AI-Powered Mental Health Chatbots in Africa: A Systematic Review and Culturally Adaptive Framework

Authors

Matshepo Lebese, University of Cape Town, South Africa

Pitso Tsibolane, University of Cape Town, South Africa

Published in

IST-Africa 2026 Conference Proceedings

ISSN: 2576-8581

ISBN: 978-1-905824-76-2

DOI: https://doi.org/tbc

Publisher

IST-Africa Institute and IIMC International Information Management Corporation Ltd

Published in Ireland

Abstract

Mental health challenges in Africa remain under-addressed due to inadequate infrastructure, stigma, and a chronic shortage of professionals. Artificial Intelligence (AI)-powered chatbots are emerging globally as low-cost, accessible tools that can offer psychological support. This paper presents a systematic review of 52 empirical studies published between 2017 and 2025, critically analysing their cultural, linguistic, and infrastructural relevance to African contexts. The findings demonstrate the potential of AI chatbots to improve accessibility, reduce symptoms of anxiety and depression, and expand psychosocial support, yet reveal limited African-specific adaptation. Most systems remain rooted in Western models and English-language designs, leaving critical gaps in local relevance, inclusivity, and sustainability. Based on the findings, the authors develop a Culturally Adaptive Digital Mental Health (CADMH) framework that integrates African cultural values, multilingual design, mobile-first optimisation, and ethical safeguards. The study highlights opportunities and barriers for integrating AI chatbots into African healthcare, offering guidance for research, practice, and policy.

Keywords

Artificial Intelligence, Chatbots, Digital Health, Mental Health, Africa, Cultural Adaptation

Cite this paper

M. Lebese and P. Tsibolane (2026) "AI-Powered Mental Health Chatbots in Africa: A Systematic Review and Culturally Adaptive Framework", IST-Africa 2026 Conference Proceedings, Miriam Cunningham and Paul Cunningham (Eds), IST-Africa Institute and IIMC, 2026, ISSN: 2576-8581, ISBN: 978-1-905824-76-2, https://doi.org/tbc

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