Artificial Intelligence (AI) in Animal Health Market – By Solution (Hardware, Software, Service) Application (Diagnostics, Identification, Tracking, and Monitoring), Animal Type (Companion, Livestock), End-use, Global Forecast (2024 – 2032)
Artificial Intelligence (AI) in Animal Health Market – By Solution (Hardware, Software, Service) Application (Diagnostics, Identification, Tracking, and Monitoring), Animal Type (Companion, Livestock), End-use, Global Forecast (2024 – 2032)
Global Artificial Intelligence (AI) in Animal Health Market size will register an 18.4% CAGR from 2024 to 2032, owing to the need for efficient veterinary practices and escalating investment in veterinary R&D. As veterinary practices seek to optimize operations and reduce administrative burdens, AI technologies provide crucial support through automation and enhanced data analysis. Furthermore, increased funding in R&D accelerates the development of innovative AI solutions, improving diagnostic accuracy and treatment efficacy. This convergence of efficiency needs and research investment will significantly expand the size of artificial intelligence (AI) in animal health industry.
For instance, in May 2024, Modern Animal introduced AI-assisted tools to enhance its medical software, Claude, aimed at reducing administrative burdens for veterinarians. These upgrades are set to improve service quality for around 60,000 pets and their families. This development underscores the increasing adoption of AI technologies to enhance efficiency, improve service quality, and manage large numbers of patients effectively. The move reflects a broader trend in the global AI in animal health market towards leveraging advanced technology to optimize veterinary practices and meet the rising demand for high-quality animal care.
The artificial intelligence (AI) in animal health market is classified based on solution, application, animal type, end-use, and region.
The identification, tracking, and monitoring segment will witness remarkable expansion through 2032 due to its crucial role in enhancing animal management. AI-driven technologies in this segment enable precise identification, real-time tracking, and comprehensive monitoring of animal health and behavior. These capabilities improve disease detection, streamline breeding processes, and ensure better overall animal welfare. The growing demand for accurate and efficient animal management solutions highlights the segment's importance, driving its dominance in artificial intelligence (AI) in animal health industry.
The livestock animals segment will see a considerable surge by 2023, driven by the substantial benefits AI offers in managing large-scale herds. AI technologies enhance disease detection, optimize breeding practices, and improve overall animal welfare by providing real-time data and predictive analytics. The rising need for efficient livestock management, coupled with the potential for increased productivity and cost savings, drives the segment's dominance. This trend reflects the major impact of AI on advancing livestock health and management practices.
Europe artificial intelligence (AI) in animal health market share will reach a notable CAGR between 2024 and 2032, fueled by its advanced technology infrastructure, significant investment in research and development, and stringent animal welfare regulations. The region’s strong focus on integrating innovative AI solutions into livestock and veterinary practices drives market growth. Europe’s commitment to improving animal health through cutting-edge technology and comprehensive monitoring systems positions it as a key contributor to global artificial intelligence (AI) in animal health industry.
Chapter 1 Methodology & Scope
1.1 Market scope & definitions
1.2 Research design
1.2.1 Research approach
1.2.2 Data collection methods
1.3 Base estimates & calculations
1.3.1 Base year calculation
1.3.2 Key trends for market estimation
1.4 Forecast model
1.5 Primary research and validation
1.5.1 Primary sources
1.5.2 Data mining sources
Chapter 2 Executive Summary
2.1 Industry 360° synopsis
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Industry impact forces
3.2.1 Growth drivers
3.2.1.1 Rising pet ownership and expenditure
3.2.1.2 Advancements in AI technology
3.2.1.3 Increased focus on animal disease prevention
3.2.1.4 Development of smart devices and wearables
3.2.2 Industry pitfalls & challenges
3.2.2.1 High cost of implementation
3.2.2.2 Data privacy and security concerns
3.3 Growth potential analysis
3.4 Regulatory landscape
3.5 Technology landscape
3.6 Future market trends
3.7 Porter’s analysis
3.8 PESTEL analysis
Chapter 4 Competitive Landscape, 2023
4.1 Introduction
4.2 Company matrix analysis
4.3 Competitive analysis of major market players
4.4 Competitive positioning matrix
4.5 Strategy dashboard
Chapter 5 Market Estimates and Forecast, By Solution, 2021 – 2032 ($ Mn)
5.1 Key trends
5.2 Hardware
5.3 Software
5.4 Service
Chapter 6 Market Estimates and Forecast, By Application, 2021 – 2032 ($ Mn)
6.1 Key trends
6.2 Diagnostics
6.3 Identification, tracking, and monitoring
6.4 Other applications
Chapter 7 Market Estimates and Forecast, By Animal Type, 2021 – 2032 ($ Mn)
7.1 Key trends
7.2 Companion animals
7.3 Livestock animals
Chapter 8 Market Estimates and Forecast, By End-use, 2021 – 2032 ($ Mn)
8.1 Key trends
8.2 Veterinary hospitals & clinics
8.3 Animal farms
8.4 Veterinary diagnostic laboratories
8.5 Other end-users
Chapter 9 Market Estimates and Forecast, By Region, 2021 – 2032 ($ Mn)