Sociotechnical-systems analysis of IoT-AI convergence in cosmetic health

Abstract

The convergence of Internet of Things (IoT) devices and artificial intelligence (AI) in cosmetic health offers significant potential for preventive healthcare and personalized beauty-health integration. Despite market growth, implementation of IoT-AI technologies remains fragmented due to misalignment between technical capabilities and social systems. This perspective article uses sociotechnical-system analysis to examine implementation challenges in digital beauty-health initiatives. The analysis revealed that devices prioritized technical accuracy over integration with user routines, applications achieved consumer adoption while creating workflow challenges for healthcare systems, and algorithms exhibited performance disparities across populations. Studies on sociotechnical systems in healthcare demonstrate that successful implementation requires joint optimization across technical infrastructure, social systems, organizational contexts, and environmental factors. We propose establishing relevant sociotechnical standards, validating integration through diverse trials, and achieving healthcare alignment to this end. The priority areas include UV monitoring, skin barrier assessment, and AI-driven personalization. Without coordinated action addressing accuracy, workflow integration, and algorithmic fairness, cosmetic IoT-AI risks amplifying existing disparities rather than democratizing personalized cosmetic health.

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