Glossary
A plain-language definition from the Curriculo hiring glossary.
AI resume screening is the use of software to read resumes, compare them with a job's requirements, and rank candidates for human review.
Why it matters
A single open role can draw hundreds of applications. A recruiter who spends a few minutes on each resume loses days to the first pass alone. AI screening does that first pass in minutes, so people can spend their time on interviews and decisions.
The quality of the screen depends on what the model looks for. Older tools count keywords. Newer ones read context: what the person built, led, or changed, and how that maps to the role.
How it works
- The resume is parsed into fields such as roles, dates, skills, and education.
- The model compares those fields and the written experience with the job description.
- Each candidate gets a score, a rank, or a label, often with a short explanation.
- A recruiter reviews the shortlist and makes the call.
As one example, Curriculo ATS scores every candidate from 0 to 100 against your job, with a written AI summary of the fit.
A short example
A job asks for experience running paid acquisition. A keyword filter misses a candidate who wrote that she managed Google Ads spend and cut cost per lead. A context-aware model reads that line as paid acquisition and ranks her near the top.
Common mistakes
- Letting the tool auto-reject people with no human review of borderline cases.
- Writing a vague job description, then blaming the model for vague results.
- Ignoring local rules. New York City's Local Law 144 requires a bias audit and candidate notice for automated hiring tools.
- Never checking a sample of low-ranked resumes to catch errors.
Read the full guide to AI resume screening, see how AI screening works step by step, and learn about bias risks in AI hiring.