The distinction is being made on end outputs -- is it more like a Powerpoint deck, or more like a production data pipeline -- not on techniques.

"Machine learning" includes plenty of activities that can be used to provide evidence for one-off human decision making (e.g., using a model to produce forecasts or to understand sensitivities).