AI-IoT integration in Tanzania’s primary healthcare system: a narrative review

Abstract

PURPOSE: This narrative review explores the integration of artificial intelligence (AI) and Internet of Things (IoT) technologies in Tanzania's primary healthcare system. It aims to identify barriers to adoption, propose strategies for effective implementation and align these insights with Tanzania's digital health transformation goals. DESIGN/METHODOLOGY/APPROACH: A narrative review methodology was employed, synthesising evidence from 21 peer-reviewed studies and reports published between 2015 and 2024. The thematic analysis examined barriers, strategies and research gaps, focusing on technical, socio-cultural and organisational factors specific to Tanzania's healthcare context. FINDINGS: The review highlights several challenges, including infrastructural limitations, low digital literacy, socio-cultural resistance and the lack of robust policy frameworks. Strategies such as participatory system design, capacity building and investments in resilient digital infrastructure emerged as critical enablers. Insights also underscore the importance of addressing ethical considerations and customising solutions to Tanzania's unique socio-economic and cultural realities. ORIGINALITY/VALUE: This study uniquely focuses on the Tanzanian context, providing actionable recommendations to bridge the gap between AI-IoT technological potential and practical implementation in low-resource settings. Integrating global and local evidence offers a comprehensive framework to guide policymakers, practitioners and stakeholders in advancing digital health innovations personalised to the needs of primary healthcare systems.