AI in public health remains pre-emergent in one Congolese health zone, study finds

Artificial intelligence is often promoted as a way to strengthen health systems, but a new study from the Democratic Republic of Congo suggests that in at least one urban health zone, the technology has not yet moved beyond early discussion. Researchers examined the Ibanda Health Zone and found no institutionally implemented clinical AI system operating there, while some health professionals reported informal personal use of consumer generative AI tools.

The study, published in BMC Health Services Research, was led by Hermès Karemere and colleagues. It set out to examine AI-related practices and implementation readiness in one urban health zone in the DRC, and to place those local findings in context using pilot experiences from elsewhere in Africa.

Methodologically, the work combined two evidence streams. The researchers conducted a secondary thematic analysis of semi-structured interviews with 11 purposively selected health professionals in the Ibanda Health Zone. They then integrated these findings with a critical narrative review of 56 scientific and grey-literature documents from the DRC, Rwanda, Kenya, and South Africa. Both streams were coded against a common framework covering use cases, institutionalization, reported effects, and health-system prerequisites.

The central result was clear: no institutionally implemented clinical AI system was identified in Ibanda. Some professionals reported using consumer generative AI informally, but this was not part of any organized deployment. The authors also noted that Google Search, the DHIS2 health data platform, and routine laboratory automation formed part of the broader digital-readiness environment, although these were not classified as AI.

Despite the absence of deployed systems, participants saw potential in the technology. They perceived possible benefits for diagnosis, laboratory turnaround times, and data management. However, the same interviews surfaced major barriers, including shortfalls in training, poor connectivity, reliance on paper records, and gaps in regulation and governance.

The review of African pilot programs added a mixed picture. Individual pilot studies from the four countries reported promising results, but the authors caution that heterogeneous designs and settings precluded direct comparison or pooled conclusions. In other words, while isolated successes exist, the evidence base does not yet allow firm generalizations about what works across the continent.

Taking the two evidence streams together, the researchers concluded that Ibanda illustrates a pre-emergent stage of AI readiness rather than established AI implementation. They suggest that any future deployment should be gradual, locally validated, and preceded by investment in data systems, infrastructure, workforce capacity, and accountable governance.

The authors are explicit about the limits of their work. These are exploratory findings that are context-specific to one health zone and a selective review, and they should not be interpreted as evidence of AI effectiveness in the DRC. The study was published as open access research on 3 September 2026, and the version shared early is subject to further edits before the final Version of Record.

For health-system researchers and policymakers, the study offers a grounded snapshot of where AI stands in a fragile, low-resource setting: enthusiasm and perceived potential among local professionals, alongside substantial structural prerequisites that remain unmet before any clinical AI system could responsibly be introduced.

Subject of Research: Implementation readiness and barriers for artificial intelligence in public health in the Ibanda Health Zone, Democratic Republic of Congo

Article Title: Opportunities and barriers to implementing artificial intelligence for public health in the Democratic Republic of Congo: a case study of the Ibanda health zone and lessons from African pilot programs

Article References: Karemere, H., Baderha, C. B., Kani, A. K., Furaha, C., Bashige, J., Katumbi, F. A., & Karemere, J. (2026). Opportunities and barriers to implementing artificial intelligence for public health in the Democratic Republic of Congo: a case study of the Ibanda health zone and lessons from African pilot programs. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15492-0

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15492-0

Keywords: artificial intelligence, public health, Democratic Republic of Congo, health systems, Ibanda Health Zone, implementation readiness, digital health, DHIS2, African pilot programs, health workforce, governance, low-resource settings