InsightAce Analytic Pvt. Ltd. announces the release of a market assessment report on the “Global Artificial Intelligence (AI) In Animal Health Market- (By Solution (Hardware, Software & Services), By Application (Diagnostics, Identification, Tracking, and Monitoring, Others), By Animal Type (Companion Animals, Production Animals)), Trends, Industry Competition Analysis, Revenue and Forecast To 2031.”
According to the latest research by InsightAce Analytic, the Global Artificial Intelligence (AI) In Animal Health Market is valued at US$ 970.44 in 2022, and it is expected to reach US$ 4432.16 Mn by 2031, with a CAGR of 18.6% during a forecast period of 2023-2031.
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AI can analyze electronic health records and other animal data to predict probable health risks. Predictive analytics allows veterinarians to intervene early and provide proactive care, improving results and lowering healthcare costs. Key market growth factors comprises increased AI applications in animal health, the availability of AI-based solutions, activities by key firms, rising animal health expenditure, and the need for better animal health outcomes. The availability of massive volumes of animal health data, such as medical imaging, electronic health records, and genomic data, was a major motivator for AI use. These massive datasets were critical for training and upgrading AI models. Virtual veterinary assistants and AI-powered chatbots are becoming increasingly common, allowing pet owners to quickly get basic health information and support. These apps bridged the gap between pet owners and doctors by assisting outside of typical clinic hours. The growing interest in AI applications for animal health has resulted in substantial investments from both the business and public sectors, thus boosting market growth.
List of Market Players in the Artificial Intelligence (AI) In Animal Health Market:
Market Dynamics:
Drivers-
Continuous improvements in AI technologies, notably machine learning and deep learning, enabled increasingly sophisticated algorithms to manage complicated animal health concerns. AI algorithms’ performance and accuracy in animal health applications improved as they developed. Machine learning algorithms have aided in drug discovery and development by analyzing large biological datasets, discovering trends, and predicting the efficacy of new treatments.
Challenges:
For efficient training, AI systems need a lot of high-quality datasets. Accessing a variety of large datasets in animal health might be difficult. Problems with data protection, standardization, and interoperability additionally hamper the sharing and aggregation of animal health data. Creating and implementing AI-based solutions for animal health also calls for specialized knowledge in AI and veterinary medicine. The lack of qualified individuals with in-depth knowledge of both fields may hamper the creation and application of AI technology.
Regional Trends:
The North America Artificial Intelligence (AI) In Animal Health Market is expected to register a maximum market share and is expected to grow at a high CAGR in the near future. The animal health sector in North America has been developed and comprised of veterinary clinics, research facilities, pharmaceutical enterprises, and IT companies. The development of complex AI algorithms for applications in animal health was sparked by the region’s strong emphasis on research and development, particularly in AI and machine learning. More recently, AI and machine learning technologies have been advancing quickly in the Asia Pacific area, particularly in China, Japan, South Korea, and India. The creation of AI-based solutions for animal health benefited from this fruitful environment.
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Recent Developments:
Segmentation of Artificial Intelligence (AI) In Animal Health Market-
By Solution-
By Application-
By Animal Type-
By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
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