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HOMERECORDAi At Work
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USING AI AT WORK

What should never go into a prompt, what to disclose, and what you stay answerable for when the output is…

◈ NEVER PASTE THIS

Assume anything you type may be stored or reviewed unless your organisation has a written agreement saying otherwise — and most consumer accounts are not covered by one. This is the only category on the page where the mistake cannot be edited afterwards.

  • Anything under a confidentiality obligation — client material, unreleased results, contracts, anything marked internal.
  • Other people's personal data — customer records, employee details, health or financial information, a CV somebody sent you in confidence.
  • Credentials of any kind — passwords, API keys, tokens, connection strings. These leak through logs, screenshots and shared histories.
  • Anything legally privileged or under embargo.
  • The test that covers everything: could you defend having emailed this to an outside company? If not, do not paste it.

Five rules that survive contact with a real job

RULE 01

Say what you used it for, specifically

Not "I used AI" and not silence. Name the part.

"I drafted the structure with an assistant and wrote the analysis myself. The figures are checked against the source."

That sentence is unremarkable in almost every workplace. Being discovered after implying otherwise is not a tool problem — it is a trust problem, and trust problems outlast the project.

RULE 02

You are still the author, legally and practically

No employer, client or regulator has accepted a tool as the responsible party. Professionals have been formally sanctioned for submitting AI-generated work containing citations that did not exist. Accountability did not move when the labour did — and that is the correct arrangement, because you are the one who can be asked why.

RULE 03

Verify anything checkable and consequential

Names, dates, figures, quotations, citations, legal and regulatory specifics. These systems produce confident, fluent text whether or not the claim underneath is true, and fluency carries no information about accuracy. The failures that damage careers are never obviously wrong — they are plausible, well-formatted and false.The same principle this site applies to itself: see the method.

RULE 04

Keep the judgement, hand over the labour

Decide before you start which part of the work is the part you are for — the position, the recommendation, the thing you would defend in a meeting. Hand over the drafting, the formatting, the first pass. If you cannot explain why the output is right, you have not done the work, you have forwarded it.

RULE 05

Know your organisation's actual policy, not the rumour of it

Many people are following a policy nobody wrote, or ignoring one that exists. Ask which tools are approved, whether there is an enterprise agreement covering data handling, and whether disclosure is expected. Ten minutes of asking removes most of the risk on this page.

If someone challenges you

Two situations, two different answers, and the wrong one in either is what causes damage.

If you did use it: say so immediately and specifically. "Yes — I used it to draft section two and to check the grammar. The analysis and the figures are mine and I have verified them." Concealment is what turns an ordinary working method into a disciplinary matter.

If you did not, and a detector says otherwise: ask what the accusation rests on. Detector tools misclassify a majority of writing by non-native English speakers in peer-reviewed testing, and cannot support a claim about an individual. Offer process evidence — drafts, version history, notes — and offer to discuss the substance of the work, which is far stronger proof of authorship than any score.Liang, Yuksekgonul, Mao, Wu & Zou, Patterns 4(7):100779, July 2023 — seven detectors, 91 TOEFL essays, average false-positive rate 61.2%. Detail on AI in schools.

◈ THE CAREER PART NOBODY SAYS OUT LOUD

Being able to operate these tools is already assumed and will not distinguish anyone for long. What stays scarce is the ability to look at a fluent, confident, professional-looking output and say precisely why it is wrong — which requires knowing the subject, not the tool. The people who struggle in this decade will not be the ones who used AI; they will be the ones who stopped being able to tell when it was wrong.Related: what the labour-market evidence actually shows

◈ WHERE THIS SITE STANDS

Using these tools at work is normal, and this site is built by someone who does it daily and says so on every relevant page. The failure mode is not use — it is use without disclosure and without checking. Those two habits cost almost nothing and prevent nearly every version of this going wrong.