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AI

Responsible Use in High-Stakes Contexts

Low-stakes use has wide margin for error. Client proposals, leadership decks, external comms, regulatory and HR documents do not.

Lesson 4

You own what you publish.

Using AI output without meaningful review attributes the content to you, your accountability does not change because AI sped up the draft.

High-stakes use contexts

Client-facingLeadershipHR / legalYou own what you publish
Client, leadership, HR, you own what you publish; AI only speeds the draft.

Core principles

  1. Client-facing: read completely; verify claims; personalize, generic AI is detectable; confirm client-specific accuracy.
  2. Leadership: Tier 3 verification on all specific claims; be explicit about data sources; hedge what you have not verified.
  3. HR: have HR review personnel records; do not rely on AI for compliance language; anonymize in prompts; watch tone on sensitive documents.
  4. Transparency: when someone expects your independent judgment and AI did the heavy lifting, frame accurately, not a disclaimer on every email, but honest when it matters.

Check yourself

How does using AI output without meaningful review change your accountability for what you publish?

Do this in Copilot

Map one upcoming high-stakes task, where AI helps, and your review process before use.

Paste this into Copilot Chat and work through it before moving on.

Pre-send checklist

I am about to send this [client / leadership / HR] communication. List five verification steps I should complete before sending, specific to this context.
Open Copilot →
  • Pre-send checklist

Did you run this in Copilot? Mark complete when you have tried it.

Next lesson: Building Good AI Judgment Over Time →