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市場調查報告書
商品編碼
1916645
農業機器人與自動化市場預測至2032年:全球機器人類型、產品/服務、農場環境、農場規模、應用及區域分析Agricultural Robotics & Automation Market Forecasts to 2032 - Global Analysis By Robot Type, Offering, Farming Environment, Farm Size, Application and By Geography |
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根據 Stratistics MRC 的一項研究,預計到 2025 年,全球農業機器人和自動化市場規模將達到 165.9 億美元,到 2032 年將達到 544.3 億美元,在預測期內複合年成長率為 18.5%。
農業機器人和自動化是指利用智慧自動化設備和機器人系統,使其能夠自主或在極少人工干預下完成農業作業。這些解決方案利用人工智慧、物聯網感測器、電腦視覺和導航系統等技術,能夠實現精準高效的田間作業,例如播種、作物監測、收割和動物飼養。農業自動化的應用有助於緩解勞動力短缺、降低投入成本、提高作業精度,並促進永續的、數據驅動的農業實踐,同時提升整體農場生產力。
精密農業簡介
為了最佳化資源利用,農民們正在加速採用無人機、自動駕駛曳引機和人工智慧感測器等技術。這些創新能夠實現更精準的播種、灌溉和施肥,從而減少廢棄物並提高產量。全球糧食需求的成長和提高生產力的壓力正在加速向數據驅動型農業的轉型。物聯網和機器學習的融合正在提升農場整體的決策水準和營運效率。各國政府和農業組織正積極推廣智慧農業,以確保永續性和糧食安全。隨著精密農業的普及,預計機器人技術在已開發市場和新興市場的應用都將迅速擴展。
缺乏技術專長
許多農民缺乏機器人、人工智慧和數據分析的培訓,減緩了這些技術的應用速度。小規模農場往往難以將自動化融入傳統耕作方式,而技術純熟勞工高成本和培訓機會有限加劇了這項挑戰。供應商也難以向農村社區提供足夠的幫助和培訓。由於缺乏足夠的專業知識,農民可能會未能充分利用先進工具或錯誤地管理機器人系統。這種知識鴻溝仍然是阻礙世界充分發揮農業自動化潛力的一大障礙。
機器人即服務 (RaaS)
農民可以透過訂閱或計量型模式獲得先進的機器人解決方案,而無需大量初始投資。這種方式降低了經濟門檻,使中小農場也能輕鬆自動化。服務供應商提供包括維護、軟體更新和技術支援在內的綜合解決方案。機器人即服務 (RaaS) 模式鼓勵農民嘗試新技術,並允許他們根據需要擴展業務規模。連接性和雲端平台的進步使遠端監控和控制更加便捷。隨著 RaaS 的普及,預計農業機器人將在各個地區加速應用。
網路安全漏洞
自主設備、無人機和物聯網感測器會產生大量數據,這些數據可能面臨洩漏風險。針對農場管理平台的網路攻擊可能會擾亂運作並洩露敏感的作物資訊。遍遠地區薄弱的安全通訊協定增加了未授權存取的風險。隨著機器人技術與雲端分析的融合,保護數位基礎設施變得至關重要。企業必須投資加密、安全網路和即時監控,以降低威脅。
疫情擾亂了農業供應鏈,導致設備交付延遲和勞動力短缺。封鎖措施限制了人們進入農場,減緩了新型態機器人系統的應用。然而,這場危機也凸顯了自動化在勞動力短缺時期維持糧食生產的重要性。農民們更加依賴無人機和自主機械來確保生產的連續性。疫情加速了數位轉型,提高了對遠端監控和預測分析的依賴。疫情過後,我們預期隨著農民將效率和風險管理放在首位,農業機器人的應用將會更加普及。
預計在預測期內,無人機(UAV)細分市場將佔據最大的市場佔有率。
預計在預測期內,無人機(UAV)領域將佔據最大的市場佔有率。無人機廣泛應用於作物監測、噴灑農藥和測繪,具有無可比擬的效率。它們能夠快速覆蓋大面積區域,使其成為現代農業不可或缺的工具。成像技術和人工智慧驅動的分析技術的進步正在不斷提升無人機的性能。農民擴大使用無人機來檢測病蟲害和營養缺乏。成本的降低和監管支持進一步推動了無人機的普及應用。
預計作物監測和分析領域在預測期內將實現最高的複合年成長率。
預計在預測期內,作物監測和分析領域將實現最高成長率。對作物健康狀況即時洞察的需求日益成長,推動了先進感測器和分析平台的應用。農民正在利用機器人技術追蹤土壤狀況、植物生長情況以及天氣影響。人工智慧和機器學習的融合,使得產量最佳化預測模型得以實現。雲端平台讓不同規模的農場都能輕鬆存取和實用化數據。對永續性和資源效率的日益重視,進一步刺激了對監測解決方案的需求。
預計北美將在預測期內佔據最大的市場佔有率。強大的技術領先優勢和精密農業技術的廣泛應用是推動成長的主要動力。美國和加拿大正在大力投資自動駕駛曳引機、無人機和人工智慧平台。政府的各項措施和補貼正在幫助農民採用智慧技術。完善的基礎設施和充足的熟練勞動力進一步鞏固了該地區的優勢。農業技術公司與研究機構之間的策略合作正在加速創新。
預計亞太地區在預測期內將實現最高的複合年成長率。人口快速成長和糧食需求不斷上升正在推動農業自動化技術的應用。中國、印度和日本等國家正在投資智慧農業技術以提高生產力。政府推行的機械化和數位農業計畫正在加速這些技術的應用。本土Start-Ups正與全球公司合作,提供符合當地需求且經濟高效的解決方案。農村地區網路連接的不斷改善正在促進物聯網和機器人系統的廣泛應用。
According to Stratistics MRC, the Global Agricultural Robotics & Automation Market is accounted for $16.59 billion in 2025 and is expected to reach $54.43 billion by 2032 growing at a CAGR of 18.5% during the forecast period. Agricultural Robotics & Automation involves the use of smart, automated equipment and robotic systems designed to execute agricultural tasks independently or with limited human control. Leveraging technologies such as AI, IoT sensors, computer vision, and navigation systems, these solutions enable precise and efficient field operations including sowing, crop monitoring, harvesting, and animal care. The adoption of automation in agriculture helps address labor shortages, lowers input costs, enhances operational accuracy, and promotes sustainable, data-driven farming practices while boosting overall farm productivity.
Precision agriculture adoption
Farmers are increasingly adopting technologies such as drones, autonomous tractors, and AI-driven sensors to optimize resource utilization. These innovations enable more accurate seeding, irrigation, and fertilization, reducing waste and improving crop yields. Rising global food demand and pressure to maximize productivity are accelerating the shift toward data-driven farming practices. Integration of IoT and machine learning is enhancing decision-making and operational efficiency across farms. Governments and agricultural organizations are promoting smart farming initiatives to ensure sustainability and food security. As precision agriculture becomes mainstream, robotics adoption is expected to expand rapidly across both developed and emerging markets.
Lack of technical expertise
Many agricultural workers lack training in robotics, AI, and data analytics, slowing the pace of implementation. Smaller farms often struggle with the complexity of integrating automation into traditional practices. High costs of skilled labor and limited access to training programs further exacerbate the challenge. Vendors face difficulties in providing adequate support and education to rural communities. Without sufficient expertise, farmers risk underutilizing advanced tools or mismanaging robotic systems. This knowledge gap continues to restrain the full potential of agricultural automation worldwide.
Robotics-as-a-service (RaaS)
Farmers can access advanced robotic solutions without heavy upfront investments, paying instead through subscription or usage-based models. This approach lowers financial barriers and makes automation accessible to small and medium-sized farms. Service providers are offering bundled solutions that include maintenance, software updates, and technical support. RaaS models also encourage experimentation with new technologies, enabling farmers to scale usage as needed. Advances in connectivity and cloud platforms are making remote monitoring and deployment more feasible. As RaaS expands, it is expected to accelerate agricultural robotics penetration across diverse geographies.
Cybersecurity vulnerabilities
Autonomous equipment, drones, and IoT sensors generate vast amounts of data that can be vulnerable to breaches. Cyberattacks targeting farm management platforms may disrupt operations or compromise sensitive crop information. Weak security protocols in rural areas heighten the risk of unauthorized access. As robotics integrate with cloud-based analytics, safeguarding digital infrastructure becomes critical. Companies must invest in encryption, secure networks, and real-time monitoring to mitigate threats.
The pandemic disrupted agricultural supply chains, delaying equipment deliveries and limiting workforce availability. Lockdowns restricted access to farms and slowed the deployment of new robotic systems. However, the crisis highlighted the importance of automation in maintaining food production during labor shortages. Farmers increasingly turned to drones and autonomous machinery to ensure continuity of operations. The pandemic also accelerated digital transformation, with greater reliance on remote monitoring and predictive analytics. Post-Covid, agricultural robotics adoption is expected to rise as farms prioritize efficiency and risk management.
The unmanned aerial vehicles (UAVs) segment is expected to be the largest during the forecast period
The unmanned aerial vehicles (UAVs) segment is expected to account for the largest market share during the forecast period. UAVs are widely used for crop monitoring, spraying, and field mapping, offering unmatched efficiency. Their ability to cover large areas quickly makes them indispensable for modern farming. Advances in imaging technologies and AI-driven analytics are enhancing UAV capabilities. Farmers are increasingly relying on drones to detect pests, diseases, and nutrient deficiencies. Cost reductions and regulatory support are further boosting UAV adoption.
The crop monitoring & analysis segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the crop monitoring & analysis segment is predicted to witness the highest growth rate. Rising demand for real-time insights into crop health is driving adoption of advanced sensors and analytics platforms. Farmers are leveraging robotics to track soil conditions, plant growth, and weather impacts. Integration of AI and machine learning is enabling predictive modeling for yield optimization. Cloud-based platforms are making data accessible and actionable across diverse farm sizes. Growing emphasis on sustainability and resource efficiency is reinforcing demand for monitoring solutions.
During the forecast period, the North America region is expected to hold the largest market share. Strong technological leadership and widespread adoption of precision farming practices are driving growth. The U.S. and Canada are investing heavily in autonomous tractors, drones, and AI-driven platforms. Government initiatives and subsidies are supporting farmers in adopting smart technologies. Robust infrastructure and access to skilled labor further strengthen the region's position. Strategic collaborations between agritech firms and research institutions are accelerating innovation.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid population growth and rising food demand are pressuring farms to embrace automation. Countries like China, India, and Japan are investing in smart farming technologies to boost productivity. Government programs promoting mechanization and digital agriculture are accelerating adoption. Local startups and global players are collaborating to deliver cost-effective solutions tailored to regional needs. Expanding rural connectivity is enabling wider deployment of IoT and robotic systems.
Key players in the market
Some of the key players in Agricultural Robotics & Automation Market include Deere & Company, Autonomous Solutions, Inc., AGCO Corporation, AgEagle Aerial Systems, CNH Industrial N.V., Harvest Automation, Trimble Inc., Naio Technologies, DJI, Agrobot, Lely, ecoRobotix, DeLaval, Blue River Technology, and BouMatic Robotics.
In December 2025, Deere & Company entered into an agreement to acquire Tenna, a construction technology company, and a holding of The Conti Group, that offers mixed-fleet equipment operations and asset tracking solutions. Tenna will continue to operate as an independent business marketed directly to construction customers under the Tenna tradename and will focus on scaling and growing the business through its proven mixed-fleet customer-focused business model.
In September 2025, AGCO announced its signing of a Virtual Power Purchase Agreement (VPPA) in partnership with BRUC, one of the largest renewable energy groups in Spain. The agreement marks a significant milestone in AGCO's renewable energy strategy and helps reduce its Scope 2 greenhouse gas emissions relating to its indirect onsite purchased electricity.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.