By: Beth Schaefer, IPD Director
Just like candidates are using AI to apply for positions (AI in the Workplace: 5 Realities Every Job Seeker Needs to Know about AI), most Applicant Tracking Systems (ATS) now use AI-driven features to rank and filter resumes. If you don’t understand how your organization’s ATS works, your best candidates may slip through your recruitment net.
Here are the five most common ATS myths- and what you need to understand to avoid losing great candidates.
Myth 1: The ATS rejects most resumes automatically
Reality: Modern ATS platforms rarely “auto‑reject.” They rank, parse, and prioritize — but a human still reviews the top candidates.
Why it matters to hiring managers: Overreliance on automation can hide qualified applicants if your settings, filters, or job description language are too rigid.
Action: Review your job descriptions for overly rigid requirements, internal jargon, and missing skill synonyms. Small word changes can dramatically improve what the ATS surfaces.
Myth 2: Keywords alone determine who gets through
Reality: Keyword matching is only one signal. ATS systems also evaluate context, skills clusters, experience patterns, and sometimes behavioral indicators.
Why it matters to hiring managers: If your job postings are vague, overly broad, or stuffed with internal jargon, the ATS will surface the wrong people.
Action: Update your job postings to align with ATS evaluation methods to ensure qualified people make it to your inbox.
Click Here For a Printable PDF of Job Seeking Advice
Myth 3: The ATS reads resumes like a human
Reality: ATS parsing is still brittle. It struggles with:
- tables
- text boxes
- unusual formatting
- graphics
- multi‑column layouts
Why it matters to hiring managers: If your organization encourages “creative résumés,” you may be unintentionally disadvantaging candidates.
Action: Work with your HR Department to provide candidates with tips and strategies for resume formatting so they understand your process and can align with it.
Myth 4: AI in the ATS eliminates bias
Reality: AI can reduce bias when properly trained and audited — but it can also amplify it if fed historical hiring data.
Why it matters to hiring managers: Your ATS could be eliminating qualified candidates that you wish to include if the historical hiring data unintentionally creates bias.
Action: Work with your HR leaders to understand how they govern, monitor, and audit AI to reduce bias.
Myth 5: If the ATS didn’t surface a candidate, they weren’t qualified
Reality: ATS ranking depends on job description clarity, recruiter filters, and system configuration — not just candidate quality.
Why it matters to hiring managers: Many qualified candidates are filtered out due to mismatched titles, nontraditional career paths, or overly narrow search parameters.
Action: Refreshing your job search process to better align with how your ATS works will help more qualified candidates make it through the screening net. This includes widening filters, reviewing default settings, and checking for unintended exclusions.
AI can accelerate hiring, but it cannot replace the human judgment that makes hiring effective. A best practice for hiring managers has been to update a position description and refresh a position posting when the role becomes open for hiring, and AI and ATS tools do not change this. Keep this best practice, but make sure you follow the actions to balance the automation. The more hiring managers understand how their organization uses and governs ATS, and the more they collaborate with HR to provide candidates with resume-formatting guidance, the stronger their candidate pool will be, and stronger their hire will be.
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