The Pre-Award Risk Assessment, Translated

Before a grant was ever awarded, someone did a pre-award risk assessment: can this organization actually handle this money? It looked at financial stability, past performance, and systems. High risk didn't always mean no — it meant more safeguards, more monitoring, more conditions.

Adopting an AI system deserves the same assessment, before you commit. Translated:

1. Can we handle this? Do we have someone who understands the tool well enough to supervise it — not just use it?
2. What's our track record? Have we managed similar technology responsibly, or is this our first time with real automation?
3. What breaks if we're wrong? Who gets hurt, and how badly, if the system fails or misbehaves?
4. What safeguards come with "yes"? More human review? A pilot period? A kill switch?

In grants, skipping this step meant money went to organizations that couldn't manage it. In AI, skipping it means powerful tools land in teams that can't supervise them.

Assess before you award yourself the tool. Conditions and safeguards aren't pessimism — they're how high-risk ideas succeed safely.

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