Report
AI in recruiting: what HR teams should know before turning it on
Which AI features help, which ones carry risk, and the questions to ask vendors.
Where AI shows up in hiring
- Writing and improving job descriptions.
- Parsing resumes into structured profiles.
- Matching and ranking candidates.
- Scheduling and candidate chat.
- Interview transcription and summaries.
Low risk vs higher risk uses
Tools that save time on writing and scheduling carry relatively low risk. Tools that rank, score, or screen out candidates carry more, because they can influence who gets hired. Anti-discrimination law applies to the outcome either way, and some jurisdictions add specific rules.
The legal picture
New York City requires a bias audit and candidate notice for automated employment decision tools used in hiring and promotion. Other states have passed or proposed similar rules, and federal anti-discrimination law applies to AI-assisted decisions just as it does to human ones. Check current rules in every place you hire.
Questions to ask vendors
- What exactly does the model do, and what data does it use?
- Can we turn ranking and scoring off?
- Do you publish independent bias audit results?
- Is our candidate data used to train your models?
- How do we explain a decision to a candidate who asks?
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