West African Physicians Support AI Use Despite Autonomy and Reliability Concerns

A multi-country mixed-methods study has found that 94.1 percent of surveyed physicians affiliated with the West African College of Physicians express willingness to adopt artificial intelligence in healthcare if the tools are proven effective, despite pervasive underlying skepticism regarding reliability and professional independence. The research evaluated medical practitioners’ perspectives, determinants of adoption willingness, and integration frameworks across West Africa, a region confronting distinct contextual challenges such as infrastructure deficits and healthcare workforce shortages.

The investigation addressed a documented lack of empirical evidence regarding how clinicians in West Africa view clinical artificial intelligence, which has been proposed to enhance diagnostic accuracy, reduce medical errors, and improve operational efficiency in resource-constrained environments. To analyze clinician perspectives, researchers conducted a cross-sectional survey of 136 physicians affiliated with the West African College of Physicians alongside 72 qualitative key informant interviews, primarily involving Nigerian healthcare professionals.

Survey results revealed a pronounced divergence between clinicians’ acknowledgment of technical potential and their immediate professional reservations. While 85.3 percent of surveyed physicians agreed that artificial intelligence could enhance diagnostic accuracy and 83.1 percent believed it could decrease medical errors, 77.9 percent perceived artificial intelligence as a threat to clinical autonomy. Furthermore, 67.6 percent of respondents rated information provided by artificial intelligence systems as unreliable.

Direct exposure to these technologies was limited across the cohort, with only 33.1 percent of participants reporting prior experience using artificial intelligence tools. Statistical modeling indicated that trust in artificial intelligence was the strongest predictor of willingness to adopt (beta = 0.48, p < 0.001), while prior use was also a statistically significant factor (beta = 0.21, p = 0.03). Experience levels also influenced openness: younger clinicians with zero to ten years of medical experience demonstrated significantly higher willingness scores than senior clinicians with twenty or more years of practice, recording mean scores of 4.5 versus 4.1 (p < 0.05).

The study’s 72 key informant interviews highlighted the prospective role of artificial intelligence as a cognitive partner capable of providing diagnostic decision support, mitigating medical mistakes, and alleviating administrative workloads. However, qualitative respondents expressed substantial concern regarding the risks of clinical over-reliance, long-term erosion of practitioner skills, workflow disruption, and poorly defined accountability structures.

To establish clinical trust, participating clinicians identified three mandatory prerequisites: system transparency and explainability, rigorous local validation in comparable populations, and clear governance models equipped with enforceable accountability mechanisms. The authors concluded that safely integrating artificial intelligence into West African clinical practice will require frameworks prioritizing independent oversight, clinician-centered design, dedicated infrastructure investments, and the integration of artificial intelligence literacy into medical education.

Subject of Research: West African clinician perceptions of artificial intelligence in healthcare

Article Title: Clinician and key informant perceptions of artificial intelligence in healthcare and frameworks for ensuring safe integration into clinical practice of the West African college of physicians: a multi-country mixed-methods study

Article References: Uzochukwu, B. S. C., Cherima, Y. J., Enebeli, U. U., Okeke, C. C., Uzochukwu, A. C., Omoha, A., Hassan, B., Eronu, E. M., Yusuf, S. M., Uzochukwu, K. A., & Kalu, E. I. (2026). Clinician and key informant perceptions of artificial intelligence in healthcare and frameworks for ensuring safe integration into clinical practice of the West African college of physicians: a multi-country mixed-methods study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-16048-y

Image Credits: AI Generated

DOI: 10.1186/s12913-026-16048-y

Keywords: artificial intelligence, clinical practice, West African College of Physicians, diagnostic accuracy, medical error reduction, clinical autonomy, algorithmic trust, cross-sectional survey, key informant interviews, Nigeria, prior AI experience, local validation, explainability, governance mechanisms, infrastructure deficits, workforce shortages, skill erosion, medical training