by Joy Nelloolichalil • 22 Nov 2024 • Originally Posted on Global Pet Industry
Advanced technology is transforming pet healthcare, improving monitoring, diagnosis and treatment
Artificial intelligence (AI) is increasingly shaping the way we care for companion animals. From continuous health monitoring to early diagnosis and remote care, AI-powered tools are tackling long-standing gaps in traditional veterinary practices. These innovations are designed to detect subtle changes earlier, provide more personalized health insights, and support pet owners and clinicians with timely information.
One pet, one profile
Among the most significant developments are wearables and health-monitoring applications that create individualized health baselines for pets. Wearable devices equipped with multiple sensors can collect continuous biometric data—such as heart rate, temperature, activity levels and location—and feed that data into algorithms that learn each animal’s normal patterns.
PetPace, a US company, has been a prominent provider of smart collars since 2016. The company developed its AI-enabled collars to address a common problem in veterinary medicine: many illnesses are only discovered after they have progressed. PetPace focuses on older dogs and animals with known medical conditions, and its collars are intended to offer close monitoring so changes can be detected earlier.
“Each dog’s collar is collecting data continuously. We’re sampling data almost twice per second,” Dr. Asaf Dagan, Chief Veterinary Scientist at PetPace, explains.
With continuous sampling, PetPace builds a unique biometric profile for every pet, establishing a reliable baseline of what is normal for that individual. If the pet’s vitals, behavior or other metrics deviate from that baseline, AI flags the change. The system can also compare an animal’s data with aggregated data from similar animals—by breed, age, or size—to help indicate whether the pet’s condition is within expected ranges for its cohort.
Early diagnosis
Other AI approaches rely on advanced image and video analysis rather than wearables. South Korea’s AI For Pet offers the TTCare app, which uses image recognition algorithms to evaluate clinical signs from photos or short videos. By reviewing images of eyes, teeth, skin, or analyzing gait from a video, the app can identify visual signs of common conditions such as eye infections, dental problems and skin disorders.
The TTCare model was trained on millions of scans and validated with veterinary expertise. Its preliminary assessments are intended to help veterinarians and pet care providers spot potential issues earlier and prioritize cases that may need in-person attention. While the app does not replace a professional diagnosis, it can serve as an efficient triage and early-warning tool.
Market growth and emerging concerns
The market for AI in pet health has grown rapidly. Research firm Grand View Research estimated the global market at $997.3 million (€895.7M) in 2022, and projected a compound annual growth rate of about 19% through 2030. The COVID-19 pandemic accelerated demand for remote care and digital tools, as access to clinics became more challenging and owners sought new ways to monitor their pets’ health from home.
“We saw a significant increase in the use of our AI technology by both pet service providers and clinics,” says Euna Huh, CEO at AI For Pet.
AI-powered health checks and remote consultations rose notably between 2020 and 2022, reflecting wider adoption among clinics and pet-care services. At the same time, experts caution that the rapid growth of AI tools brings challenges. Some vendors use “AI” as a marketing label without the deep data and rigorous analytics required to support reliable medical assessments. Properly functioning AI systems typically require extensive, high-quality datasets, validated algorithms and clinical oversight to make meaningful, trustworthy inferences.
“To genuinely qualify as AI, you need vast amounts of data. You can’t make a diagnosis on just a few data points. It also requires advanced analytics, algorithms and models that go beyond basic statistics.”
Recent innovations and broader uses
Companies continue to expand applications of their technology. PetPace recently introduced a pregnancy-tracking program designed for dog breeders, leveraging continuous biometric monitoring to support breeders through gestation. The company is also exploring non-medical uses for its sensor technology, such as an earthquake-warning initiative. Research indicates animals may exhibit behavioral or physiological changes before seismic events, and sensor data from many animals could potentially contribute to early-warning systems; PetPace’s work is currently advancing through field testing in Peru.
In South Korea, innovators are combining sensors and connectivity into new formats, including smart leashes that monitor temperature and pulse, and smart litter or toilet systems designed to detect early signs of urinary tract infections from waste analysis. Government programs and investment in the region aim to scale these innovations, with ambitions to substantially grow the pet healthcare sector in the coming years.
As AI tools for pet health continue to evolve, their value will depend on rigorous validation, meaningful datasets, clinician involvement, and clear communication with pet owners. When responsibly developed and deployed, these technologies hold real promise to improve early detection, personalize care, and support healthier, longer lives for companion animals.