市场调查报告书
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1605284
农业人工智慧市场规模、份额、成长分析,按技术、按产品、按应用、按部署模式、按最终用户、按地区 - 行业预测,2024-2031Artificial Intelligence in Agriculture Market Size, Share, Growth Analysis, By Technology (Machine Learning, Computer Vision), By Offering, By Application, By Deployment Mode, By End User, By Region - Industry Forecast 2024-2031 |
2022年,农业人工智慧的全球市场规模为18.2亿美元,从2023年的22.3亿美元成长到2031年的113.9亿美元,预计在预测期内(2024-2031年)将以复合年增长率增长。 2019 年为22.6%。
全球农业人工智慧市场正在经历显着成长,先进技术从根本上改变了农业。世界各地的农民越来越多地采用人工智慧主导的工具来提高营运效率和生产能力。主要应用包括作物监测、害虫检测和产量预测,并透过即时资料分析来支援明智的决策、最大限度地减少资源浪费并提高产量。人工智慧嵌入式无人机和自主机器人的使用将透过实现化学肥料和农药的精确散布来进一步完善作物管理。此外,人工智慧增强的农业机械可以提高生产力,同时降低劳动成本。透过结合人工智慧聊天机器人和虚拟助手,农民可以获得对天气、市场趋势和策略规划的重要见解,从而改善风险管理。随着人工智慧的应用扩展到基因组学和作物育种等领域,它将有助于开发更具弹性的植物品种。然而,儘管人工智慧在农业领域的发展前景广阔,但各地区仍面临挑战,包括资料隐私、高昂的实施成本和技术取得的不平等。儘管如此,随着全球农业部门越来越多地利用人工智慧的变革性优势来推动更永续和高效的农业,未来看起来是光明的。
Global Artificial Intelligence in Agriculture Market size was valued at USD 1.82 billion in 2022 and is poised to grow from USD 2.23 billion in 2023 to USD 11.39 billion by 2031, growing at a CAGR of 22.6% during the forecast period (2024-2031).
The Global Artificial Intelligence in Agriculture Market is witnessing significant growth, fundamentally transforming farming through advanced technologies. Farmers around the world are increasingly adopting AI-driven tools to enhance operational efficiency and production capabilities. Key applications include crop monitoring, pest detection, and yield forecasting, facilitated by real-time data analytics that support informed decision-making, minimize resource waste, and boost yields. The use of drones and autonomous robots with integrated AI further refines crop management by allowing for precise application of fertilizers and pesticides. Moreover, AI-enhanced agricultural machinery improves productivity while reducing labor costs. The incorporation of AI chatbots and virtual assistants provides farmers with crucial insights into weather, market trends, and strategic planning, thus improving risk management. As AI applications expand into areas like genomics and crop breeding, they contribute to developing more resilient plant varieties. However, despite the promising growth of AI in agriculture, challenges such as data privacy, high implementation costs, and uneven access to tech persist across regions. Nonetheless, the future appears bright for the global agriculture sector as it increasingly leverages the transformative benefits of artificial intelligence, driving toward more sustainable and efficient farming practices.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Artificial Intelligence In Agriculture market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Artificial Intelligence In Agriculture Market Segmental Analysis
Global Artificial Intelligence in Agriculture Market is segmented by technology, offering, application, deployment mode, end user and region. Based on technology, the market is segmented into machine learning (supervised learning, unsupervised learning, reinforcement learning), computer vision and predictive analytics. Based on offering, the market is segmented into hardware (sensors, drones, cameras), software (AI platforms, AI solutions) and services (professional services, managed services). Based on application, the market is segmented into precision farming (yield monitoring, field mapping, crop scouting), livestock monitoring (health monitoring, behaviour monitoring), drone analytics (crop health monitoring, soil health monitoring), agricultural robots (harvesting robots, weeding robots) and others (weather forecasting, irrigation management). Based on deployment mode, the market is segmented into cloud, on-premises and hybrid. Based on end user, the market is segmented into farmers, agricultural corporations, research institutions and government agencies. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & and Africa.
Driver of the Global Artificial Intelligence In Agriculture Market
A significant factor driving the Global Artificial Intelligence in Agriculture Market is the escalating demand for sustainable and efficient farming methods. With the global population on the rise, the need for increased food production intensifies, compelling the agricultural sector to enhance productivity while conserving resources. AI-driven technologies present innovative solutions that optimize various agricultural processes, including precision farming and systematic decision-making based on data analysis. This shift towards the adoption of AI is becoming essential for farmers and agricultural organizations, as they strive to address the dual challenges of food security and environmental sustainability effectively.
Restraints in the Global Artificial Intelligence In Agriculture Market
A significant challenge facing the Global Artificial Intelligence in Agriculture Market is the high initial implementation cost. The adoption of AI technologies demands a considerable investment in hardware, software, and associated services. Moreover, the necessity of training personnel and upgrading existing infrastructure to integrate AI solutions can impose a heavy financial burden, particularly for smaller and less resourceful farmers. This cost barrier often limits the overall adoption of AI in agricultural practices and, in turn, restrains market growth. To effectively address this issue, it is essential to develop affordable AI solutions, provide accessible financing alternatives, and introduce government incentives to promote broader acceptance of AI within the agricultural sector.
Market Trends of the Global Artificial Intelligence In Agriculture Market
The Global Artificial Intelligence in Agriculture market is witnessing a notable trend characterized by the rising adoption of digital farming platforms. Agricultural stakeholders, including farmers and organizations, are increasingly leveraging AI-powered platforms that deliver holistic solutions for crop management, data analytics, and informed decision-making. These innovative platforms harness diverse AI technologies, such as machine learning, satellite imagery, and IoT sensors, facilitating real-time insights and optimization of agricultural practices. This trend signifies a transformative shift in the industry towards data-centric and technology-enabled methodologies aimed at enhancing productivity, sustainability, and profitability, ultimately reshaping the future of agriculture.