AI in Animal Health Market Will Reach USD 7,477.9 Million by 2033

Introduction

The Artificial Intelligence (AI) in Animal Health Market has experienced a notable surge in valuation, from USD 1,197.7 million in 2023 to an anticipated USD 7,477.9 million by 2033, achieving a Compound Annual Growth Rate (CAGR) of 20.1%. This robust growth is underpinned by the integration of cutting-edge computational methods like machine learning and data analysis, which significantly enhance diagnosis, treatment, and management of animal health. The market’s expansion is fueled by strategic initiatives from key players, such as Mars Incorporated’s acquisition of Heska Corporation in June 2023, aimed at accelerating R&D innovations and broadening access to diagnostics and technology​​.

The AI in Animal Health Market is experiencing significant growth, fueled by technological advancements and strategic investments. For instance, Boehringer Ingelheim’s substantial investment in a new strategic production center in France and Bimeda’s establishment of a manufacturing facility in China highlight the industry’s momentum. These developments promote sophisticated solutions like AI-driven surgical robotics and advanced disease diagnosis. Diagnostics, benefiting from AI’s ability to process extensive datasets, emerged as the dominant market segment in 2022. This application of AI provides critical insights into animal health, influencing production optimization and cost reduction efforts.

Moreover, the market is poised for further expansion through innovations in remote monitoring and telehealth, spurred by the COVID-19 pandemic’s push for digital healthcare solutions. North America currently leads the market, thanks to its advanced veterinary healthcare infrastructure. However, the Asia Pacific region is expected to see rapid growth, driven by rising investments in animal healthcare and the adoption of technologies such as Alibaba Cloud’s ET Agricultural Brain. Despite facing challenges like data breaches and the high costs of AI technology, the sector remains on a path of transformative growth, offering substantial opportunities for innovation in diagnostics, remote monitoring, and telehealth services.

Key Takeaways

• The AI in Animal Health Market is forecasted to grow from USD 1,197.7 million in 2023 to USD 7,477.9 million by 2033, at a CAGR of 20.1%.
• Key drivers include technological advancements in AI, enhancing diagnostics, treatment, and monitoring in veterinary healthcare.
• The diagnostics segment dominates application usage, capturing over 47.8% of the market share in 2023 due to growing AI integration in veterinary diagnostics.
• Companion animals held a major market share of 73.9% in 2023, driven by increased pet expenditures and AI-based health solutions availability.
• The production animal segment is projected to grow the fastest, propelled by the global demand for animal protein and efficient livestock management.
• Data security concerns and high AI system costs are significant barriers, hindering broader market adoption, especially in developing regions.
• Remote monitoring and telehealth through AI offer substantial growth opportunities by enabling timely veterinary care and diagnosis.
• Precision livestock farming, powered by AI, is improving farm productivity and animal welfare through optimized management and health care.
• North America led the market in 2023 with a 37.8% share, supported by advanced veterinary healthcare infrastructure and AI adoption.
• The Asia Pacific region is anticipated to see the fastest growth, driven by an increasing animal population and local AI innovations in agriculture.

AI in Animal Health Statistics

• Over 66% of U.S. households, equating to 86.9 million homes, own pets, indicating a significant market for pet-related products and services.
• Pet spending reached approximately $143.6 billion by 2023, showcasing a substantial increase in consumer expenditure on pet care.
• UF Health invested $750,000 across three years to develop an AI-powered digital imaging platform for animal diagnostics, enhancing veterinary care.
• AI technology has reduced diagnostic errors in animal health by about 25%, enhancing the accuracy of medical assessments.
• Adoption of AI-led treatments has boosted animal survival rates by approximately 30%, improving overall health outcomes.
• AI-driven monitoring systems have effectively decreased livestock mortality by around 20%, enhancing farm productivity.
• Veterinary clinics employing AI solutions have reported a notable 40% improvement in patient outcomes, enhancing medical care quality.
• AI-powered predictive models have achieved an impressive 85% accuracy rate in detecting animal diseases, aiding early diagnosis.
• Investment in AI for animal health has surged by 50% over the past year, indicating growing confidence in AI’s potential.
• AI-enabled precision farming techniques have increased animal yield by approximately 15%, optimizing agricultural practices.
• AI-based disease surveillance systems have successfully reduced outbreaks by around 30%, improving animal welfare and public health.
• AI algorithms reduce veterinary medicine drug development timelines by 40%, enhancing efficiency and innovation in the field.
• SignalPET processes 2 million+ radiographs yearly, utilizing AI to advance pet healthcare through accurate diagnostics and pathology detection.
• SignalPET’s AI identifies 50+ distinct signs in radiographic studies, aiding in comprehensive pathology detection for improved pet health outcomes.
• SignalPET’s AI maintains a consistent 95% accuracy rate, bolstering diagnostic confidence among veterinary professionals.
• With 1,000+ hospitals worldwide using SignalPET’s technology, AI in veterinary radiology sees extensive implementation and trust.
• Over 10,000 clinicians, including those from prominent US veterinary groups, leverage SignalPET’s AI solutions for enhanced diagnostic capabilities.
• Series A funding of $23 million, totaling $35 million, supports ImpriMed’s expansion into human oncology, marking a pivotal milestone.
• The SediVue Dx Urine Sediment Analyzer trains AI with 350 million urine sediment images, improving accuracy in diagnostic interpretation.
• Over 1,000 users benefit from Vetology AI, generating 154,356 AI reports, highlighting widespread adoption and utility.
• Vetology’s image bank boasts 6.6 million veterinary images, enriching AI training datasets for comprehensive diagnostic solutions.

Emerging Trends

In the rapidly evolving field of animal health, Artificial Intelligence (AI) is setting new benchmarks for care and management, heralding a transformative era for the industry. The integration of AI in animal health is enhancing early detection and diagnosis of diseases, facilitating the development of tailored treatment plans, and improving overall animal welfare. This integration is characterized by several emerging trends that are reshaping the veterinary landscape.

• Advanced Diagnostics and Treatment Planning: AI’s capability to analyze vast datasets with precision is revolutionizing diagnostics, enabling the identification of disease patterns and risk factors with unprecedented accuracy. This advancement not only aids in early disease detection but also streamlines the treatment planning process. Innovations, such as computer-implemented methods for interpreting diagnostic tests and AI-enabled digital imaging platforms, are at the forefront of this transformation, offering more effective diagnostic solutions and treatment recommendations​​.
• Enhanced Feed Products: The development of new feed products incorporating functional ingredients is another trend driven by AI and biotechnology. These products aim to boost animal health through nutrition, addressing specific dietary needs and preventing diseases. Key players in the industry are exploring feed additives and leveraging microbiome technology to introduce novel feed solutions, thereby improving animal nutrition and health outcomes​​.
• Wearable Technology and Real-time Health Monitoring: The advent of wearable sensors and real-time monitoring devices represents a significant leap forward in animal healthcare. These technologies enable continuous monitoring of animal health, allowing for early intervention and personalized care. By collecting and analyzing data on vital signs and behavior, AI-powered devices provide insights that can lead to more proactive and preventive healthcare strategies​​.
• Telemedicine and Remote Care: Telemedicine is becoming an increasingly important component of animal healthcare, facilitated by advancements in AI and digital technologies. Virtual consultations and remote monitoring services offer convenient access to veterinary care, reducing stress for both animals and their owners and ensuring timely medical intervention​​.
• Personalized Nutrition and Biotechnology: Personalized nutrition, driven by genetic testing and AI analysis, is tailoring diets to meet the individual health needs of pets, enhancing their well-being. Concurrently, biotechnology is innovating animal agriculture by improving traits such as disease resistance and meat quality through genetic engineering and cultured meat production​​.
• Blockchain for Traceability and Transparency: Blockchain technology is being applied to animal supply chains to ensure the integrity and safety of products. This technology enhances transparency, enabling stakeholders to track the movement of animals and verify the authenticity of animal products, thereby fostering trust among consumers​​.

Use Cases

• Diagnostic and Imaging Tools: AI has been increasingly adopted as a diagnostic aid in veterinary practices. It can suggest potential diagnoses and recommend therapies or further testing based on clinical signs and test findings, similar to applications in human medicine for conditions like diabetes and atrial fibrillation. AI-imbued devices, such as stethoscopes and urine sediment analysis tools, are also in use, enhancing diagnostic accuracy and efficiency​​.
• Monitoring Livestock and Precision Farming: In livestock farming, AI technologies, including machine learning algorithms, play a crucial role in monitoring animal behavior, welfare, and optimizing feeding schedules. These systems can predict disease outbreaks, monitor livestock vocalizations to assess welfare, and alter shed and aquaculture conditions to improve productivity and comply with regulatory standards. Furthermore, AI is used in pasture evaluation, optimizing hatcheries, identifying live embryos in eggs, and monitoring embryo development to enhance reproductive performance​​.
• Risk Management and Compliance: AI aids in navigating the complexities of data management, particularly in animal health, where data can be massive and heterogeneous. The challenge lies in making this data interoperable and accessible for research and practical applications, despite its often private nature and the ownership complexities. Addressing these challenges through AI can lead to better collaboration among stakeholders and more effective decision-making processes​​.
• Enhancing Animal Welfare and Practice Efficiency: AI not only accelerates the diagnosis and treatment of animals, making medical care more accessible and effective, but also plays a significant role in enhancing the operational efficiency of veterinary practices. It supports faster diagnostics, improved client communication through real-time data processing, and aids in managing the vast data collected by practices​​.
• Future Perspectives: The application of AI in animal health is poised for significant growth, with ongoing research focusing on disease prediction, abnormal image detection, and the identification of disease-related sounds. Manuscripts that explore novel machine learning approaches to control strategies, impacts of animal diseases, and the intersection of AI with One Health are particularly encouraged​​.

Recent Developments

• Merck Animal Health: A new leadership team has been announced for Merck Animal Health’s Animal Health Intelligence Operating Unit. This move signifies a strategic focus on leveraging advancements in animal health intelligence and data analytics to optimize care and management practices in the veterinary sector.
• SignalPet: SignalPet stands out for its deployment of AI-driven radiology software within veterinary practices. This technology aims to refine the precision of radiograph interpretations, thereby enhancing diagnostic accuracy and operational efficiency in animal healthcare settings.
• OneCup AI: Specializing in precision ranching technologies, OneCup AI introduces BETSY, an artificial intelligence ranch assistant designed for cattle, sheep, and horses. BETSY is equipped to monitor various health indicators such as disease presence, nutritional intake, activity levels, and growth patterns, while also featuring a revolutionary 360 Live ID™ for animal face recognition.
• ImpriMed, Inc.: ImpriMed is recognized for its pioneering work in AI-powered treatment solutions for canine cancer. The company is expanding its innovative approach to include human oncology, aiming to tailor cancer treatment plans with enhanced precision by utilizing AI to analyze responses to existing pharmaceuticals.
• IDEXX Laboratories, Inc.: IDEXX Laboratories has integrated artificial intelligence into its diagnostic equipment suite, exemplified by the ProCyte One Hematology Analyzer and SediVue Dx Analyzer. These tools leverage AI to improve accuracy and speed in diagnosing conditions from blood and urine samples, respectively.
• Zoetis Services LLC: Zoetis has enhanced its Vetscan Imagyst diagnostics platform by incorporating artificial intelligence in dermatology diagnostics and equine Fecal Egg Count (FEC) analysis. These advancements promise to elevate the standard of veterinary care through more accurate and timely diagnostics.
• VetCT: VetCT is exploring new frontiers in veterinary care by focusing on the efficiency of teleradiology processes and the acquisition and processing of imaging data. Through the adoption of AI tools, VetCT aims to streamline these processes, improving service delivery and diagnostic outcomes.
• Vetology LLC: Vetology LLC merges artificial intelligence with veterinary expertise to deliver rapid and precise radiology reports. The company’s AI-driven software has been clinically validated to enhance diagnostic accuracy, thereby supporting better health outcomes for animals.
• Petriage: Petriage has achieved a notable milestone by securing a patent for its AI-enabled online pet symptom checker. This tool, known for its 97% accuracy rate, assists pet owners in assessing the urgency of medical attention needed for their pets, marking a significant advancement in pet healthcare management.

Conclusion

In conclusion, the Artificial Intelligence (AI) in Animal Health Market is on a trajectory of rapid and transformative growth, largely driven by the continuous advancements in technology and strategic investments by key players. This growth is not just numerical but reflects a profound shift in how veterinary care is delivered, with AI enhancing diagnostics, treatment planning, and operational efficiencies. The market faces challenges such as data security and the high costs of AI systems, yet the opportunities for innovation in diagnostics, telehealth, and precision livestock farming are immense. As the sector moves forward, the integration of AI in animal health promises to revolutionize veterinary practices, improve animal welfare, and offer a more personalized approach to animal healthcare. The future of this market is bright, with AI at the forefront of shaping a new era in animal health services.