You can build a tool, projects and a company on the premise of "automating/improving field <X> through AI". What you lack in maths can be made up by your intimate knowledge of the field.
You will gradually improve your knowledge of maths and the day will come when you'll realise you are finally able to apply this knowledge to a field you know much less about.
That's pretty much what happened to me and the team I assembled for my current startup. Not bad in IT, not bad in e-commerce, decent in maths (as much as a double degree in EE & computer science goes: not an expert but can read maths written by others).
We started with a reduced functional scope, teamed with hardcore mathematicians, expanded our maths knowledge, expanded the functional scope, started writing our own maths, etc...
Like every skillset, learning maths is gradual. Don't expect to write the next "AI breakthrough research paper" tomorrow, but read and try to understand the whys and wherefores of trending stuff (which you'll often hear about here on HN).
I'd suggest an approach where you use your (presumably good) software engineering skills to join an engineering gig in a data science team. Then, gradually pick up tools, slowly pivoting into fully fledged ML/AI. It is definitely possible as a career path.
The fast.ai course is very good.