AI In Blood Pressure Monitoring Market Size, Share & Trends Analysis growing at a CAGR of 29.98% from 2025 to 2030
The global AI in blood pressure monitoring market size was estimated at USD 932.52 million in 2024 and is projected to reach USD 4.38 billion by 2030, growing at a CAGR of 29.98% from 2025 to 2030. Rising prevalence of hypertension and cardiovascular diseases, increasing demand for continuous and non-invasive monitoring, and growing consumer adoption of smart health devices are significant factors contributing to market growth.
Key Market Trends & Insights
- North America AI in blood pressure monitoring market accounted for the largest revenue share of over 49% in 2024.
- The U.S. AI in blood pressure monitoring market held the largest market share in 2024.
- By end use, the hospitals & acute care segment held the largest market share of over 39% in 2024.
- By application, the hypertension management segment accounted for the largest revenue share of over 37% in 2024.
- By technology, the machine learning segment accounted for the largest revenue share of over 51% in 2024.
Market Size & Forecast
- 2024 Market Size: USD 932.52 Million
- 2030 Projected Market Size: USD 4.38 Billion
- CAGR (2025-2030): 29.98%
- North America: Largest market in 2024
- Asia Pacific: Fastest growing market
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In addition, advancements in AI and sensor technologies and integration with telehealth & remote patient monitoring platforms are some other factors fueling market growth further. The increasing prevalence of hypertension and cardiovascular disorders (CVDs) globally significantly contributes to the AI in blood pressure monitoring market growth. For instance, according to the World Health Organization, an estimated 1.28 billion adults (aged 30-79 years) are currently living with hypertension. In addition, CVDs are the leading cause of death globally, causing an estimated 17.9 million deaths each year. This case surge pressures healthcare systems to adopt technologies that offer early detection, real-time monitoring, and proactive intervention. AI-powered blood pressure monitors help early detection of irregularities, supporting proactive disease management.
Machine learning and AI algorithms have made significant advancements in signal processing, data interpretation, and pattern recognition. With advanced biosensors and IoT connectivity, AI analyzes blood pressure data alongside other health metrics such as heart rate, activity levels, oxygen concentration, and sleep quality. These advancements have enhanced the accuracy, predictive capabilities, and personalization of blood pressure monitoring systems. In addition, edge AI allows faster processing and real-time feedback directly on the device, reducing the dependence on cloud infrastructure.
