AI in Indian Agriculture Market Overview:
Agriculture plays a vital role in India’s economy. Over 58 percent of the rural households depend on agriculture as their principal means of livelihood. Agricultural exports constitute 10 percent of the country’s exports and is the fourth-largest exported principal commodity category in India.
Data generated by sensors or agricultural drones collected at farms, on the field or during transportation offer a wealth of information about soil, seeds, livestock, crops, costs, farm equipment or the use of water and fertilizer. Internet of Things technologies and advanced analytics help farmers analyse real time data like weather, temperature, moisture, prices or GPS signals and provide insights on how to optimize and increase yield, improve farm planning, make smarter decisions about the level of resources needed, when and where to distribute them in order to prevent waste.
Major obstacles in the growth of AI market in agriculture are high cost of cutting-edge AI technology and lack of awareness of AI in agriculture market between end users. Recently, more than 61% of small and medium enterprises (SMEs) surveyed believed that they are not on the radar of seriously executing AI in their business process because of budget restraints and lack of skilled workers.
The improving accessibility of low-cost IoT sensors and affordable solutions for smart agriculture has mitigated the challenges associated with the adoption of IoT-based big data analytics in agriculture to a large extent.
On the back of increased FDI and conducive government initiatives, the agriculture sector is increasingly looking at ways to leverage Artificial Intelligence technology for better crop yield. Many technology companies and start-ups have emerged in the past few years with targeted agri-based solutions that benefit the farmers.
The most popular applications of AI in Indian agriculture fall into three major categories:
1) Crop and Soil Monitoring – Companies are leveraging sensors and various IoT-based technologies to monitor crop and soil health. Crop In is a Bengaluru-based start-up which claims to be an intuitive, intelligent, and self-evolving system that delivers future-ready farming solutions to the agricultural sector. Crop In uses technologies such as AI to help clients analyse and interpret data to derive real-time actionable insights on standing crop and projects spanning geographies. Its agri-business intelligence solution called Smart Risk “leverages agri-alternate data and provides risk mitigation and forecasting for effective credit risk assessment and loan recovery assistance.
2) Predictive Agricultural Analytics – Various AI and machine learning tools are being used to predict the optimal time to sow seeds, get alerts on risks from pest attacks, and more. A new AI based plant management tool is currently being tested in Maharashtra to identify the pink bollworm pest. A tool has been built by wadhwani institute for artificial intelligence. Which earned Google earned a grant for its innovative pest management solution.
3) Supply Chain Efficiencies – Companies are using real-time data analytics on data-streams coming from multiple sources to build an efficient and smart supply chain. Uttar Pradesh based start-up Gabasco has the advantage of a high-tech team. Gobasco developed real-time data analytics on data-streams coming from multiple sources across the country aided with AI-optimized automated pipelines to dramatically increase the efficiency of the current agri supply chain.
The AI market in Indian Agriculture is currently features moderate competition, with some established, international vendors dominating the market. The ecosystem of the AI in Indian agriculture market comprises technology providers, namely IBM (US), John Deere (US), Microsoft (US), Agribotix (US), The Climate Corporation (US), Crop In, Gobasco, Intello labs etc. Major players in the market are mainly focusing on mergers and acquisitions, and partnerships to improve their product portfolios.
Additionally, the market players are focusing on offering advanced and innovative platforms. For instance, in April 2019, Trimble Inc. announced the launch of Farmer Core software subscription that enables farmers in connecting their farm operations. The Farmer Core software offers Auto Sync feature that helps to automatically sync guidance lines, landmarks, boundaries, and operator information using Precision-IQ field application.
Company profiling section includes a detailed analysis of key industry players like its basic information such as legal name, website, headquarters, its market position, historical background and top 5 closest competitors by Market capitalization/revenue along with contact information. Each player/ manufacturer revenue figures, growth rate and gross profit margin is provided in easy to understand tabular format for past 5 years and a separate section on recent development like mergers, acquisition or any new product/service launch, competitive benchmarking, key strategies, associated with enterprise information archiving market. And an analysis of the enterprise information archiving solutions market Revealing Top Players, Trail Blazers, Specialists and Mature Players.
The objective of the report is to present overall picture of AI in Indian Agriculture Market information archiving solutions market. The past, present and the estimated future of AI in Indian Agriculture Market is presented with the help of complicated data and its precise analysis in a lucid language. All the aspects of AI in Indian Agriculture Market have been covered in this report such as PORTER, SVOR, PESTEL analysis the potential impact of macro-economic factors on this market has been elaborated structurally as well as statistically which will help the potential investor to understand the market dynamics and structure in an explicit manner.