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Artificial Intelligence (AI) In Animal Health Market Size is valued at 1351.10 Mn in 2024 and is predicted to reach 7758.09 Mn by the year 2034 at a 19.2% CAGR during the forecast period for 2025-2034.
Artificial intelligence (AI) has made substantial advances in various disciplines, including healthcare, and has just begun to impact animal health. AI in animal health entails the application of machine learning algorithms and other AI approaches to improve veterinarian treatment, animal welfare, and research. Artificial intelligence is used to track and monitor wildlife populations, assisting conservation efforts and management plans.
Researchers collected data on endangered animals and their habitats using AI-enabled drones, camera traps, and other technologies. Rapid advances in machine learning techniques, particularly deep learning, enabled better animal health pattern detection and predictive modelling. AI algorithms were growing more sophisticated and capable of digesting vast animal health data.
However, The supply of drugs, vaccines, and testing equipment is critical to the animal health sector. Travel limitations and manufacturing issues may have disrupted the global supply chain, affecting the availability of certain AI-powered diagnostic equipment and technologies.
Artificial Intelligence (AI) In Animal Health Market is segmented as solution, application, and animal type. According to the solution segment, the market is segmented into Hardware, Software & Services. The application segment includes Diagnostics, Identification, Tracking & Monitoring, and Others. By animal type, the market is segmented into Diagnostics, Identification, Tracking, Monitoring, and Others.
The Software & Services division is expected to hold a major share in the global Artificial Intelligence (AI) In Animal Health Market in 2022. Continuous advancements in software technologies, including sensors, imaging devices, computer vision, deep learning, and wearables are fueling the rise of the categories. These solutions are becoming more accessible to animal owners because of improved performance, miniaturization, higher computing power, and cost savings. Increased cooperation between software developers, technology businesses, veterinary clinics, research institutions, and industry groups is also contributing to market growth.
The Diagnostics segment is likely to grow at a rapid rate in the global Artificial Intelligence (AI) In Animal Health Market. The increasing integration of AI in veterinary diagnostics, the availability of AI-powered diagnostic solutions, and the need to increase diagnostic capabilities in animal health all contribute to this expansion. Some of the leading market companies in AI in the veterinary diagnostics sector include IDEXX, Zoetis, SignalPET, and Vetology LLC.
The North America Artificial Intelligence (AI) In Animal Health Market is estimated to witness the highest market revenue in the near future. To assist veterinarians in diagnosing diseases and abnormalities, AI systems can analyze radiographs, CT scans, and MRI pictures. These algorithms can discover patterns and signals humans may miss, resulting in greater accuracy and faster diagnosis.
The expanding integration of AI in veterinary diagnostics and modern veterinary healthcare infrastructure in the U.S. and Canada are important factors driving the regional share. Due to the expanding animal population and activities by local market players, Asia Pacific is likely to increase rapidly. For example, Alibaba Cloud's ET Agricultural Brain applies the company's in-house AI technology to agriculture.
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Report Attribute |
Specifications |
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The Market Size Value In 2024 |
USD 1351.10 Mn |
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Revenue Forecast In 2034 |
USD 7758.09 Mn |
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Growth Rate CAGR |
CAGR of 19.2% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Million and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Components, By Verticals, By Application |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany;India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; South Korea; South East Asia |
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Competitive Landscape |
Alpha Phenomics Inc., Animals.ai, EIO Diagnostics Inc, Farm4Trade, FarmSee, Halter USA Inc., Heska Corporation, IDEXX Laboratories, Inc., ImpriMed, Inc., IMV Technologies, Kraal (UK), Merck & Co., Inc., Moichor Inc., OneCup AI, OPTIFARM, Petriage, Pondus Limited, porklogic.ai, Serket SignalPET, TARGAN Inc., Vet-AI, VetCT, Vetology LLC, Zoetis Services LLC, Other Prominent Players. |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Artificial Intelligence (AI) In Animal Health Market Snapshot
Chapter 4. Global Artificial Intelligence (AI) In Animal Health Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. COVID-19 Impact Analysis
Chapter 5. Market Segmentation 1: By Solutions Estimates & Trend Analysis
5.1. By Solutions & Market Share, 2024-2034
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Solutions:
5.2.1. Hardware
5.2.2. Software & Services
Chapter 6. Market Segmentation 2: By Application Estimates & Trend Analysis
6.1. By Solutions & Market Share, 2024-2034
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Application:
6.2.1. Diagnostics
6.2.2. Identification, Tracking, and Monitoring
6.2.3. Others
Chapter 7. Market Segmentation 3: By Animal Type Estimates & Trend Analysis
7.1. By Solutions & Market Share, 2024-2034
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 to 2034 for the following By Animal Type:
7.2.1. Companion Animals
7.2.2. Production Animals
Chapter 8. Artificial Intelligence (AI) In Animal Health Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Solutions, 2021-2034
8.1.2. North America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Application, 2021-2034
8.1.3. North America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Animal Type, 2021-2034
8.1.4. North America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts by country, 2021-2034
8.1.4.1. U.S.
8.1.4.2. Canada
8.2. Europe
8.2.1. Europe Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by By Solutions, 2021-2034
8.2.2. Europe Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Application, 2021-2034
8.2.3. Europe Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Animal Type, 2021-2034
8.2.4. Europe Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by country, 2021-2034
8.2.4.1. Germany
8.2.4.2. Poland
8.2.4.3. France
8.2.4.4. Italy
8.2.4.5. Spain
8.2.4.6. UK
8.2.4.7. Rest of Europe
8.3. Asia Pacific
8.3.1. Asia Pacific Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by Solutions, 2021-2034
8.3.2. Asia Pacific Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Application, 2021-2034
8.3.3. Asia Pacific Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Animal Type, 2021-2034
8.3.4. Asia Pacific Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by country, 2021-2034
8.3.4.1. China
8.3.4.2. India
8.3.4.3. Japan
8.3.4.4. Australia
8.3.4.5. Rest of Asia Pacific
8.4. Latin America
8.4.1. Latin America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by Solutions, 2021-2034
8.4.2. Latin America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Application, 2021-2034
8.4.3. Latin America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Animal Type, 2021-2034
8.4.4. Latin America Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by country, (US$ Million) 2021-2034
8.4.4.1. Brazil
8.4.4.2. Rest of Latin America
8.5. Middle East & Africa
8.5.1. Middle East & Africa Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by Solutions, (US$ Million)
8.5.2. Middle East & Africa Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Application, 2021-2034
8.5.3. Middle East & Africa Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) estimates and forecasts By Animal Type, 2021-2034
8.5.4. Middle East & Africa Artificial Intelligence (AI) In Animal Health Market revenue (US$ Million) by country, (US$ Million) 2021-2034
8.5.4.1. South Africa
8.5.4.2. GCC Countries
8.5.4.3. Rest of MEA
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. Alpha Phenomics Inc.
9.2.2. Animals.ai
9.2.3. EIO Diagnostics Inc
9.2.4. Farm4Trade
9.2.5. FarmSee
9.2.6. Halter USA Inc.
9.2.7. Heska Corporation
9.2.8. IDEXX Laboratories, Inc.
9.2.9. ImpriMed, Inc.
9.2.10. IMV Technologies
9.2.11. Kraal (UK)
9.2.12. Merck & Co., Inc.
9.2.13. Moichor Inc.
9.2.14. OneCup AI
9.2.15. OPTIFARM
9.2.16. Petriage
9.2.17. Pondus Limited
9.2.18. porklogic.ai
9.2.19. Serket
9.2.20. SignalPET
9.2.21. TARGAN Inc.
9.2.22. Vet-AI
9.2.23. VetCT
9.2.24. Vetology LLC
9.2.25. Zoetis Services LLC
9.2.26. Other Prominent Players
Artificial Intelligence (AI) In Animal Health Market By Solution-
Artificial Intelligence (AI) In Animal Health Market By Application-
Artificial Intelligence (AI) In Animal Health Market By Animal Type-
By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
