Artificial intelligence for surgical care in war-torn sudan: Feasibility, barriers, and ethical perspectives from a conflict zone

• Mixed-methods assessment of AI awareness, readiness, and perceived barriers among Sudanese surgeons working during active armed conflict. • Findings show moderate conceptual awareness of AI but very limited hands-on exposure, with training, infrastructure, and power/connectivity constraints predominating. • Surgeons most frequently identified potential AI applications in training, emergency triage, perioperative decision support, and resource allocation under severe constraints. • Qualitative and quantitative integration highlights the need for offline-capable, context-adapted AI tools and clear ethical governance in fragile surgical systems. Artificial intelligence (AI) offers transformative potential for clinical care, yet its deployment in conflict-affected, low-resource settings remains under-researched. This study evaluates AI awareness, barriers, and readiness among Sudanese surgeons amidst the nation's ongoing armed conflict. A sequential explanatory mixed-methods design was employed. An online survey, adapted from validated instruments, assessed AI familiarity, perceived barriers, ethical concerns, and readiness among Sudanese general surgery residents and specialists. From October 2024 to June 2025, 185 completed responses were obtained from a stratified random sample of 195 eligible participants. Follow-up semi-structured interviews were conducted with 20 purposively selected specialists. Quantitative data were analyzed using descriptive statistics, chi-square tests, and the Kruskal-Wallis test with Dunn’s post-hoc comparisons. Qualitative interviews were conducted until thematic saturation was achieved and analyzed thematically, with coding verified through inter-coder reliability. While AI awareness was moderate (68.7%), practical clinical exposure (9.4%) and advanced literacy (10.3%) were notably low. Surgeons identified AI’s primary utility in training (68.2%) and perioperative decision-making (65.4%). Significant barriers included infrastructure deficits (87.6%), training gaps (79.1%), and financial constraints (72.4%). Conflict-specific challenges were acute, with 92.5% reporting severe technology shortages and 78.3% citing unreliable power/internet. Qualitative themes highlighted AI’s potential for triage and resource allocation, though concerns regarding accountability and ethical governance persisted. This study provides inaugural evidence on AI feasibility within an African zone. Despite infrastructure collapse, Sudanese surgeons show strong interest in AI for triage and diagnostics. To move forward, development must prioritize offline-compatible, context-adapted tools and robust governance frameworks. These findings provide a blueprint for integrating AI to bolster surgical resilience during humanitarian crises.