Machine learning requires a large high-quality dataset, which a lot of companies simply don't have. Building one takes a lot of time and money. The gains don't outweigh the costs in many cases.

Another problem is that machine learning models are never a 100% correct and not easily interpretable, so they cannot be used for some critical processes. Good luck with explaining a customer why his account blocked due to a false positive made be the AI.

I think there is still a lot of potential for boring symbolic AI, in a lot of domains you can get results quickly, reliably and if the AI is wrong it's easy to debug.