I only see ML and data science as having real value when considered as a single component of a larger system, most of which will not consist of anything close to ML. Many real world environments are too entropic to see much accuracy from ML models except in very, very limited bands (facial recognition, for example).

As other commenters here have posted, without the integration of data science into both the business needs and the rest of the existing tech stack it will remain a fun school course activity.