Artificial Intelligence in Agriculture Market (Technology - Machine Learning, Computer Vision, and Predictive Analytics; Offering - Software, and AI-as-a-Service; Application - Drone Analytics, Precision Farming, and Others): Global Industry Analysis, Trends, Size, Share and Forecasts to 2030

A recent report published by Infinium Global Research on artificial intelligence in agriculture market provides in-depth analysis of segments and sub-segments in the global as well as regional artificial intelligence in agriculture market. The study also highlights the impact of drivers, restraints, and macro indicators on the global and regional artificial intelligence in agriculture market over the short term as well as long term. The report is a comprehensive presentation of trends, forecast and dollar values of global artificial intelligence in agriculture market.

Market Insight:

The global artificial intelligence in agriculture market was valued at USD 852.15 million in 2022 and is expected to reach USD 5390.14 million in 2030, with a CAGR of 22.40% during the forecast period 2023-2030.

The integration of Artificial Intelligence (AI) into agriculture is fundamentally reshaping modern farming and agribusiness practices. AI technologies, encompassing machine learning, computer vision, data analytics, and automation, are becoming pivotal tools to address the critical challenges faced by the agriculture sector. These challenges range from the need to increase food production to efficiently manage resources and promote sustainability. "AgTech," the application of artificial intelligence in agriculture leverages data-driven decision-making to revolutionize various aspects of farming, including crop management, livestock care, and supply chain logistics. This paradigm shift ushers in an era of precision agriculture, empowering farmers to make well-informed, real-time decisions that enhance crop yields, reduce waste, conserve resources, and maintain the overall health of agricultural ecosystems.

Market growth in AI for agriculture is primarily driven by the increasing global population and the growing scarcity of resources. With the world's population steadily rising, there is a heightened demand for food production. AI offers the means to optimize agricultural practices efficiently to meet this escalating demand. Furthermore, the challenges posed by climate change and environmental pressures have intensified the demand for AI in agriculture. Unpredictable weather patterns, extreme temperatures, and shifting pest dynamics are significant concerns for the industry. AI can provide predictive and adaptive solutions to mitigate these risks and enhance the resilience of farming operations. Additionally, AI enables the efficient management of scarce resources, such as water and arable land, through precision agriculture techniques, leading to improved sustainability and reduced resource wastage. However, the implementation of AI technologies in agriculture often requires substantial initial investments in hardware, software, sensors, and infrastructure, which can act as a constraint to market growth. Despite that, the continuous advancements in AI technologies present significant opportunities in agriculture, including the use of AI-powered robotics and drones for precise tasks like planting, harvesting, and crop monitoring.

North America is expected to hold a significant market share in the forthcoming forecast period. This is attributable to the region's robust and dynamic technology ecosystem, particularly in the United States. It hosts leading tech companies, renowned research institutions, prestigious universities, and a vibrant startup culture that actively contributes to AI innovation in agriculture. Silicon Valley, in particular, serves as a prominent hub for technological advancements. Furthermore, North America's culture of innovation and entrepreneurship fosters experimentation and risk-taking, resulting in a burgeoning number of startups and companies dedicated to developing AI solutions for agriculture. Additionally, the region attracts substantial investments in AI and agriculture-related startups from venture capital firms and corporate investors, providing the necessary funding to drive research and development in AI for agriculture. The Asia-Pacific (APAC) region is poised to experience the fastest growth in the AI in agriculture market. APAC boasts a significant share of the world's agricultural land and a large population dependent on agriculture for their livelihoods and food supply. The sheer scale of agriculture in the region presents a compelling opportunity for AI technologies to make a substantial impact.

Report Scope of the Artificial Intelligence in Agriculture Market:

Segment Covered

The report on global artificial intelligence in agriculture market covers segments such as technology, offering, and application. On the basis of technology, the sub-markets include machine learning, computer vision, and predictive analytics. On the basis of offering, the sub-markets include software, and AI-as-a-service. On the basis of application, the sub-markets include drone analytics, precision farming, and others.

Companies Profiled:

The report provides profiles of the companies in the market such as Deere & Company, IBM Corporation, Microsoft Corporation, Climate LLC, Farmers Edge Inc., AgEagle Aerial Systems Inc, Descartes Labs Inc., Tule Technologies Inc, Precision Hawk, and Taranis.

Report Highlights:

The report provides deep insights into demand forecasts, market trends, and micro and macro indicators. In addition, this report provides insights into the factors that are driving and restraining the growth in this market. Moreover, The IGR-Growth Matrix analysis given in the report brings an insight into the investment areas that existing or new market players can consider. The report provides insights into the market using analytical tools such as Porter's five forces analysis and DRO analysis of the artificial intelligence in agriculture market. Moreover, the study highlights current market trends and provides forecasts from 2023-2030. We also have highlighted future trends in the market that will affect the demand during the forecast period. Moreover, the competitive analysis given in each regional market brings an insight into the market share of the leading players.