I often read "the performance of the system is satisfactory" or " when your model is satisfactory".

But what does it mean in the context of Machine Learning?

Are there any clear and/or generic criteria for Machine Learning model to be satisfactory for commercial use?

Is decision what model to choose or whether additional model adjustments or improvements are needed based on data scientist experience, customer satisfaction or benchmarking academic or market competition results?