Global AI in Livestock Welfare Monitoring Market Size is valued at US$ 2.3 Bn in 2024 and is predicted to reach US$ 11.8 Bn by the year 2034 at an 18.4% CAGR during the forecast period for 2025-2034.
AI-powered livestock welfare monitoring enhances animal health, optimizes environmental conditions, and tracks behavior through smart sensors, cameras, and machine learning algorithms. By autonomously detecting early signs of illness, stress, or discomfort, it enables farmers to take timely action—preventing disease outbreaks and improving productivity. This technology not only raises animal welfare standards but also reduces labor costs and operational inefficiencies, creating a more sustainable & efficient farming system. The demand for effective livestock management and technical improvements is driving the market for AI in livestock welfare management, which is expanding rapidly.
Additionally, the use of AI technologies in livestock welfare management is being spurred by the growing demand for sustainable livestock production methods.Farmers are increasingly seeking precision solutions in order to enhance animal welfare and mitigate their environmental impact. The integration of AI systems with IoT devices is another noteworthy trend. Moreover, improved connection and data analytics are enabling farmers to make well-informed choices, maximizing resource allocation and feed efficiency. Furthermore, stakeholders are being pushed to invest in AI in livestock welfare management by the increased awareness of food safety and quality.
Some of the Key Players in AI in Livestock Welfare Monitoring Market:
The AI in livestock welfare monitoring market is segmented by component, type, livestock type, application, deployment mode, technology, and end-user. The components of the market are software [data management platforms, behaviour analytics software, AI & machine learning models, health monitoring algorithms], hardware [cameras, sensors, microphones, gateways, RFID tags], and services [maintenance & support, installation & integration services, training & consulting]. By type, the market is segmented into wearable sensor-based systems, thermal imaging systems, vision-based systems, integrated multi-sensor platforms, and audio-based monitoring systems. By livestock type, the market is segmented into swine, poultry, cattle, sheep & goats, and others.
According to the application, the market comprises health monitoring, environmental monitoring, behaviour analysis, stress & pain detection, feeding pattern monitoring, and breeding management. The deployment mode segment categorizes into on-premises, cloud-based, and hybrid. As per the technology, the market is segmented into machine learning, edge AI, computer vision, IOT & smart sensors, and data analytics. By end-user, the market is segmented into animal welfare organizations, commercial livestock farms, veterinary clinics & hospitals, research institutes & universities, and government & regulatory bodies.
In 2024, the software category dominated the market for AI in livestock welfare management. The primary factor for this leadership is the crucial part software plays in organizing and integrating data from multiple sources in the agricultural setting. Decoding the data collected by sensors and IoT devices and turning it into insights that farmers can use is mostly dependent on software solutions. Additionally, the necessity for accurate, scalable software that can efficiently handle large amounts of data is driving the demand for software in AI in livestock welfare management. In addition, the software enables automatic controls and real-time monitoring, which raises farms' total operating efficiency.
The AI in livestock welfare management market is dominated by vision-based systems because they allow for the constant, non-intrusive monitoring of livestock behavior, posture, and movement patterns. These systems are preferred by farmers and researchers because they make it easier to identify irregularities like social disengagement, aggressive behavior, or lameness. Visual recognition systems are more accurate due to developments in deep learning algorithms and high-definition imaging. Early detection of health issues is made possible by these instruments, which lowers treatment expenses and lessens animal suffering.
North America dominates the AI-driven livestock welfare management market, driven by stringent animal welfare regulations and a strong focus on operational efficiency. The region's producers lead in adopting vision-based and sensor-enabled systems to monitor health, feeding patterns, and behavioral data. Supported by cutting-edge digital infrastructure and robust R&D investments, North America accelerates AI innovation, setting the global benchmark for sustainable and ethical livestock farming practices.
Asia-Pacific AI in livestock welfare management market is predicted to experience the fastest rate of growth. Several important factors support the region's leading growth in AI in livestock welfare management. First off, it has some of the largest agricultural industries in the world, especially when it comes to raising cattle. The region's growing population and rising demand for animal-based products further highlight this, calling for improved management of livestock health.
|
Report Attribute |
Specifications |
|
Market Size Value In 2024 |
USD 2.3 Bn |
|
Revenue Forecast In 2034 |
USD 11.8 Bn |
|
Growth Rate CAGR |
CAGR of 18.4% from 2025 to 2034 |
|
Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2025 to 2034 |
|
Historic Year |
2021 to 2024 |
|
Forecast Year |
2025-2034 |
|
Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
|
Segments Covered |
By Component, By Type, By Livestock Type, By Application, By Deployment Mode, By Technology, By End-user, and By Region |
|
Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
|
Country Scope |
U.S.; Canada; Germany; The UK; France; Italy; Spain; Rest of Europe; China; Japan; India; South Korea; Southeast Asia; Rest of Asia Pacific; Brazil; Argentina; Mexico; Rest of Latin America; GCC Countries; South Africa; Rest of the Middle East and Africa |
|
Competitive Landscape |
Merck Animal Health, Afimilk, Connecterra, DeLaval, Vence (acquired by Merck), Gallagher Animal Management, HerdDogg, Lely, Allflex, PrecisionAG (formerly PrecisionHawk), Stellapps, Zoetis, Tri-Scan (acquired by Zoetis), AgriWebb, Cainthus, Nedap, Silent Herdsman (acquired by Afimilk), Halo (livestock monitoring Al), SmartBow (by Allflex), and Cargill (livestock Al division) |
|
Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Geographic competitive landscape. |
|
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 AI In Livestock Welfare Monitoring Market Snapshot
Chapter 4. Global AI In Livestock Welfare Monitoring 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. Porter's Five Forces Analysis
4.7. Incremental Opportunity Analysis (US$ MN), 2025-2034
4.8. Competitive Landscape & Market Share Analysis, By Key Player (2024)
4.9. Use/impact of AI on AI In Livestock Welfare Monitoring Market Industry Trends
4.10. Global AI In Livestock Welfare Monitoring Market Penetration & Growth Prospect Mapping (US$ Mn), 2024-2034
Chapter 5. AI In Livestock Welfare Monitoring Market Segmentation 1: By Type, Estimates & Trend Analysis
5.1. Market Share by Type, 2024 & 2034
5.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Type:
5.2.1. Vision-Based Systems
5.2.2. Wearable Sensor-Based Systems
5.2.3. Thermal Imaging Systems
5.2.4. Audio-Based Monitoring Systems
5.2.5. Integrated Multi-Sensor Platforms
Chapter 6. AI In Livestock Welfare Monitoring Market Segmentation 2: By End-User, Estimates & Trend Analysis
6.1. Market Share by End-User, 2024 & 2034
6.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following End-User:
6.2.1. Commercial Livestock Farms
6.2.2. Research Institutes & Universities
6.2.3. Veterinary Clinics & Hospitals
6.2.4. Animal Welfare Organizations
6.2.5. Government & Regulatory Bodies
Chapter 7. AI In Livestock Welfare Monitoring Market Segmentation 3: By Application, Estimates & Trend Analysis
7.1. Market Share by Application, 2024 & 2034
7.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Application:
7.2.1. Health Monitoring
7.2.2. Behavior Analysis
7.2.3. Feeding Pattern Monitoring
7.2.4. Stress & Pain Detection
7.2.5. Environmental Monitoring
7.2.6. Breeding Management
Chapter 8. AI In Livestock Welfare Monitoring Market Segmentation 4: By Livestock Type, Estimates & Trend Analysis
8.1. Market Share by Livestock Type, 2024 & 2034
8.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Livestock Type:
8.2.1. Cattle
8.2.2. Swine
8.2.3. Poultry
8.2.4. Sheep & Goats
8.2.5. Others
Chapter 9. AI In Livestock Welfare Monitoring Market Segmentation 5: By Component, Estimates & Trend Analysis
9.1. Market Share by Component, 2024 & 2034
9.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Component:
9.2.1. Hardware
9.2.1.1. Cameras
9.2.1.2. Microphones
9.2.1.3. Sensors
9.2.1.4. RFID Tags
9.2.1.5. Gateways
9.2.2. Software
9.2.2.1. Behavior Analytics Software
9.2.2.2. Health Monitoring Algorithms
9.2.2.3. Data Management Platforms
9.2.2.4. AI & Machine Learning Models
9.2.3. Services
9.2.3.1. Installation & Integration Services
9.2.3.2. Maintenance & Support
9.2.3.3. Training & Consulting
Chapter 10. AI In Livestock Welfare Monitoring Market Segmentation 6: By Deployment Mode, Estimates & Trend Analysis
10.1. Market Share by Deployment Mode, 2024 & 2034
10.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Deployment Mode:
10.2.1. Cloud-Based
10.2.2. On-Premise
10.2.3. Hybrid
Chapter 11. AI In Livestock Welfare Monitoring Market Segmentation 7: By Technology, Estimates & Trend Analysis
11.1. Market Share by Technology, 2024 & 2034
11.2. Market Size Revenue (US$ Million) & Forecasts and Trend Analyses, 2021 to 2034 for the following Technology:
11.2.1. Computer Vision
11.2.2. Machine Learning
11.2.3. IoT & Smart Sensors
11.2.4. Edge AI
11.2.5. Data Analytics
Chapter 12. AI In Livestock Welfare Monitoring Market Segmentation 8: Regional Estimates & Trend Analysis
12.1. Global AI In Livestock Welfare Monitoring Market, Regional Snapshot 2024 & 2034
12.2. North America
12.2.1. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
12.2.1.1. US
12.2.1.2. Canada
12.2.2. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
12.2.3. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
12.2.4. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
12.2.5. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Livestock Type, 2021-2034
12.2.6. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.2.7. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.2.8. North America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
12.3. Europe
12.3.1. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
12.3.1.1. Germany
12.3.1.2. U.K.
12.3.1.3. France
12.3.1.4. Italy
12.3.1.5. Spain
12.3.1.6. Rest of Europe
12.3.2. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
12.3.3. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
12.3.4. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
12.3.5. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Livestock Type, 2021-2034
12.3.6. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.3.7. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.3.8. Europe AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
12.4. Asia Pacific
12.4.1. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
12.4.1.1. India
12.4.1.2. China
12.4.1.3. Japan
12.4.1.4. Australia
12.4.1.5. South Korea
12.4.1.6. Hong Kong
12.4.1.7. Southeast Asia
12.4.1.8. Rest of Asia Pacific
12.4.2. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
12.4.3. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
12.4.4. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
12.4.5. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Livestock Type, 2021-2034
12.4.6. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.4.7. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.4.8. Asia Pacific AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
12.5. Latin America
12.5.1. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Country, 2021-2034
12.5.1.1. Brazil
12.5.1.2. Mexico
12.5.1.3. Rest of Latin America
12.5.2. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
12.5.3. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
12.5.4. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
12.5.5. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Livestock Type, 2021-2034
12.5.6. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.5.7. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.5.8. Latin America AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
12.6. Middle East & Africa
12.6.1. Middle East & Africa Wind Turbine Rotor Blade Market Revenue (US$ Million) Estimates and Forecasts by country, 2021-2034
12.6.1.1. GCC Countries
12.6.1.2. Israel
12.6.1.3. South Africa
12.6.1.4. Rest of Middle East and Africa
12.6.2. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Type, 2021-2034
12.6.3. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by End-User, 2021-2034
12.6.4. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Application, 2021-2034
12.6.5. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Livestock Type, 2021-2034
12.6.6. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Component, 2021-2034
12.6.7. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Deployment Mode, 2021-2034
12.6.8. Middle East & Africa AI In Livestock Welfare Monitoring Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2021-2034
Chapter 13. Competitive Landscape
13.1. Major Mergers and Acquisitions/Strategic Alliances
13.2. Company Profiles
13.2.1. Afimilk
13.2.1.1. Business Overview
13.2.1.2. Key Type/Service Overview
13.2.1.3. Financial Performance
13.2.1.4. Geographical Presence
13.2.1.5. Recent Developments with Business Strategy
13.2.2. Allflex
13.2.3. Cainthus
13.2.4. Connecterra
13.2.5. DeLaval
13.2.6. Gallagher Animal Management
13.2.7. HerdDogg
13.2.8. Lely
13.2.9. Merck Animal Health
13.2.10. Nedap
13.2.11. PrecisionAG (formerly PrecisionHawk)
13.2.12. Stellapps
13.2.13. Vence (acquired by Merck)
13.2.14. Zoetis
13.2.15. AgriWebb
13.2.16. Silent Herdsman (acquired by Afimilk)
13.2.17. SmartBow (by Allflex)
13.2.18. Tri-Scan (acquired by Zoetis)
13.2.19. Cargill (livestock AI division)
13.2.20. Halo (livestock monitoring AI)
Segmentation of AI in Livestock Welfare Monitoring Market -
AI in Livestock Welfare Monitoring Market by Component-
AI in Livestock Welfare Monitoring Market by Type -
AI in Livestock Welfare Monitoring Market by Livestock Type-
AI in Livestock Welfare Monitoring Market by Application-
AI in Livestock Welfare Monitoring Market by Deployment Mode-
AI in Livestock Welfare Monitoring Market by Technology-
AI in Livestock Welfare Monitoring Market by End-user-
AI in Livestock Welfare Monitoring Market 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.
