The report identifies significant risks for low- and middle-income countries, where health systems often lack the capacity to act on short-term forecasts. Vulnerable communities could miss out on life-saving early warnings if AI forecasting tools are not paired with localised health data and institutional support. For example, in Nigeria, preparedness actions often require weeks of notice, but existing forecast products only provide days or seasonal predictions. Without targeted investments in training, data infrastructure, and local ownership, the benefits of AI forecasting may remain inaccessible to those who need them most.