Simple advice from an ML consultant: it starts with a use case.
Many of you are technical minds. That's great. The world needs technical minds. You're hacking away at a better future.
But. Technical minds often fail to relate the technical application of what the thing they can build actually will do - for the business, in business terms, to the non-technical people in the driver seat, that it often falls on deaf ears and ultimately never sees light.
Clients also tend to see applied data science as a 'nice to have', versus a source of competitive advantage (or soon, as a means of keeping up with the competition). The consultant's advice was very simple: it's all about the use case.
If you can, isolate the single most important use case. When you work through the implementation - what you might call the solution architecture, ensure it all stacks up to a demonstrable ROI.
What will it cost? What will it return? Then analyse and mitigate the risks involved.
You currently do X, we could do Y, it will deliver Z.
Make it concrete. Business is often that simple.