Delray Beach, FL, June 03, 2025 (GLOBE NEWSWIRE) — The global AI in Remote Patient Monitoring Market valued at US$1551.8 million in 2023, stood at US$1,967.7 million in 2024 and is projected to advance at a resilient CAGR of 27.5% from 2024 to 2030, culminating in a forecasted valuation of US$8,438.5 million by the end of the period. The growing number of elderly people and the growing need for affordable healthcare solutions are the main factors propelling the AI in remote patient monitoring market. The United Nations Population Fund (UNFPA) predicts people aged 65 and older will grow from 10.3% worldwide population in 2024 to 20.7% by 2074. People aged 65+ will put a high strain on health services since healthcare budgets remain limited.
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By component, the artificial intelligence in remote patient monitoring market has been segmented into devices, software and services. In 2023, devices segment is estimated to hold the largest share of the market for AI in remote patient monitoring. AI-powered wearables like smartwatches and biosensors enable seamless, real-time health tracking, while portable and handheld devices such as AI-driven ECG monitors and glucose meters support remote diagnostics and chronic disease management. In the hospital environment, these stationary devices have helped increase the efficiency of Remote Patient Monitoring by functioning alongside enhanced AI analytics, cloud computing, and the Internet of Medical Things for optimum data transmission. As part of its continued commitment to telehealth and easily available, technologically enabled patient care, the Department of Veterans Affairs (VA) initiated several projects in 2025 to enhance remote patient monitoring (RPM). Among those were contracts to establish systems to allow tracking via telemetry for some 35 VA Medical Centers.
By end-user, the global AI in remote patient monitoring market has seen significant growth at a very rapid pace. The patient segment is anticipated to be the biggest driver of growth in this sector. Factors such as the rising prevalence of chronic diseases, growing awareness of personalized healthcare, and increased patient engagement in self-monitoring are driving this growth. By enabling early disease detection, predictive analytics, and real-time monitoring of health, AI improves RPM, reduces hospital stays length, and recommends better patient outcomes. Real-time monitoring of health due to AI, predictive analytics, and early detection of diseases forms RPM to result in reduced hospital stay lengths and improved patient outcomes. AI-powered virtual assistants, digital health platforms, and remote diagnostics allow remote patient monitoring to become …