting agricultural productivity and ensuring food security, indicating a robust future for the India Applied AI in Agriculture Market expansion.

As farmers continue to embrace these technologies, the market is expected to witness a diverse range of innovations and solutions tailored to the specific needs of the agricultural sector.

**India Applied****AI****in Agriculture Market Key Players and Competitive Insights**

The competitive landscape of the India Applied AI in Agriculture Market has been significantly evolving due to the increasing integration of technology in agricultural practices. Various players are leveraging artificial intelligence to enhance productivity, crop yield, and farm management efficiency.

This sector is characterized by a mix of startups focusing on agritech solutions and established companies incorporating AI into their existing agricultural services. These advancements not only streamline operations but also provide actionable insights through data analytics, enabling farmers to make informed decisions.

With growing investments in agricultural technology, the market is becoming increasingly competitive as companies strive to differentiate themselves with innovative solutions tailored to meet the specific needs of Indian farmers.

AgroStar has established a strong presence in the India Applied AI in Agriculture Market, focusing on providing farmers with agricultural solutions via mobile technology. The company’s strengths lie in its user-friendly platform that offers expert advice and inputs based on real-time data analysis.

AgroStar has successfully leveraged AI to provide personalized recommendations on crop management, soil health, and pest control, enhancing the farming experience for many users. Its extensive distribution network across rural India allows for widespread access to its technology, and the company’s commitment to farmer education through digital platforms further reinforces its position in the market.

AgroStar’s ability to innovate and adapt to regional agricultural challenges has solidified its reputation as a major player in the sector.

Gramophone has emerged as a notable contender in the India Applied AI in Agriculture Market, focusing on delivering technological solutions designed to empower farmers with knowledge and resources. The company provides key services such as advice on crop selection, pest management, and soil testing, ensuring that farmers can optimize their yields.

Gramophone’s strengths are amplified by its extensive market presence, which includes a robust supply chain that facilitates timely access to quality agricultural inputs. Additionally, the company actively engages in mergers and acquisitions to enhance its technology and expand its service offerings.

This strategic growth has allowed Gramophone to incorporate cutting-edge AI capabilities into its platform, driving efficiency and supporting farmers in making data-driven decisions. Through its innovation-driven approach, Gramophone is positioning itself as a strong competitor in the evolving landscape of agricultural technology in India.

**Key Companies in the India Applied****AI****in Agriculture Market Include**

- AgroStar
- Gramophone
- CropIn
- DeHaat
- Intello Labs
- Ninjacart
- Aibono
- Skymet Weather
- Fasal

**India Applied****AI****in Agriculture****Market****Developments**

In collaboration with Syngenta and the Indian government, CropIn started implementing satellite-based AI analytics for smallholder farms in Andhra Pradesh and Karnataka in May 2024. By providing over 30,000 farm plots with crop-yield forecasts, disease notifications, and irrigation schedules, the company was able to increase average profits by more than 30% per acre.

In Karnataka, Maharashtra, and Telangana, Fasal formally launched its farm-level IoT sensor network and AI-powered micro-climate advisory in February 2025. According to users in field trials, this allowed for real-time irrigation, weather, and pest guidance, which resulted in a 20% reduction in water and pesticide use.

In March 2024, DeHaat had scaled to provide 1.8 million farmers in 12 states with localized crop calendars and disease/pest alerts through contact centers and apps, expanding its AI-advisory engine to 35 crop varieties.

AgroStar's 2024 ESG Impact report, published in July 2024, outlines their digital-first approach, which includes resolving over 10 million agronomy queries using AI-guided advising, boosting yields by 27%, cutting input costs by 17%, and establishing connections with over 25 export markets.

By incorporating machine learning-based demand forecasting and price insights into its fresh produce logistics network in more than 60 cities, Ninjacart improved its supply-chain AI in September 2023.

Early in 2024, Intello Labs carried on testing AI-based crop quality detection with agribusiness partners, allowing automated image analytics-based fault detection during harvest grading. These advancements show tangible AI applications in India's agriculture sector from January 2023, spearheaded by Intello Labs, CropIn, Fasal, DeHaat, AgroStar, and Ninjacart.

**India Applied****AI****in Agriculture Market Segmentation Insights**

- **Applied AI in Agriculture Market Technology Outlook** - Machine Learning - Computer Vision - Predictive Analytics
- **Applied AI in Agriculture Market Offering Outlook** - Software - AI-as-a-Service
- **Applied AI in Agriculture Market Application Outlook** - Drone Analytics - Precision Farming

## Market Drivers

### Growing Awareness and Education

The increasing awareness and education regarding the benefits of AI in agriculture are pivotal for the applied ai-in-agriculture market. Farmers are becoming more informed about how AI technologies can enhance their productivity and profitability. Educational programs and workshops are being organized to demonstrate the practical applications of AI in farming. This knowledge dissemination is crucial, as it empowers farmers to adopt new technologies confidently. Furthermore, as agricultural universities and institutions incorporate AI into their curricula, the next generation of farmers is likely to be more adept at utilizing these tools. This growing awareness is expected to lead to a broader acceptance of AI solutions, thereby propelling the applied ai-in-agriculture market forward.

### Rising Demand for Food Security

The growing population in India is intensifying the demand for food security, which is a significant driver for the applied ai-in-agriculture market. As the population is projected to reach 1.5 billion by 2030, the pressure on agricultural productivity is mounting. AI technologies can assist in maximizing crop yields and minimizing losses through predictive analytics and real-time monitoring. The applied ai-in-agriculture market is expected to benefit from this trend, as farmers seek innovative solutions to meet the increasing food demand. Moreover, the integration of AI can lead to more efficient resource utilization, reducing waste and enhancing sustainability. This alignment with food security goals positions the applied ai-in-agriculture market as a vital component in addressing future agricultural challenges.

### Technological Advancements in AI

The rapid evolution of artificial intelligence technologies is a primary driver for the applied ai-in-agriculture market. Innovations in machine learning, computer vision, and data analytics are enabling farmers to optimize their operations. For instance, AI algorithms can analyze vast datasets to provide insights on soil health, crop conditions, and pest management. In India, the market for AI in agriculture is projected to reach approximately $2.6 billion by 2025, reflecting a compound annual growth rate (CAGR) of around 25%. This growth is largely attributed to the increasing adoption of smart farming techniques, which leverage AI to enhance productivity and sustainability. As farmers become more aware of these technologies, the demand for AI-driven solutions is likely to surge, further propelling the applied ai-in-agriculture market.

### Government Initiatives and Support

Government policies and initiatives play a crucial role in fostering the applied ai-in-agriculture market. The Indian government has been actively promoting the use of technology in agriculture through various schemes and subsidies. Programs aimed at digitizing agriculture and enhancing farmers' access to AI tools are gaining traction. For example, the Digital India initiative encourages the integration of technology in farming practices. Additionally, the government has allocated substantial funds to support research and development in agricultural technologies, which is expected to boost the applied ai-in-agriculture market. With an increasing focus on food security and sustainable practices, government backing is likely to enhance the adoption of AI solutions among farmers, thereby driving market growth.

### Increased Investment in Agri-Tech Startups

The surge in investment in agri-tech startups is significantly influencing the applied ai-in-agriculture market. Investors are increasingly recognizing the potential of AI-driven solutions to transform traditional farming practices. In recent years, funding for agri-tech ventures in India has seen a remarkable increase, with investments reaching over $1 billion in 2025 alone. This influx of capital is facilitating the development of innovative AI applications tailored for the agricultural sector. Startups are focusing on areas such as precision farming, crop health monitoring, and supply chain optimization, which are essential for enhancing productivity. As these startups continue to innovate and scale, they are likely to drive the growth of the applied ai-in-agriculture market, creating a dynamic ecosystem for technological advancement.

## Future Outlook

The [Applied AI in Agriculture Market](https://www.marketresearchfuture.com/reports/applied-ai-in-agriculture-market-12168) in India is projected to grow at a 29.32% CAGR from 2025 to 2035, driven by technological advancements and increasing demand for sustainable farming practices.

**New opportunities:**

- Development of precision agriculture platforms utilizing AI for crop monitoring. Integration of AI-driven predictive analytics for yield optimization. Creation of automated pest management systems using AI technologies.

By 2035, the market is expected to achieve substantial growth, positioning itself as a leader in agricultural innovation.

## Segment Insights

### By Technology: Machine Learning (Largest) vs. Computer Vision (Fastest-Growing)

In the India applied ai-in-agriculture market, Machine Learning holds the largest share, significantly impacting various agricultural practices. Its ability to process vast amounts of data and generate actionable insights makes it indispensable for farmers seeking to optimize yields. Meanwhile, Computer Vision is emerging as the fastest-growing segment, revolutionizing how farmers interact with their crops and livestock by providing visual data analysis and monitoring capabilities. Predictive Analytics complements these technologies by offering forecasts about crop yields, pest invasions, and market trends. This synergy among the technologies drives aggressive adoption in the sector as stakeholders strive for increased efficiency and productivity. The growing need for data-driven decision-making, supported by government initiatives promoting digital agriculture, further accelerates the development of these technologies in the market.

Technology: Machine Learning (Dominant) vs. Predictive Analytics (Emerging)

Machine Learning stands out as the dominant force within the India applied ai-in-agriculture market, providing farmers with crucial insights for optimizing crop management and resource utilization. By leveraging algorithms and historical data, it enables precision agriculture practices that enhance productivity and reduce costs. On the other hand, Predictive Analytics is considered an emerging technology, gaining traction due to its ability to forecast agricultural trends and identify potential issues before they arise. This aspect makes predictive tools invaluable as farmers increasingly rely on advanced analytics to minimize risks and enhance operational efficiencies. Together, these technologies represent a pioneering change in agricultural practices, driving the sector towards a more innovative and efficient future.

### By Offering: Software (Largest) vs. AI-as-a-Service (Fastest-Growing)

In the India applied ai-in-agriculture market, the offering segment is primarily divided into Software and AI-as-a-Service. Software has established itself as the largest segment, capturing a significant portion of the market share due to its widespread adoption among farmers and agribusinesses. It provides essential tools for data analysis, crop management, and predictive analytics, making it indispensable in modern agriculture. On the other hand, AI-as-a-Service is gaining traction rapidly, being recognized as the fastest-growing segment in this market. Its growth is driven by the increasing demand for cloud-based solutions and the accessibility of AI technologies for small and medium-sized enterprises. This shift allows farmers to utilize advanced analytics and machine learning models without substantial upfront investments, fostering innovation and efficiency in agricultural practices.

Software (Dominant) vs. AI-as-a-Service (Emerging)

Software in the India applied ai-in-agriculture market is characterized by its robust capability to provide versatile solutions for various agricultural challenges, including pest management, yield prediction, and resource optimization. Its dominance stems from established customer bases and proven efficacy in enhancing farm productivity. Conversely, AI-as-a-Service represents an emerging trend, fostering growth by allowing access to advanced AI models through subscription-based services. This model appeals especially to new entrants in the agriculture sector seeking to leverage technology without significant capital expenditure. The agility and scalability offered by AI-as-a-Service are reshaping traditional agricultural practices, offering significant potential for future expansion and innovation.

### By Application: Drone Analytics (Largest) vs. Precision Farming (Fastest-Growing)

In the India applied ai-in-agriculture market, Drone Analytics dominates with a significant market share, representing the most established segment. This segment encompasses various drone technologies that monitor crop health, optimize resource use, and enhance agricultural practices through precision data. On the other hand, Precision Farming, while currently smaller in market share, is experiencing rapid growth as farmers increasingly adopt AI-driven solutions to improve yield accuracy and reduce waste. This trend is spurred by the rising demand for sustainable agricultural practices and the integration of advanced technologies in farming. Growth trends in the India applied ai-in-agriculture market indicate a shift towards more automated and data-driven farming methods. Factors such as increasing investment in agricultural technology, government initiatives promoting smart farming, and the need to enhance food security are driving adoption. As farmers face challenges like climate change and resource scarcity, innovations in Precision Farming are poised for acceleration, while Drone Analytics remains critical for optimizing agricultural operations and maximizing productivity.

Drone Analytics (Dominant) vs. Precision Farming (Emerging)

Drone Analytics is characterized by its ability to provide real-time insights into crop conditions and land usage through aerial imagery and data processing. This segment is well-established, leveraging advancements in AI to enhance traditional agricultural practices. It allows farmers to make informed decisions, leading to improved yield outcomes and resource management. In contrast, Precision Farming is considered an emerging segment that utilizes data analytics to optimize field-level management regarding crops. This approach is enhancing efficiency and sustainability, focusing on specific conditions of the crops and soil. As farmers embrace AI innovations, Precision Farming solutions are gaining traction, positioning them as essential tools for modern agriculture.

## Competitive Benchmarking

The applied ai-in-agriculture market in India is characterized by a dynamic competitive landscape, driven by technological advancements and increasing demand for sustainable agricultural practices. Major players such as Bayer AG (DE), Corteva Agriscience (US), and John Deere (US) are at the forefront, each adopting distinct strategies to enhance their market presence. Bayer AG (DE) focuses on innovation through its digital farming solutions, aiming to integrate AI with traditional agricultural practices. Corteva Agriscience (US) emphasizes partnerships with local farmers to tailor its AI solutions, thereby enhancing crop yields and sustainability. John Deere (US) leverages its strong brand reputation to push for digital transformation in farming, integrating AI into its machinery to optimize operations. Collectively, these strategies contribute to a competitive environment that is increasingly centered around technological integration and sustainability.Key business tactics within this market include localizing manufacturing and optimizing supply chains to meet regional demands. The competitive structure appears moderately fragmented, with several key players influencing market dynamics. This fragmentation allows for a variety of innovative solutions to emerge, as companies strive to differentiate themselves through unique offerings and localized strategies. The collective influence of these players fosters a competitive atmosphere where agility and responsiveness to market needs are paramount.
In October Bayer AG (DE) announced a partnership with a leading Indian agri-tech startup to develop AI-driven pest management solutions. This strategic move is significant as it not only enhances Bayer's product portfolio but also aligns with the growing trend of integrating local knowledge into technological solutions. By collaborating with local innovators, Bayer positions itself to better address the specific challenges faced by Indian farmers, thereby strengthening its market foothold.
In September Corteva Agriscience (US) launched a new AI-based platform aimed at optimizing fertilizer application for Indian crops. This initiative is crucial as it addresses the pressing need for efficient resource utilization in agriculture, potentially reducing costs for farmers while increasing productivity. The platform's introduction reflects Corteva's commitment to sustainability and its strategic focus on leveraging AI to enhance agricultural practices in India.
In August John Deere (US) unveiled a new line of AI-integrated tractors designed specifically for the Indian market. This development is noteworthy as it showcases John Deere's dedication to innovation and its understanding of local agricultural needs. By offering advanced machinery that incorporates AI, John Deere not only enhances operational efficiency for farmers but also reinforces its competitive edge in a rapidly evolving market.
As of November current trends in the applied ai-in-agriculture market include a pronounced shift towards digitalization, sustainability, and the integration of AI technologies. Strategic alliances among key players are increasingly shaping the competitive landscape, fostering innovation and collaboration. Looking ahead, it is likely that competitive differentiation will evolve, moving away from traditional price-based competition towards a focus on technological innovation, reliability in supply chains, and sustainable practices. This shift underscores the importance of adaptability and forward-thinking strategies in maintaining a competitive advantage in the market.

## Recent News & Developments

In collaboration with Syngenta and the Indian government, CropIn started implementing satellite-based AI analytics for smallholder farms in Andhra Pradesh and Karnataka in May 2024. By providing over 30,000 farm plots with crop-yield forecasts, disease notifications, and irrigation schedules, the company was able to increase average profits by more than 30% per acre.

In Karnataka, Maharashtra, and Telangana, Fasal formally launched its farm-level IoT sensor network and AI-powered micro-climate advisory in February 2025. According to users in field trials, this allowed for real-time irrigation, weather, and pest guidance, which resulted in a 20% reduction in water and pesticide use.

In March 2024, DeHaat had scaled to provide 1.8 million farmers in 12 states with localized crop calendars and disease/pest alerts through contact centers and apps, expanding its AI-advisory engine to 35 crop varieties.

AgroStar's 2024 ESG Impact report, published in July 2024, outlines their digital-first approach, which includes resolving over 10 million agronomy queries using AI-guided advising, boosting yields by 27%, cutting input costs by 17%, and establishing connections with over 25 export markets.

By incorporating machine learning-based demand forecasting and price insights into its fresh produce logistics network in more than 60 cities, Ninjacart improved its supply-chain AI in September 2023.

Early in 2024, Intello Labs carried on testing AI-based crop quality detection with agribusiness partners, allowing automated image analytics-based fault detection during harvest grading. These advancements show tangible AI applications in India's agriculture sector from January 2023, spearheaded by Intello Labs, CropIn, Fasal, DeHaat, AgroStar, and Ninjacart.

**India Applied****AI**

## Report Scope

| MARKET SIZE 2024 | 205.68(USD Million) |
| --- | --- |
| MARKET SIZE 2025 | 265.99(USD Million) |
| MARKET SIZE 2035 | 3480.0(USD Million) |
| COMPOUND ANNUAL GROWTH RATE (CAGR) | 29.32% (2025 - 2035) |
| REPORT COVERAGE | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
| BASE YEAR | 2024 |
| Market Forecast Period | 2025 - 2035 |
| Historical Data | 2019 - 2024 |
| Market Forecast Units | USD Million |
| Key Companies Profiled | Bayer AG (DE), Corteva Agriscience (US), Syngenta AG (CH), John Deere (US), Trimble Inc. (US), AG Leader Technology (US), Taranis (IL), Farmers Edge (CA), Aker Solutions (NO) |
| Segments Covered | Technology, Offering, Application |
| Key Market Opportunities | Integration of precision agriculture technologies enhances yield and resource efficiency in the applied ai-in-agriculture market. |
| Key Market Dynamics | Rising adoption of precision agriculture technologies drives efficiency and sustainability in the applied AI-in-agriculture market. |
| Countries Covered | India |

## Frequently Asked Questions

**Q: What is the current valuation of the applied ai-in-agriculture market in India?**
A: The market valuation was $205.68 Million in 2024.

**Q: What is the projected market size for the applied ai-in-agriculture sector in India by 2035?**
A: The projected valuation for 2035 is $3480.0 Million.

**Q: What is the expected CAGR for the applied ai-in-agriculture market in India from 2025 to 2035?**
A: The expected CAGR during the forecast period 2025 - 2035 is 29.32%.

**Q: Which technology segments are leading in the applied ai-in-agriculture market in India?**
A: Key technology segments include Machine Learning ($688.0 Million), Computer Vision ($1030.0 Million), and Predictive Analytics ($1762.0 Million).

**Q: What are the primary offerings in the applied ai-in-agriculture market in India?**
A: The main offerings are Software ($1200.0 Million) and AI-as-a-Service ($2280.0 Million).

**Q: What applications are driving growth in the applied ai-in-agriculture market in India?**
A: Drone Analytics ($680.0 Million) and Precision Farming ($2800.0 Million) are significant applications.

**Q: Who are the key players in the applied ai-in-agriculture market in India?**
A: Prominent players include Bayer AG, Corteva Agriscience, Syngenta AG, and John Deere.

**Q: How does the performance of the applied ai-in-agriculture market in India compare to global trends?**
A: While specific global trends are not referenced, the Indian market shows robust growth potential with a projected valuation increase.

**Q: What role does predictive analytics play in the applied ai-in-agriculture market in India?**
A: Predictive Analytics is valued at $1762.0 Million, indicating its crucial role in decision-making processes.

**Q: What is the significance of precision farming in the applied ai-in-agriculture market in India?**
A: Precision Farming, valued at $2800.0 Million, is a key application driving efficiency and productivity in agriculture.


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