Exploring the impact of generative AI tools on healthcare delivery in Tanzania

Abstract

PURPOSE: This study explores the impact of generative AI tools on healthcare delivery in Tanzania. It examines its potential to enhance efficiency, accessibility and decision-making in health informatics while addressing infrastructure, ethics and equity challenges in low-resource settings. DESIGN/METHODOLOGY/APPROACH: A mixed-methods approach was employed, combining quantitative surveys with 100 respondents and qualitative semi-structured interviews with 30 participants, including healthcare professionals and patients from urban and rural areas in Tanzania. Quantitative data were analysed using descriptive and inferential statistics, while qualitative data were examined using thematic analysis to identify recurring patterns and insights. FINDINGS: The study reveals significant disparities in digital literacy and AI adoption between urban and rural participants, with healthcare professionals showing higher acceptance of AI tools than patients. While ChatGPT was perceived as a useful tool for enhancing decision-making and healthcare delivery, concerns about infrastructure limitations, data privacy and algorithmic bias were prominent. Participants highlighted infrastructural barriers, such as unreliable Internet and electricity, as major challenges to AI adoption. ORIGINALITY/VALUE: This study is one of the first to examine the role of generative AI like ChatGPT in a low-resource healthcare system. It provides empirical insights into the opportunities and barriers to AI integration in Tanzania. It emphasizes the importance of localized, equitable and ethical AI implementations tailored to specific healthcare needs in underserved areas.

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