Depending on your perspective of "ML", the insurance industry already uses "ML" (i.e. very complicated decision trees) to process claims. Very few large insurance companies are non-automated in claims processing.

The places where the money hides, so to speak, include (1) handling complex cases [customers] (2) scaling a human's ability to process non-automatable settlements. (3) scaling internal support interactions with customers (4) introspection to claims data and support data. (5) graceful handling of prior authorizations.

These problems are not as attractive, but they are where insurance companies spend most of their money. It's still a tech problem, but it's not super fancy.

Existing carriers struggle to solve these problems, because they have historically grown by acquisition, and as such do not have the kinds of unified data systems required for the rapid development of applications that perform the required kinds of introspection. It's a space that's ripe for disrupting.