You've clarified your stance from nobody to nobody in business. That's good, although, I think that is opinion based on your experiences. I suspect that business will care if researchers can make it easy to learn on premise on their small datasets while maintaining high accuracy. The ability to easily update and adapt under non-stationarity without having to retrain from scratch benefits all. The same is true of models that maintain uncertainty or that can explain decision outputs. Tracking uncertainty, robustness to changes, on-line updatability and explainability are all related in that they are examples of things that become easier under causal modeling.

A parallel discussion we are having is whether the gain in accuracy is always worth the gain in complexity and loss in speed. It's something to decide on a case by case basis. It's basic hygiene to reach for the simplest model first.