AI Wearable Devices as a Case Study for Research on the Health Big Data Economy

Abstract

Against the backdrop of a growing global burden of chronic diseases and the deepening digital transformation, AI wearable devices-serving as crucial gateways for health data collection and intelligent analysis-are reshaping the operational logic and value-creation pathways of the health economy. This paper systematically explores the economic mechanisms and practical impacts of AI wearable devices throughout the processes of health big data collection, processing, and application. The research findings indicate that AI wearables have evolved from simple fitness-tracking tools into comprehensive “health managers” equipped with functions such as disease warning and remote monitoring. The vast, high-frequency, and multidimensional health data generated by these devices, when processed through algorithmic modeling and delivered as services, have significantly reduced individual healthcare expenditures, optimized the allocation of medical resources, and fostered emerging industries such as Insurtech and telemedicine. However, their development also faces tangible challenges, including risks of data privacy breaches, widening health inequality, a lack of data standardization, and lagging regulatory frameworks. By constructing a “technology-data-economy” transmission chain, this study reveals the role and constraints of AI wearable devices within the economic system, offering both theoretical and empirical insights into understanding the economic transformation driven by health big data.

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