Using AI at work: judgment calls

Intermediate · 7 min · Write a personal usage plan covering pasting, verification and disclosure at work.

  • judgment
  • privacy
  • verification

Using AI at work well comes down to a plan you write before you start: what you paste, what never, what you verify, what you disclose. Four lines, reused for every task. The plan is personal, but it answers to three masters: your employer’s rules, your readers’ trust, and your own name.

The four lines

  1. Paste — the classified-safe version: scrubbed data, public material, your own text. What not to paste set the buckets; the plan names them once so you stop re-deciding per task.
  2. Never — secrets, personal data, confidential figures, and untrusted content with a tool-enabled assistant (the prompt-injection boundary, drilled in the injection lesson).
  3. Verify — every number, name, quote and claim against its source before it appears in anything sent or published. Treat output as a draft with your name pending — the five-question check is the standing pass.
  4. Disclose — follow your workplace’s rules: some require labeling AI-assisted content, some restrict it for certain tasks entirely. When no policy exists, say so and set a local norm with your team — the absence of a rule is not a license; it is a gap you just found.

The meeting test

Before AI-assisted output goes into something consequential, three questions:

  • Can I explain where each fact came from?
  • Can I defend this text if someone questions it?
  • Would I be comfortable if the whole process were visible?

Three yeses — ship it. Any no — fix that step first. The test is quick, and it encodes everything above in one pass.

Judgment calls that recur

  • Tone about people: AI drafts, you decide — reviewing performance, saying no, delicate news. The draft can help; the choice is yours.
  • Policy gray zones: ask early, not after. One message to your manager beats one embarrassed meeting.
  • Your accountability: whatever the tool contributed, the signature is human. That is not a formality — it is why the other three lines exist.

Worked example

Task: a quarterly report section with customer examples. Paste: the outline, my own paragraphs, dashboard structure with fake sample values. Never: customer names and contract figures, raw exports, unreleased numbers. Verify: every figure against its dashboard; every example fictionalized or cleared; numbers re-typed, not copied. Disclose: change-log note that AI assisted the draft, plus a flag to the manager that no team policy exists yet.

AI-assisted output is heading into something consequential at work. What does the lesson’s meeting test ask?

Practice

Plan your usage before you start

You are about to use AI to draft a quarterly report section. It will include customer examples and figures from three internal dashboards. Your workplace has no explicit AI policy yet — and the section goes out under your name.

Write your usage plan before you start: what you will paste, what stays out, what you will verify, and what you will disclose. Then self-check it against the rubric and compare with a model answer.

Self-check — does your plan cover these?
Hint

Four lines: paste / never / verify / disclose.

What does 'under your name' change about the final step?

Transfer

  • New job, new tool: rewrite the four lines for that context in ten minutes.
  • Freelance or client work: version of the plan per client, agreed in writing.
  • Teams: share your plan as a starting point — local norms beat silent variation.

Key takeaways

  • Four lines before you start: what you paste, what never, what you verify, what you disclose.
  • Verify every figure, name and claim against its source — the signature stays human.
  • No workplace policy is not a license: ask early and set a local norm with your team.

Next

Next: Does ChatGPT train on your data? — the policy layer under these habits: what the controls actually control, dated and sourced.

Finished this lesson?