The increasing use of Artificial Intelligence (AI), specifically machine learning, in weather and climate modeling is not a sudden revolution but rather an evolution of existing scientific techniques. While sensationalized examples like AI-generated fake city forecasts have emerged, meteorologists and climate scientists are not being replaced. Instead, machine learning, a long-studied method of using computers to identify patterns in data, is being integrated. This involves training models, such as neural networks, on vast datasets to discern complex relationships that might be difficult for humans to detect manually. The core principle remains identifying patterns, with machine learning enabling the analysis of intricate connections within the data.