Unfortunately it's hard to sell your project's difficulty to someone who doesn't know as much about ML.
I'm not sure if you've done this, but IMO the best way to give non-technical people confidence in a long-running project is to break down your work into milestones each with a concrete deliverable, and then estimate how long you think each milestone will take. That way, the business manager can determine:
When will the project be done?
Is the project on-track to finish on time?
What will be delivered and at what dates?
Which is probably all that they care about. If the person who assigned you the project and your boss think your timeline is reasonable, your project is on time and you're delivering what you're supposed to, then no one can really complain.
I've always been of the opinion that writing timelines for ML projects is a lot harder than non-ML work, since often for ML you are trying to hit some "good enough" bar, but you don't know exactly what it will take to get there.
Unfortunately it's hard to sell your project's difficulty to someone who doesn't know as much about ML.
I'm not sure if you've done this, but IMO the best way to give non-technical people confidence in a long-running project is to break down your work into milestones each with a concrete deliverable, and then estimate how long you think each milestone will take. That way, the business manager can determine:
When will the project be done?
Is the project on-track to finish on time?
What will be delivered and at what dates?
Which is probably all that they care about. If the person who assigned you the project and your boss think your timeline is reasonable, your project is on time and you're delivering what you're supposed to, then no one can really complain.
I've always been of the opinion that writing timelines for ML projects is a lot harder than non-ML work, since often for ML you are trying to hit some "good enough" bar, but you don't know exactly what it will take to get there.