세계의 동물 건강용 인공지능(AI) 시장은 2024년에 11억 2,120만 달러로 평가되며, 예측 기간에는 2030년까지 CAGR이 11.10%로 견고한 성장이 예측됩니다.
세계의 동물 건강용 인공지능(AI) 시장은 수의학 및 동물 헬스케어 산업에서 역동적이고 혁신적인 힘으로 부상하고 있습니다. 최첨단 기술을 활용한 AI는 동물의 진단, 치료 및 관리 방식에 혁명을 일으켜 동물 복지 향상, 질병 관리 강화, 보다 효율적인 수의학 진료로 이어지고 있습니다. 머신러닝, 컴퓨터 비전, 자연 언어 처리, 예측 분석 등 AI 기술은 동물 의료의 다양한 문제를 해결하기 위해 활용되고 있습니다. AI 알고리즘은 엑스레이, MRI와 같은 의료 영상과 생체 샘플에서 얻은 방대한 양의 데이터를 분석하여 사람의 눈에는 보이지 않는 미묘한 패턴과 이상을 식별할 수 있습니다. 이 기능을 통해 수의사는 암, 관절 질환, 감염 등의 질병을 조기에 발견할 수 있으며, 신속한 개입이 용이해져 치료 성공 가능성을 높일 수 있습니다.
| 시장 개요 | |
|---|---|
| 예측 기간 | 2026-2030년 |
| 시장 규모 : 2024년 | 11억 2,120만 달러 |
| 시장 규모 : 2030년 | 21억 1,313만 달러 |
| CAGR : 2025-2030년 | 11.10% |
| 급성장 부문 | 진단약 |
| 최대 시장 | 북미 |
AI를 통한 예측 분석이 동물의 헬스케어에 혁명을 일으키고 있습니다. AI 시스템은 과거 건강 데이터, 유전 정보, 환경적 요인을 분석하여 잠재적인 건강 위험과 질병 발생에 대한 인사이트와 예측을 생성할 수 있습니다. 이러한 사전 예방적 접근 방식을 통해 수의사 및 동물 위생 전문가들은 예방 조치를 시행하고, 백신 접종 전략을 최적화하며, 동물 개체군내 질병 확산을 최소화할 수 있습니다. 원격의료와 원격 모니터링 역시 AI의 통합으로 큰 활기를 띠고 있습니다. 웨어러블 기기 및 센서의 도움으로 AI 기반 시스템은 동물의 활력 징후, 행동 및 활동 수준을 지속적으로 모니터링할 수 있습니다. 이 실시간 데이터는 수의사 전문가에게 전송되어 동물의 건강 상태를 원격으로 추적하고 필요한 경우 적시에 개입할 수 있습니다. 이는 질병의 조기 발견이 경제적 손실을 방지하고 식품 공급망의 안전을 보장할 수 있는 가축 관리에 특히 유용합니다. 가축 위생에 AI를 도입하면 합리적이고 맞춤 치료 계획을 수립할 수 있습니다. AI 알고리즘은 개별 동물의 특성, 병력, 치료 결과를 분석하여 수의사가 각 환자에게 최적화된 치료 프로토콜을 조정하는 데 도움을 줄 수 있습니다. 이러한 수준의 커스터마이징은 치료 효과를 향상시킬 뿐만 아니라 부작용을 최소화하고 보호자의 의료 비용을 절감할 수 있습니다. 그러나 동물 건강 분야의 AI 시장은 기대와 함께 몇 가지 과제에 직면해 있습니다. 데이터 프라이버시 및 보안에 대한 우려와 견고하고 다양한 데이터세트의 필요성은 중요한 고려 사항입니다. 또한 기존 수의학 진료에 AI 기술을 통합하려면 효과적인 활용과 최적의 결과를 보장하기 위해 수의사 및 동물 의료 전문가에 대한 적절한 훈련과 교육이 필요합니다.
애완동물 사육 증가와 수의료 수요의 증가
데이터 프라이버시와 보안에 대한 우려
영상 진단에서 AI의 통합
Global Artificial Intelligence (AI) In Animal Health Market was valued at USD 1121.20 Million in 2024 and is anticipated to project robust growth in the forecast period with a CAGR of 11.10% through 2030. The global Artificial Intelligence (AI) in Animal Health market has emerged as a dynamic and transformative force within the veterinary and animal healthcare industry. Leveraging cutting-edge technologies, AI is revolutionizing the way animals are diagnosed, treated, and cared for, leading to improved animal welfare, enhanced disease management, and more efficient veterinary practices. AI technologies, including machine learning, computer vision, natural language processing, and predictive analytics, are being harnessed to address various challenges in animal health. One of the significant areas of impact is in the early detection and diagnosis of diseases. AI algorithms can analyze vast amounts of data from medical images, such as X-rays and MRIs, as well as biological samples, to identify subtle patterns and anomalies that might escape the human eye. This capability enables veterinarians to detect diseases like cancer, joint disorders, and infections at earlier stages, facilitating prompt intervention and increasing the chances of successful treatment.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 1121.20 Million |
| Market Size 2030 | USD 2113.13 Million |
| CAGR 2025-2030 | 11.10% |
| Fastest Growing Segment | Diagnostics |
| Largest Market | North America |
AI-driven predictive analytics are revolutionizing animal health management. By analyzing historical health data, genetic information, and environmental factors, AI systems can generate insights and forecasts about potential health risks and disease outbreaks. This proactive approach allows veterinarians and animal health professionals to implement preventive measures, optimize vaccination strategies, and minimize the spread of diseases within animal populations. Telemedicine and remote monitoring have also witnessed a significant boost through AI integration. With the help of wearable devices and sensors, AI-powered systems can continuously monitor animals' vital signs, behavior, and activity levels. This real-time data can be transmitted to veterinary professionals, enabling them to remotely track an animal's health status and provide timely interventions when necessary. This is particularly valuable for livestock management, where the early detection of illnesses can prevent economic losses and ensure the safety of the food supply chain. The adoption of AI in animal health has led to streamlined and personalized treatment plans. By analyzing individual animal characteristics, medical history, and treatment outcomes, AI algorithms can assist veterinarians in tailoring treatment protocols that are optimized for each patient. This level of customization not only improves the efficacy of treatments but also minimizes adverse effects and reduces healthcare costs for animal owners. However, along with its promises, the AI in Animal Health market also faces certain challenges. Data privacy and security concerns, as well as the need for robust and diverse datasets, are critical considerations. Additionally, the integration of AI technologies into established veterinary practices requires proper training and education for veterinarians and animal health professionals to ensure effective utilization and optimal outcomes.
Key Market Drivers
Increasing Pet Ownership and Demand for Veterinary Care
The global artificial intelligence (AI) in animal health market is experiencing significant expansion, largely fueled by rising pet ownership and the growing demand for advanced veterinary care. A significant 71% of adults residing in rural areas own at least one pet, highlighting the strong prevalence of pet ownership in these regions. Additionally, rural residents are more likely to have multiple pets, with 47% owning more than one. In comparison, 32% of suburban residents and 26% of urban dwellers have multiple pets, indicating a higher concentration of pet ownership in rural communities. As more households' welcome pets, the need for efficient, cost-effective, and technology-driven veterinary solutions is increasing. AI is playing a transformative role in enhancing pet healthcare services, from early disease detection to personalized treatment plans.
Key Market Challenges
Data Privacy and Security Concerns
Data privacy and security concerns are significant challenges in the global Artificial Intelligence (AI) in Animal Health market, as the integration of AI technologies into veterinary practices requires the handling of sensitive and personal animal health data. These concerns revolve around the protection of confidential information, prevention of unauthorized access, and the ethical use of data to ensure that the benefits of AI are realized without compromising privacy and security. In the AI-driven Animal Health Market, vast amounts of data are collected from various sources, including electronic health records, medical images, genetic information, and sensor data from wearable devices. This data is used to train AI algorithms and generate insights for early disease detection, predictive analytics, and personalized treatment plans. However, the potential risks associated with data privacy and security must be carefully managed. One primary concern is the risk of data breaches and unauthorized access. Veterinary clinics, research institutions, and other stakeholders collect and store sensitive information about animals, their health conditions, and genetic profiles.
Key Market Trends
Integration of AI in Diagnostic Imaging
The integration of AI in diagnostic imaging within the global Artificial Intelligence (AI) in Animal Health Market refers to the application of AI technologies to enhance the accuracy, efficiency, and interpretation of medical images used in veterinary diagnosis and treatment. AI algorithms are employed to analyze and process various types of diagnostic images, such as X-rays, MRIs, CT scans, and ultrasounds, with the aim of aiding veterinarians in identifying abnormalities, diseases, and conditions in animals. AI's role in diagnostic imaging involves pattern recognition, anomaly detection, and image segmentation. By learning from vast datasets, AI algorithms can pinpoint subtle details and deviations that may go unnoticed by the human eye. This technology can assist veterinarians in making more informed and timely diagnoses, leading to improved treatment planning and better outcomes for animals. The integration of AI in diagnostic imaging holds the potential to revolutionize veterinary care by reducing human error, accelerating the diagnostic process, and enhancing the overall quality of medical imaging analysis. It can also enable veterinarians to focus on complex cases and critical decisions, while routine tasks are automated by AI algorithms. Overall, the integration of AI in diagnostic imaging represents a significant advancement in the AI in Animal Health Market, contributing to the advancement of veterinary medicine and providing a valuable tool for accurate and efficient diagnosis and treatment of animals.
Zoetis Services LLC
Merck & Co., Inc.
Laboratory Corporation of America Holdings
Heska Corporation
SignalPET
VetCT
Vetology LLC.
OneCup AI
Petriage
ImpriMed, Inc.
In this report, the Global Artificial Intelligence (AI) In Animal Health Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
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Company Profiles: Detailed analysis of the major companies present in the Global Artificial Intelligence (AI) In Animal Health Market.
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