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AI in Animal Health Market By Technology (Machine Learning, Natural Language Processing, Computer Vision, Robotics), By Application (Disease Diagnosis, Drug Discovery, Monitoring & Surveillance, Animal Behavior Monitoring, Veterinary Imaging), By Animal Type (Livestock, Companion Animals, Aquatic Animals), By End-User (Veterinary Hospitals & Clinics, Research & Diagnostic Labs, Pharmaceutical Companies, Government & Academic Institutes), and By Region; Global Insights & Forecast (2024 – 2030)

Published: December, 2024  
|   Report ID: ANH4646  
|   Animal Nutrition & Health

As per Intent Market Research, the AI in Animal Health Market was valued at USD 1.1 billion in 2023 and will surpass USD 3.8 billion by 2030; growing at a CAGR of 19.0% during 2024 - 2030.

The AI in animal health market has grown substantially in recent years, as the adoption of artificial intelligence technologies transforms the way animal health management, diagnosis, and treatment are approached. AI solutions are enabling more efficient, accurate, and cost-effective methods of diagnosing diseases, developing drugs, and monitoring animal behavior. With the increasing focus on animal welfare, productivity, and precision livestock farming, the market is expected to continue expanding as these technologies become more integrated into veterinary practices, livestock management, and companion animal care. AI’s role in enhancing animal health outcomes has made it a key driver for innovation in the sector.

Machine Learning Technology Is Largest Owing to Its Role in Diagnostics and Disease Prediction

Machine learning (ML) is the largest subsegment within the technology segment of the AI in animal health market, driving significant growth and adoption across veterinary diagnostics, disease prediction, and behavior analysis. ML’s ability to analyze vast amounts of data and recognize patterns has proven invaluable in identifying early signs of illness in animals, optimizing treatment plans, and predicting disease outbreaks. This capability is critical in both livestock management, where early detection can prevent large-scale losses, and in companion animal care, where it aids in diagnosing conditions faster and more accurately than traditional methods.

Machine learning algorithms continue to evolve, with advancements allowing for the development of AI systems that can learn and improve over time. As a result, ML is increasingly being integrated into veterinary practices and livestock management solutions. These systems not only support veterinary professionals in diagnosing and treating animals but also help in predictive analytics, which can foresee potential health risks and prevent the onset of diseases. The increasing adoption of machine learning-based tools in the animal health sector ensures its dominance within the technology segment.

Animal Health Market Size

Disease Diagnosis Application Is Fastest Growing Owing to AI's Impact on Early Detection

In the application segment, disease diagnosis is the fastest-growing subsegment within the AI in animal health market. The need for accurate and timely disease detection is paramount in veterinary care, especially with the rising concerns over zoonotic diseases and livestock epidemics. AI-powered diagnostic tools using machine learning and computer vision technologies enable veterinarians to detect diseases at early stages, thereby improving treatment outcomes and preventing the spread of infectious diseases. Additionally, AI-driven diagnostic systems allow for faster, more efficient processing of medical imaging, reducing the burden on veterinary professionals and enhancing the quality of care.

The focus on disease diagnosis is growing, especially in response to the increased demand for precision medicine in both companion animals and livestock. These systems can analyze medical images such as X-rays, ultrasounds, and MRIs with remarkable accuracy, often detecting conditions that may go unnoticed by human clinicians. As the healthcare industry increasingly prioritizes preventive care, AI-driven diagnostics are poised to play a pivotal role in revolutionizing veterinary practices globally.

Livestock Animal Type Is Largest Owing to Advancements in Precision Livestock Farming

The livestock segment remains the largest within the animal type category in the AI in animal health market. With the growing need for more efficient livestock management and the focus on improving productivity, AI technologies in precision livestock farming are proving invaluable. Livestock farmers are increasingly adopting AI solutions to monitor the health of animals, predict diseases, track growth, and optimize feed, which contributes to better yield and lower costs. The rise of AI-powered systems that provide real-time monitoring and automated alerts for disease outbreaks is accelerating the adoption of these technologies in the livestock sector.

Moreover, AI-driven systems are helping farmers move toward sustainable practices, such as reducing antibiotic use and enhancing animal welfare. Precision livestock farming solutions that incorporate AI allow for more personalized care for animals, which is critical to ensuring their health and productivity. The increasing demand for AI-based solutions in livestock management is expected to continue driving the growth of this segment as more farms seek to optimize operations through technological integration.

Veterinary Hospitals & Clinics End-User Is Largest Owing to Increasing Adoption of AI Solutions

The veterinary hospitals and clinics segment is the largest subsegment in the end-user category of the AI in animal health market. Veterinary clinics are increasingly incorporating AI-driven diagnostic tools and imaging systems to improve the accuracy and efficiency of their services. AI-based solutions assist veterinary professionals in diagnosing conditions such as infections, tumors, and bone fractures, enabling quicker and more accurate results. Additionally, AI technologies help in monitoring pet health and behavior, offering personalized care to companion animals, which strengthens the bond between veterinarians and pet owners.

Veterinary hospitals and clinics have also embraced AI for streamlining administrative tasks such as appointment scheduling, patient management, and treatment planning. The rise in the number of pet owners and the growing demand for advanced healthcare for pets contribute to the increasing reliance on AI solutions in veterinary practices. The trend of expanding veterinary services through AI-driven technologies is expected to continue, making this segment the largest in terms of adoption and growth.

North America Region Is Largest Owing to Technological Advancements and Strong Market Presence

The North America region holds the largest share of the AI in animal health market. This dominance is attributed to the region's advanced healthcare infrastructure, high adoption rates of innovative technologies, and a strong presence of key players in the veterinary and animal health sectors. In particular, the U.S. has seen significant investments in AI research and development, contributing to rapid advancements in disease diagnosis, behavior monitoring, and livestock management. The region’s veterinary professionals and animal health organizations are highly receptive to the adoption of AI, and regulatory frameworks are increasingly accommodating, enabling seamless integration of AI solutions in clinical and agricultural settings.

The growth of AI in North America is further fueled by a high level of awareness regarding animal health and welfare, as well as increased spending on pet care. With major players like Zoetis, Merck, and IDEXX Laboratories headquartered in the U.S., the region is likely to maintain its leading position in the global market.

Animal Health Market Size by Region 2030

Competitive Landscape: Leading Companies and Market Dynamics

The AI in animal health market is highly competitive, with several prominent players dominating the landscape. Leading companies include Zoetis, Bayer AG, Merck & Co., IDEXX Laboratories, and Elanco, which are at the forefront of technological innovation in veterinary diagnostics, livestock monitoring, and animal health management. These companies are focusing on the development and integration of AI-driven solutions into their product portfolios, aiming to enhance the accuracy and efficiency of diagnostics and improve overall animal care.

The competitive landscape is characterized by a mix of large multinational corporations and smaller, innovative startups that focus on AI technologies for veterinary applications. Strategic partnerships, mergers, and acquisitions are common in this market, as companies seek to expand their technological capabilities and reach new customers. Ongoing research and development investments, coupled with the increasing demand for precision medicine and livestock farming solutions, will continue to drive competition in the AI in animal health market, with companies striving to maintain leadership in this rapidly evolving sector.

Recent Developments:

  • Zoetis launched an AI-powered diagnostic tool to enhance disease detection in livestock.
  • Bayer AG acquired an AI-based veterinary diagnostics startup to expand its disease diagnosis capabilities.
  • Elanco Animal Health partnered with an AI tech firm to improve precision livestock management.
  • IDEXX Laboratories introduced an AI-driven imaging system for faster, more accurate veterinary diagnostics.
  • Merck & Co., Inc. received approval for its AI vaccine development platform for livestock diseases.

List of Leading Companies:

  • Bayer AG
  • Zoetis Inc.
  • Merck & Co., Inc.
  • IDEXX Laboratories
  • Elanco Animal Health
  • Cargill Inc.
  • Vetoquinol S.A.
  • Mars Petcare
  • Merial (acquired by Boehringer Ingelheim)
  • Virbac
  • Heska Corporation
  • Agri-Tech East
  • Teledyne Technologies
  • Aquabyte
  • PetPace

Report Scope:

Report Features

Description

Market Size (2023)

USD 1.1 Million

Forecasted Value (2030)

USD 3.8 Billion

CAGR (2024 – 2030)

19.0%

Base Year for Estimation

2023

Historic Year

2022

Forecast Period

2024 – 2030

Report Coverage

Market Forecast, Market Dynamics, Competitive Landscape, Recent Developments

Segments Covered

AI in Animal Health Market By Technology (Machine Learning, Natural Language Processing, Computer Vision, Robotics), By Application (Disease Diagnosis, Drug Discovery, Monitoring & Surveillance, Animal Behavior Monitoring, Veterinary Imaging), By Animal Type (Livestock, Companion Animals, Aquatic Animals), By End-User (Veterinary Hospitals & Clinics, Research & Diagnostic Labs, Pharmaceutical Companies, Government & Academic Institutes)

Regional Analysis

North America (US, Canada, Mexico), Europe (Germany, France, UK, Italy, Spain, and Rest of Europe), Asia-Pacific (China, Japan, South Korea, Australia, India, and Rest of Asia-Pacific), Latin America (Brazil, Argentina, and Rest of Latin America), Middle East & Africa (Saudi Arabia, UAE, Rest of Middle East & Africa)

Major Companies

Bayer AG, Zoetis Inc., Merck & Co., Inc., IDEXX Laboratories, Elanco Animal Health, Cargill Inc., Vetoquinol S.A., Mars Petcare, Merial (acquired by Boehringer Ingelheim), Virbac, Heska Corporation, Agri-Tech East, Teledyne Technologies, Aquabyte, PetPace

Customization Scope

Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements

1. Introduction

   1.1. Market Definition

   1.2. Scope of the Study

   1.3. Research Assumptions

   1.4. Study Limitations

2. Research Methodology

   2.1. Research Approach

      2.1.1. Top-Down Method

      2.1.2. Bottom-Up Method

      2.1.3. Factor Impact Analysis

  2.2. Insights & Data Collection Process

      2.2.1. Secondary Research

      2.2.2. Primary Research

   2.3. Data Mining Process

      2.3.1. Data Analysis

      2.3.2. Data Validation and Revalidation

      2.3.3. Data Triangulation

3. Executive Summary

   3.1. Major Markets & Segments

   3.2. Highest Growing Regions and Respective Countries

   3.3. Impact of Growth Drivers & Inhibitors

   3.4. Regulatory Overview by Country

4. AI in Animal Health Market, by Technology (Market Size & Forecast: USD Million, 2022 – 2030)

   4.1. Machine Learning

   4.2. Natural Language Processing

   4.3. Computer Vision

   4.4. Robotics

   4.5. Others

5. AI in Animal Health Market, by Application (Market Size & Forecast: USD Million, 2022 – 2030)

   5.1. Disease Diagnosis

   5.2. Drug Discovery

   5.3. Monitoring & Surveillance

   5.4. Animal Behavior Monitoring

   5.5. Veterinary Imaging

6. AI in Animal Health Market, by Animal Type (Market Size & Forecast: USD Million, 2022 – 2030)

   6.1. Livestock

   6.2. Companion Animals

   6.3. Aquatic Animals

   6.4. Others

7. AI in Animal Health Market, by End-User (Market Size & Forecast: USD Million, 2022 – 2030)

   7.1. Veterinary Hospitals & Clinics

   7.2. Research & Diagnostic Labs

   7.3. Pharmaceutical Companies

   7.4. Government & Academic Institutes

8. Regional Analysis (Market Size & Forecast: USD Million, 2022 – 2030)

   8.1. Regional Overview

   8.2. North America

      8.2.1. Regional Trends & Growth Drivers

      8.2.2. Barriers & Challenges

      8.2.3. Opportunities

      8.2.4. Factor Impact Analysis

      8.2.5. Technology Trends

      8.2.6. North America AI in Animal Health Market, by Technology

      8.2.7. North America AI in Animal Health Market, by Application

      8.2.8. North America AI in Animal Health Market, by Animal Type

      8.2.9. North America AI in Animal Health Market, by End-User

      8.2.10. By Country

         8.2.10.1. US

               8.2.10.1.1. US AI in Animal Health Market, by Technology

               8.2.10.1.2. US AI in Animal Health Market, by Application

               8.2.10.1.3. US AI in Animal Health Market, by Animal Type

               8.2.10.1.4. US AI in Animal Health Market, by End-User

         8.2.10.2. Canada

         8.2.10.3. Mexico

    *Similar segmentation will be provided for each region and country

   8.3. Europe

   8.4. Asia-Pacific

   8.5. Latin America

   8.6. Middle East & Africa

9. Competitive Landscape

   9.1. Overview of the Key Players

   9.2. Competitive Ecosystem

      9.2.1. Level of Fragmentation

      9.2.2. Market Consolidation

      9.2.3. Product Innovation

   9.3. Company Share Analysis

   9.4. Company Benchmarking Matrix

      9.4.1. Strategic Overview

      9.4.2. Product Innovations

   9.5. Start-up Ecosystem

   9.6. Strategic Competitive Insights/ Customer Imperatives

   9.7. ESG Matrix/ Sustainability Matrix

   9.8. Manufacturing Network

      9.8.1. Locations

      9.8.2. Supply Chain and Logistics

      9.8.3. Product Flexibility/Customization

      9.8.4. Digital Transformation and Connectivity

      9.8.5. Environmental and Regulatory Compliance

   9.9. Technology Readiness Level Matrix

   9.10. Technology Maturity Curve

   9.11. Buying Criteria

10. Company Profiles

   10.1. Bayer AG

      10.1.1. Company Overview

      10.1.2. Company Financials

      10.1.3. Product/Service Portfolio

      10.1.4. Recent Developments

      10.1.5. IMR Analysis

    *Similar information will be provided for other companies 

   10.2. Zoetis Inc.

   10.3. Merck & Co., Inc.

   10.4. IDEXX Laboratories

   10.5. Elanco Animal Health

   10.6. Cargill Inc.

   10.7. Vetoquinol S.A.

   10.8. Mars Petcare

   10.9. Merial (acquired by Boehringer Ingelheim)

   10.10. Virbac

   10.11. Heska Corporation

   10.12. Agri-Tech East

   10.13. Teledyne Technologies

   10.14. Aquabyte

   10.15. PetPace

11. Appendix

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A comprehensive market research approach was employed to gather and analyze data on the AI in Animal Health Market. In the process, the analysis was also done to analyze the parent market and relevant adjacencies to measure the impact of them on the AI in Animal Health Market. The research methodology encompassed both secondary and primary research techniques, ensuring the accuracy and credibility of the findings.

Research Approach - Animal Health MarketSecondary Research

Secondary research involved a thorough review of pertinent industry reports, journals, articles, and publications. Additionally, annual reports, press releases, and investor presentations of industry players were scrutinized to gain insights into their market positioning and strategies.

Primary Research

Primary research involved conducting in-depth interviews with industry experts, stakeholders, and market participants across the AI in Animal Health ecosystem. The primary research objectives included:

  • Validating findings and assumptions derived from secondary research
  • Gathering qualitative and quantitative data on market trends, drivers, and challenges
  • Understanding the demand-side dynamics, encompassing end-users, component manufacturers, facility providers, and service providers
  • Assessing the supply-side landscape, including technological advancements and recent developments

Market Size Assessment

A combination of top-down and bottom-up approaches was utilized to analyze the overall size of the AI in Animal Health Market. These methods were also employed to assess the size of various subsegments within the market. The market size assessment methodology encompassed the following steps:

  1. Identification of key industry players and relevant revenues through extensive secondary research
  2. Determination of the industry's supply chain and market size, in terms of value, through primary and secondary research processes
  3. Calculation of percentage shares, splits, and breakdowns using secondary sources and verification through primary sources

Bottom Up and Top Down - Animal Health MarketData Triangulation

To ensure the accuracy and reliability of the market size, data triangulation was implemented. This involved cross-referencing data from various sources, including demand and supply side factors, market trends, and expert opinions. Additionally, top-down and bottom-up approaches were employed to validate the market size assessment.

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