If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The report "Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, Hardware, AI-as-a-Service, and Services), Application, and Geography - Global Forecast to 2026", is estimated to be USD 1.0 billion in 2020 and is projected to reach USD 4.0 billion by 2026, at a CAGR of 25.5% between 2020 and 2026. The market growth is driven by the increasing implementation of data generation through sensors and aerial images for crops, increasing crop productivity through deep-learning technology, and government support for the adoption of modern agricultural techniques. Browse 81 market data Tables and 40 Figures spread through 152 Pages and in-depth TOC on "Artificial Intelligence in Agriculture Market by Technology (Machine Learning, Computer Vision, and Predictive Analytics), Offering (Software, Hardware, AI-as-a-Service, and Services), Application, and Geography - Global Forecast to 2026" The market for drone analytics is expected to grow at the highest rate due to its extensive use for diagnosing and mapping to evaluate crop health and to make real-time decisions. Favorable government mandates for the use of drones in agriculture are also expected to fuel the growth of the drone analytics market. Increasing awareness among farm owners regarding the advantages associated with AI technology is expected to further fuel the growth of the AI in agriculture market.
Artificial Intelligence (AI) in Agriculture market research is an intelligence report with meticulous efforts undertaken to study the right and valuable information. The data which has been looked upon is done considering both, the existing top players and the upcoming competitors. Business strategies of the key players and the new entering market industries are studied in detail. Well explained SWOT analysis, revenue share and contact information are shared in this report analysis. According to the research report, the rising practice of Artificial Intelligence (AI) in Agriculture in the Artificial Intelligence (AI) in Agriculture industry is likely to boost the global Artificial Intelligence (AI) in Agriculture market significantly over the forthcoming years.
The Global Artificial Intelligence (AI) in Agriculture 2019 Market Research Report is a professional and in-depth study on the current state of Artificial Intelligence (AI) in Agriculture Market. The report provides a basic overview of the industry including definitions and classifications. The Artificial Intelligence (AI) in Agriculture analysis is provided for the international markets including development trends, competitive landscape analysis, and key regions development status. Get sample copy of this [email protected] http://bit.ly/35HA8Qb While the regions considered in the scope of the report include North America, Europe, and various others.
New York City, NY: December, 2019 – Published via (WiredRelease) – The report titled Artificial Intelligence (AI) in Agriculture Market is the latest additions to MarketResearch.biz's It offers detail information on restraints, challenges, leading growth drivers, driving forces, profit projection, size, CAGR, consumption, risk analysis, trends, and opportunities, competitive analysis of the Artificial Intelligence (AI) in Agriculture market up to the year 2029. Market participants can use this research on market dynamics to plan effective growth strategies and prepare for future challenges beforehand. Each trend of the Artificial Intelligence (AI) in Agriculture market is precisely analyzed and researched about by the market analysts. Firstly, the Artificial Intelligence (AI) in Agriculture Market Report provides a basic overview of the industry including definitions, classifications, applications and chain structure.
AI having applications in various sectors including agriculture has completely transformed the approaches of the agriculture market. AI in Agriculture helps the farmers in examining weather, soil, and field data to improve farming operations and crop productivity. AI in the agriculture market seems to be driven by the Internet of Things (IoT) due to its ability to revolutionize and transform current farming methods to a new level. Although, collecting accurate field data requires high initial investments which may hamper the growth of AI in the agriculture market. Some of the leading companies influencing the market are Ag Leader Technology, Trimble, Agribotix, Granular, SAP, Mavrx, PrecisionHawk, aWhere, IBM and Prospera Technologies.
Key Questions Answered in this Report: • What is the estimated global artificial intelligence in agriculture market size in terms of value during the period 2018-2024? Global Artificial Intelligence (AI) in Agriculture Market Forecast, 2019-2024 The Global Artificial Intelligence (AI) in Agriculture Market Analysis projects the market to grow at a significant CAGR of 28.38% during the forecast period from 2019 to 2024. The reported growth in the market is expected to be driven by the increasing need to optimize farm operation planning, growing demand to derive insights from emerging complexities of data-driven farming, and rising development of autonomous equipment in agriculture. Artificial intelligence has emerged to be a strong driving force behind the growth of data-driven farming.Regions and countries where agriculture is the major source of livelihood and sustenance, the artificial intelligence technology has led to greater profitability in the farms of those economies. The reduction in expenditure and resultant positive RoI with AI's integration in farm equipment and operations has even reached above 30% in a few countries.
According to a new market intelligence report by BIS Research titled'Global Artificial Intelligence (AI) in Agriculture Market Analysis and Forecast, 2019-2024', the artificial intelligence in agriculture market is estimated at $578.0 million in 2019 and is projected to reach $2,015.7 million by 2024. The market is expected to grow at a CAGR of 28.38% from 2019 to 2024. The reported growth in the market is expected to be driven by the increasing need to optimize farm operation planning, growing need to derive insights from emerging complexities of data-driven farming, and rising development of autonomous equipment in agriculture. Browse More than 49 Data Tables and 129 Figures spread through 293 Pages and in-depth TOC on "Global Artificial Intelligence in Agriculture Market" Precision agriculture is a rising phenomenon in the farming industry since the past decade and has been adapted to improve crop yield to meet the global food demand. It involves the application of emerging smart technologies such as artificial intelligence in farming operations to reduce the wastage of resources with precise and variable application of agri-inputs.
Between 2013 and 2016, U.S. farmers and ranchers weathered a 45% dip in net farm income -- the largest since the Great Depression -- while the number of mouths to feed grew sharply by the day. The global population is expected to increase by 2.2 billion by 2050, and the world's farmers will have to grow about 70% more food than is now produced. If you ask Microsoft, the solution lies in technology. The tech giant's FarmBeats program, which launched in preview today on Azure Marketplace ahead of Ignite 2019, is a multi-year effort to bring robust data analytics to the agriculture sector. With a backend built on Azure and compatibility with hardware from a range of top manufacturers, it aims to promote what Ranveer Chandra, FarmBeats project lead and chief scientist at Azure Global, calls "data-driven" farming techniques.