Eligibility Checks Are Pre-Deployment Reviews

Before a single grant dollar went out the door, we ran eligibility checks. Was this person or project actually qualified? Did the rules allow it? It felt slow. It was the whole point — the check existed to stop bad spending before it started, not to apologize for it after.

AI needs the same gate, and most teams skip it.

A pre-deployment review asks the eligibility questions in plain English: Who will this system affect? Is this an appropriate job to hand to a machine at all? What could go wrong for the people on the receiving end? Who is accountable if it goes wrong?

Notice what this is not. It's not a technical review. It's not about model accuracy scores. It's the human question underneath: should we be doing this, to these people, in this way?

In grants work, skipping eligibility didn't just risk waste — it risked the entire program's funding. The stakes with AI are the same shape: one careless deployment can cost you customer trust, regulatory trouble, and months of cleanup.

Slow down at the gate. Check eligibility before you deploy. It's cheaper than every alternative.

I explain frameworks; I don't give legal counsel.