Local Social Structures as Enablers and Barriers for AI Enabled Medical Drone Delivery: Early Evidence from a Developing Economy

Medical Drone Delivery Systems (MDDS) such as Zipline in Rwanda have grown to become one of the most cutting-edge responses to the healthcare supply problems in low and middle income countries (LMICs). MDDS employ Artificial Intelligence (AI) for autonomous flight and route optimisation, but their sustainability under long-term use is rarely considered especially in relation to local social structures that favour or limit success. Drawing on Structuration Theory and taking a sociomaterial perspective, this multimethod qualitative and quantitative study examines how community trust, governance norms, and regulations shape MDDS sustainability. This study used semi-structured interviews and documentary analysis. Findings identify strong public government trust as a core societal enabler, and technical constraints (including 3 kgs payload limit and stringent airspace regulations) as barriers. This paper provides early empirical evidence regarding AI-based drone logistics and actionable insights for policymakers seeking to integrate MDDS into national healthcare systems.