International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 13, Issue 4 (April 2026), Pages: 72-85

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 Original Research Paper

Ethical frameworks and predictors of ethical artificial intelligence adoption in Kenya’s health sector

 Author(s): 

David Muchangi Mugo *

 Affiliation(s):

Department of Computing and Information Technology, University of Embu, Embu, Kenya

 Full text

    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-7070-7656

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2026.04.008

 Abstract

This study used a mixed-methods approach that combined a semi-structured questionnaire with a systematic literature review to examine the factors that influence ethical Artificial Intelligence (AI) adoption in Kenya’s health sector. The aim was to provide evidence to support both policy development and practical implementation. Data were collected from 150 healthcare providers working in healthcare institutions and digital health companies in Kenya and were analyzed using multiple linear regression. The main independent variables were data governance, ethical awareness, regulatory compliance, and organizational accountability. The results showed that all four variables significantly predicted ethical AI adoption. Data governance (β = 0.3157, p < .05) and ethical awareness (β = 0.2415, p < .05) were the strongest predictors, followed by organizational accountability (β = 0.1894, p < .05) and regulatory compliance (β = 0.1128, p < .05). Diagnostic tests confirmed the validity of the regression model (VIF < 3.0, Durbin–Watson = 2.12, p > .05). The findings highlight the importance of strengthening data governance practices, developing human capacity, improving organizational accountability, and ensuring compliance with existing regulatory frameworks to support faster and more ethical AI adoption in the healthcare sector. The paper concludes with policy recommendations that emphasize Afrocentric ethical perspectives inspired by African philosophies such as Ubuntu, capacity building for stakeholders in the healthcare ecosystem on ethical AI, stronger regulatory systems, and efforts to increase public trust in AI-based healthcare solutions.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Ethical awareness, Organizational accountability, Data governance, Afrocentric ethics, Regulatory compliance

 Article history

Received 17 October 2025, Received in revised form 5 March 2026, Accepted 2 April 2026

 Acknowledgment

The author sincerely thanks the healthcare professionals, ICT officers, data governance managers, and administrators from public hospitals, private healthcare facilities, and digital health startups across Kenya for generously contributing their time and valuable insights to this study. The author also acknowledges the support of the University of Embu, particularly the Department of Computing and Information Technology, for providing a conducive research environment. Appreciation is further extended to colleagues and peers whose constructive feedback and encouragement contributed to the final manuscript. 

 Compliance with ethical standards

 Ethical considerations:

This study involved human participants and was conducted in accordance with established ethical standards. All participants were informed about the purpose of the study, and participation was voluntary. Informed consent was obtained from all respondents before completing the questionnaire. The anonymity and confidentiality of participants were strictly maintained. No personally identifiable information was collected, and all data were used solely for academic research purposes. 

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

Mugo DM (2026). Ethical frameworks and predictors of ethical artificial intelligence adoption in Kenya’s health sector. International Journal of Advanced and Applied Sciences, 13(4): 72-85

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