The Question
Here it is: "What specific hours of labor do I want AI to replace?"
Not "How can we transform our business?" Not "What's possible with AI?" Those are nice to think about. But they don't guide action.
The useful question forces clarity. It makes you specific. It separates genuine opportunity from shiny object syndrome.
Why Specificity Matters
I worked with a manufacturing company last year. Their owner wanted to "leverage AI to optimize operations." That's a 40-pound problem statement.
We narrowed it down: "Our demand planner spends 8 hours a week pulling data from three systems and building forecasts. Can AI do that?" Suddenly, it was a 2-pound problem with a clear answer: yes, and here's what it costs.
That's the difference between a good project and a failed one.
The other thing specificity does: it forces you to examine whether the work is actually suitable for automation. Not all repetitive work is. Some tasks that look rule-based actually require judgment calls. Some are so integrated into your workflow that removing them creates new problems.
The Litmus Test
Use this filter. Ask "Can I write down the exact steps for this task?" If yes, it's a candidate. If no, it probably isn't.
That's not a perfect test — some things that seem subjective can actually be automated with the right setup. But it gets you 80% of the way there.
At Dig Solutions, we started with our own workflows. "Our team manually audits client reports for errors, 6 hours per month." Clear problem. Clear metric. We built an agent. It works.
The Honest Answer
If you can't name specific hours of labor you want to replace, you're not ready to implement AI. That doesn't mean you should wait. It means you should have a conversation with someone who can help you get specific. That conversation is the difference between a project with clear ROI and a consulting engagement that drains your budget.