Artificial Intelligence (AI) in Agriculture Market to hit USD 186 billion by 2025 - Insights on Key Developments, COVID-19 Impact, Value Chain Analysis, Expansion Plans, and Future Outlook: Adroit Market Research

Increasing demand for agricultural production due to the growing population, advanced technologies for enhancing crop productivity, and increasing adoption of data management systems, drives the demand for AI in agriculture market


Dallas, Texas, May 25, 2021 (GLOBE NEWSWIRE) -- The “Artificial Intelligence (AI) in Agriculture Market by Component (hardware, software, services), Technology (computer vision, machine learning, predictive analytics), Application (precision farming, agriculture robots, drone analytics, livestock monitoring, others), and Region, Global Forecast 2018 to 2025” study provides an elaborative view of historic, present and forecasted market estimates.

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The global AI in agriculture market size is anticipated to reach at USD 186 billion by 2025. The extended usage of big data, and machine learning technology, along with artificial intelligence and probabilistic logic has paved the way for a greater development of AI in agriculture industry past few years. Furthermore, the evolution of Internet of Things (IoT) has also fueled the growth momentum of the industry with its various applications in the advancements of the interactive software platform. The industry players operating within the AI in agriculture market are investing significant resources to continuous product development in order to keep up with the market dynamics.

AI techniques for farming enable enhanced yield and productivity. Thus, agribusiness organizations adopt AI technologies in the form of predictive analytics-based solutions. These techniques help yield healthier crops, control pests, enhance agriculture related tasks within the complete food supply chain, and monitor the soil. AI is progressively being implemented in the farming industry for the development of accuracy and harvest quality as it enables analyze farm data.

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Based on the application segment, the market is bifurcated into agriculture robots, drone analytics, livestock monitoring, precision farming, and others. In 2019, the precision farming segment gathered the largest market revenue and it is anticipated to dominate the market throughout the forecast period. Precision farming uses artificial intelligence for data interpretation, collection, and analysis of digital information. For example, GPS-enabled combine harvesters use AI to monitor the harvest produce for field unpredictability analysis that includes differences in soil makeup, water, or fungus, to generate georeferenced information.

The global AI in agriculture market has strong competition among the well-established and new emerging players. These market players target to gain a competitive advantage over the other players by participating in partnerships, mergers, and acquisitions and expanding their businesses.

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The global AI in agriculture solution industry is a wide range to North America, Asia Pacific, Europe, South America, and the Middle East & Africa. The Asia Pacific region is expected to be the prominent region with India as the largest AI in agriculture market. Countries such as Japan, China, and South Korea are anticipated to be at the forefront in the adoption of AI in agriculture owing to increased technological investment in the countries. Moreover, rising trend of cloud-based solution in medium and large industries propels the demand for AI in agriculture in the region.

The major players of the global AI in agriculture solution market are IBM, Deere & Company, AgEagle Aerial Systems, Microsoft, The Climate Corporation, Granular, Prospera Technologies, Taranis, aWhere, Descartes Labs, Tule Technologies, and more. The AI in agriculture solution market is fragmented with the existence of well-known global and domestic players across the globe.

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Major Points from Table of Contents:

Chapter 1 Introduction
Chapter 2 Research Methodology
Chapter 3 Executive Summary
Chapter 4 Market Outlook
Chapter 5 AI in Agriculture Market by Component
Chapter 6 AI in Agriculture Market by Technology
Chapter 7 AI in Agriculture Market by Application
Chapter 8 AI in Agriculture Market By Region
Chapter 9 Competitive Landscape
Chapter 10 Company Profiles

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