AI Hiring Compliance in 2026: A Practical Checklist for HR Teams

Using AI in hiring is legal nearly everywhere. Using it without disclosure, auditing, or a human review path is where teams get into trouble. This is the checklist, written for someone who has to open a role next week rather than write a policy paper.

What the rules ask for

New York City's Local Law 144 is the strictest regime in the United States: an automated employment decision tool needs an independent bias audit every year, the results published, and candidates told at least 10 business days before the tool is used. California, Illinois and Texas each add their own AI hiring rules — Illinois, for example, requires that candidates be told whenever AI is used in a hiring decision.

None of these rules bans AI screening. All of them make it something you must be able to explain.

The checklist

1. 01Write down which stage the AI touches. Sourcing, screening, interviewing, ranking, or deciding. The obligations attach to decisions, so be precise.
2. 02Disclose it to candidates before they enter the stage. One clear paragraph in the job post and the invitation email.
3. 03Keep a human on every reject and every advance. Named, and able to answer a candidate's question without contacting the vendor.
4. 04Agree the rubric before the role opens. Scoring criteria written first is the difference between assessment and rationalisation.
5. 05Require cited evidence for every rating. A score you cannot trace to an answer cannot be defended.
6. 06Monitor selection rates by group. Quarterly at minimum, and again after any model change.
7. 07Commission the bias audit if you are in scope. Independent, annual, published.
8. 08Contract for data. Confirm in writing whether candidate content trains vendor models, how long transcripts are retained, and how you export them.
9. 09Give candidates their assessment summary. Not required everywhere; it is the cheapest trust-building step available.
10. 10Keep the records. Job post, notice, rubric, transcripts, decisions, and who made them.

The common failure

Not malice — drift. A team adopts a tool for sourcing, then quietly starts using its ranking to reject, and nobody re-reads the notice or the audit scope. Re-check the first item on this list whenever the way you use the tool changes.

Related reading

• AI in HR, explained — where AI works and where it does not.
• How to choose reliable AI HR tools — governance questions to ask vendors.
• AI HR tools comparison table — which categories include bias monitoring.

This is not legal advice; confirm your obligations for your jurisdiction and role types. Octively runs disclosed, structured, evidence-cited, human-reviewed hiring by default — join the waitlist for early access.