Abstract Global medium‐range weather forecasts suffer occasional failures (‘busts’) linked to tropical cyclones (TCs). We investigate TC influences on extratropical predictability by comparing forecasts from a physics‐based model (ECMWF‐IFS) and an AI‐hybrid model (Google‐NGCM) initialized near TC genesis. Analyzing 108 out‐of‐sample Northern Hemisphere cases reveals similar extratropical error growth patterns and comparable performance between the models. This suggests that the Neural General Circulation Model (NGCM) is capable of predicting the bulk upscale effects of tropical convection without directly representing convective processes. Leveraging the NGCM’s computational efficiency, we compare forecasts initialized with and without TC genesis to isolate track‐dependent forecast impacts. For Week‐2 extratropical forecasts, TC impacts are highly time‐, metric‐, and track‐dependent. The analysis confirms that some poleward‐moving TCs degrade Week‐2 US and European forecasts and suggests significant impacts from westward‐moving TCs. The findings highlight the utility of the AI‐hybrid model in predictability research and complex tropical‐extratropical teleconnections that warrant future research.