Abstract Surface solar radiation is a key component of the polar energy budget and solar energy resource availability, but biases in climate models limit confidence in future projections. We developed a U‐Net deep learning framework to correct surface solar radiation from 12 Coupled Model Intercomparison Project Phase 6 models using the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 as reference. The correction reduced mean biases by up to 91% and markedly reduced inter‐model spread. Corrected projections under four Shared Socioeconomic Pathways show persistent declines in surface solar radiation and surface solar radiation resources across both polar regions throughout the twenty‐first century, with larger decreases under higher emissions. The Arctic exhibits substantially stronger declines than Antarctica, especially over Greenland and Arctic coastal regions. These results suggest that continued warming will reduce polar surface solar radiation resources and that the Arctic radiation environment is particularly sensitive to greenhouse‐gas forcing.