Beyond the Cloud: Edge AI for LMICs

As AI adoption accelerates, cloud infrastructure remains the dominant model for AI deployment. However, in many low- and middle-income countries (LMICs), connectivity constraints, bandwidth costs and limited local compute mean that cloud-based AI is not always the most practical or cost-effective option. This report examines the emerging role of edge AI as an alternative pathway for AI deployment in LMICs.

Drawing on forecasts of AI-capable smartphone adoption across 11 markets, comparative cost modelling of cloud and edge inference for multiple use cases, a mapping of more than 150 edge AI deployments and detailed case studies across sectors, the report analyses the technical, economic and ecosystem factors shaping edge AI adoption. It examines the implications for AI infrastructure, responsible AI and the enabling conditions required to scale edge AI, and provides recommendations for industry, policymakers and development partners to support its responsible adoption across LMICs.