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An applicant tracking system (ATS) is software employers use to manage job openings and applications—from publishing a vacancy and collecting resumes to coordinating interviews and recording hiring decisions. It may parse resumes or help recruiters search and prioritize candidates, but there is no single ATS algorithm or universal “ATS score,” and not every system automatically rejects resumes.
For applicants, the practical goal is a truthful, relevant resume that is easy for software and people to read. For employers, an ATS is a workflow and recordkeeping tool whose screening rules, integrations, and optional AI features need careful configuration and oversight.
What is an applicant tracking system?
ATS stands for applicant tracking system. “Tracking” means managing candidates and applications through a recruiting process, not simply scanning resumes. Employers use ATS platforms to keep job, candidate, communication, interview, and decision information in one place.
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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →An ATS may be part of a broader human-resources information system (HRIS), a specialist recruiting platform, an agency-focused system, or custom application infrastructure. Common vendors include Greenhouse, Ashby, Lever, Workable, SmartRecruiters, Workday Recruiting, iCIMS, SAP SuccessFactors, Oracle Recruiting, BambooHR, Jobvite, and Recruitee. Their features and configurations differ; a vendor name alone does not tell you how a particular employer screens candidates.
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An ATS is not necessarily AI, a ranking engine, or an automated decision-maker. A platform can store applications and support human review without ranking anyone. Optional modules may add resume parsing, search, matching, assessments, chatbots, interview summaries, fraud detection, or identity verification. The distinction matters: the ATS is the broader system, while each screening or AI function has its own inputs, outputs, risks, and settings.
What does an ATS do?
A typical system can support some or all of these tasks:
- Manage requisitions: Create and approve roles, define hiring teams and stages, and record role requirements.
- Publish jobs: Post openings to a company career site or job boards and track where applications came from.
- Collect applications: Receive resumes, cover letters, links, work samples, and answers to application questions. An employer can also use an external career site connected to its ATS; SmartRecruiters, for example, documents an application API for that kind of setup (SmartRecruiters application API).
- Parse resumes: Extract information such as contact details, employers, titles, dates, education, and skills into searchable fields.
- Track candidates: Store applications, identify possible duplicate profiles, and move people between stages such as application review, interview, offer, rejection, or withdrawal.
- Search and filter: Find candidates by terms, experience, answers, qualifications, or other configured criteria. Some platforms also offer matching or recommendations.
- Coordinate interviews: Schedule meetings, share structured questions or interview kits, and collect scorecards and feedback.
- Communicate and automate: Send acknowledgments, reminders, interview instructions, and other messages, sometimes when a candidate changes stage.
- Maintain talent pools: Search previous applicants and organize candidates for possible future roles.
- Report and integrate: Track pipeline activity and connect recruiting with tools such as an HRIS, calendars, job boards, assessments, background checks, and payroll.
These capabilities can improve visibility and reduce repetitive coordination. They do not guarantee better hiring. An ATS can make a well-designed process more consistent, but it can also apply a poorly defined screening rule at scale.
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How an application moves through an ATS
A common workflow looks like this, although employers can change its order and automation:
- The employer creates a job requisition and gets any required approvals.
- The role is published on a career site, job board, or both.
- A candidate submits an application and answers any required questions.
- The ATS stores the application and uploaded documents.
- A parser may extract resume details into profile fields.
- Eligibility questions or other configured rules may affect the application’s status or visibility.
- Recruiters search, filter, sort, or review applications; some systems offer matching or ranking assistance.
- Selected applicants move through recruiter screens, interviews, and other stages.
- Interviewers submit feedback, and the hiring team makes a decision.
- The system records an outcome and may trigger communications, reporting, or onboarding steps.
The exact workflow depends on the employer, product, configuration, role, location, and subscription. A public application page cannot show you every rule or feature used behind it.
How resume parsing works—and why it is not the same as ranking
Resume processing can involve several distinct steps:
- Text extraction: Reading text from a DOCX, PDF, or other file.
- Field extraction: Identifying details such as a person’s name, job titles, employers, dates, education, and skills.
- Normalization: Organizing or interpreting fields so that related information can be searched consistently.
- Search indexing: Making extracted information available to recruiters’ searches.
- Matching or ranking: Comparing a candidate’s information with criteria for a particular role, if the employer uses such a feature.
A resume can look clear to a person but still be parsed incorrectly. Text embedded in an image, scanned pages without selectable text, complex tables, multiple columns, headers or footers containing essential details, decorative symbols, and unusual section labels can all make extraction less predictable. That does not mean every table or two-column resume will fail; parser behavior varies. Complexity simply creates avoidable uncertainty.
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Parsing also does not itself decide whether someone should be hired. An error in the parsed fields can make relevant experience harder to find, so many ATS interfaces retain the original resume alongside extracted data. What a recruiter can see depends on the product and the employer’s permissions and workflow.
Does an ATS automatically reject resumes?
Sometimes an application can be screened out automatically, but there is no universal rule that ATS software rejects every resume without certain keywords. An employer might configure a required question as a knockout, use eligibility rules, filter search results, prioritize candidates with a matching feature, or have a recruiter review every application. A rejection can also result from a recruiter’s action, a workflow, or a later hiring decision.
Knockout questions commonly ask about a role’s actual requirements, such as required work authorization, a license, a shift, location, travel, or a minimum qualification. Depending on the employer’s setup, a particular answer may remove an application from further consideration. Candidates should answer accurately rather than trying to guess or manipulate the intended response.
Some newer systems add AI-assisted matching or review. Greenhouse describes its Talent Matching feature as assistive rather than an automated hiring decision and documents a manual-review route when a resume cannot be parsed or a candidate opts out of AI-assisted review (Greenhouse Talent Matching FAQ). That describes this feature, not every ATS or every employer’s workflow.
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Is there an ATS score?
There is no universal ATS score shared by employers. Individual products may show a match score, relevance ranking, tag, recommendation, eligibility flag, or recruiter-entered rating. Those outputs depend on the platform and its configuration. A score from a public resume-checking tool cannot be assumed to match a particular employer’s private system, criteria, or settings.
How to make a resume easier to read and parse
“ATS-readable” is a useful shorthand for a resume that is clear to both software and people—not a format guaranteed to pass an algorithm. Use this practical checklist:
- Choose a conventional, relatively simple layout, preferably a clear single-column design.
- Use familiar section headings such as Experience, Education, Skills, and Certifications.
- Make sure text is selectable, rather than saved as a picture. For a PDF, select and copy a few lines to check that the text comes out in a sensible order.
- Keep employer names, job titles, and dates distinct and consistent. Avoid unexplained date formats or details placed only in a header, footer, sidebar, chart, or graphic.
- Use ordinary bullets and readable fonts; do not depend on icons or decorative symbols to convey essential information.
- Submit the file type requested by the employer. A text-based PDF is often reasonable if accepted, but PDF is not universally best; use DOCX when the application specifies it.
- Review any fields the application fills from your resume. Correct mistakes rather than assuming the parser got everything right.
- Keep a copy of the exact resume and answers you submitted.
Use job-description terminology honestly
Relevant language can help recruiters search and makes your experience easier to understand. Identify required qualifications, core responsibilities, tools, certifications, and domain terms in the posting. When a term accurately describes your experience, use it naturally and show it in context—for example, in a bullet explaining how you used a tool or skill.
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A cover letter is similarly employer-dependent: some postings do not request one, some systems store it as an attachment, and others ask targeted short-answer questions instead. Follow the application’s instructions rather than submitting a generic letter to satisfy an imagined ATS rule.
What ATS features may use AI?
Depending on the product and settings, AI-related features may help draft job descriptions, search or match candidates, summarize applications or interviews, transcribe interviews, or detect suspicious activity. These functions should not be treated as interchangeable:
- AI-written-text detection attempts to identify text produced with generative AI.
- Spam or duplicate detection looks for repeated or suspicious application patterns.
- Identity verification checks a person’s identity through a separate process or provider.
- Deepfake or fraud detection targets particular forms of impersonation or misleading material.
- Candidate matching or summaries help organize or interpret application information.
A vendor’s fraud-detection or identity feature does not prove that all ATS products can reliably identify AI-written resumes. Greenhouse’s Real Talent materials describe fraud and spam detection, AI-assisted matching, and identity verification as product features (Greenhouse Real Talent overview). Employers should assess each function separately, including its error rate, scope, and effect on candidates.
AI output is not automatically objective. A matching result reflects the job criteria, data, model, configuration, and human use of the result. A summary can omit a qualification; a ranking can favor conventional career paths; and a fraud flag can misclassify legitimate behavior. Employers should know whether a feature filters, ranks, recommends, summarizes, or makes a decision—and preserve appropriate human review.
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Applications can contain contact details, employment and education history, demographic information, and sometimes sensitive personal data. Information may be handled by the ATS provider and integrated third parties. Candidates should read the employer’s privacy notice where available. Employers should review access controls, retention and deletion, data exports, subprocessors, security, model-training terms, and any data sent to external AI providers. Vendor privacy statements are representations to evaluate, not a substitute for reviewing the contract and actual data flows. For example, Ashby describes its AI data practices and third-party model controls on its AI information page; customers still need to assess those claims for their own use.
Employment rules depend on where and how a tool is used. The EEOC has stated that federal civil-rights laws apply when employers use software, algorithms, or AI to make or inform selection decisions. It has also cautioned that meeting the four-fifths rule alone does not guarantee a selection procedure is free of disparate impact (EEOC annual performance report).
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In New York City, Local Law 144 applies to certain automated employment decision tools. The city’s FAQ describes bias-audit and notice requirements for covered employers and employment agencies, subject to the law’s definitions and details (NYC DCWP AEDT FAQ). Other jurisdictions and sectors may have different requirements. A vendor’s statement that a product is “compliant” does not by itself settle an employer’s obligations.
A bias audit evaluates a defined tool and use under a particular method and set of data; it is not proof that the system is fair in every job, configuration, or later version. Sample size, proxy variables, accessibility barriers, human decisions, and changed criteria can all affect what an audit says. NIST’s AI Risk Management Framework offers a voluntary structure for managing AI risks across a system’s lifecycle, but it is not a substitute for legal compliance.
Accessibility matters at the application stage as well as in assessment tools. If a form, test, identity check, or other hiring step is inaccessible, candidates should use the employer’s accommodation or recruiting contact. Employers should provide a workable accommodation path and test the candidate journey with assistive technology and mobile devices. This article is a technology and operations overview, not legal advice.
What applicants should do if something goes wrong
If the application will not accept a resume or seems to have imported it incorrectly, try a supported browser, check required fields and file-size limits, remove unusual characters from the filename, and use an unencrypted file in a requested format. If a complex document is causing problems, try a clean DOCX or text-based PDF, then check that the extracted text reads in order. Do not submit contradictory versions repeatedly unless the employer asks you to.
Save the application confirmation or ID if one is provided. If the form or assessment is inaccessible, contact the employer through its accommodation route or recruiting contact instead of silently abandoning the application or trying to work around a barrier without support.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How employers should evaluate and operate an ATS
An ATS should fit the organization’s hiring model: the volume of openings, number of recruiters and hiring managers, job types, countries, legal entities, and whether hiring is centralized or distributed. A very small employer may be able to manage occasional hiring with email and a spreadsheet; a growing or high-volume operation may need reliable permissions, history, coordination, and reporting. Alternatives include an HRIS-native recruiting module, a specialist ATS, a recruiting CRM, an agency system, or custom application infrastructure.
Before adopting a system, assess these areas:
- Workflow depth: Requisition approvals, configurable stages, scorecards, scheduling, offer management, referrals, internal mobility, agency workflows, and automation controls.
- Candidate experience: Mobile usability, accessibility, application length, parsing accuracy, save-and-return options, localization, privacy language, accommodation routing, and status communications.
- Search and matching: Whether search is keyword-based, semantic, AI-assisted, or combined; whether recruiters can understand why a candidate surfaced; whether ranking can be disabled; and whether unparsed applications receive manual review.
- Reporting: Request sample reports for stage conversion, time in stage, time to fill, sourcing, offer acceptance, candidate experience, and recruiter workload. Where legally appropriate, assess adverse impact and diversity reporting carefully.
- Integrations and portability: Test HRIS, payroll, job boards, calendars, email, assessments, background checks, single sign-on, APIs, webhooks, migration, exports, retention, and deletion.
- Security and privacy: Review encryption, role-based access, MFA, audit logs, data residency, disaster recovery, breach notification, data-processing terms, and subprocessors.
- AI governance: Request feature-level documentation, data-flow details, model or provider information, version-change notices, human oversight, disclosure and opt-out controls, accessibility testing, and relevant audit materials.
- Total cost: Include subscription and seat or active-job limits, implementation, migration, support, job advertising, messaging, video interviews, assessments, background checks, AI usage, API access, contract minimums, renewals, and termination or export fees.
For each AI feature, document its purpose, inputs and outputs, who can access it, whether it ranks or filters, who reviews the output, how candidates are notified, and how errors can be challenged or corrected. Test the complete application and recruiter journey with different file formats, names, career paths, employment gaps, certifications, devices, and accommodation requests. A manual-review route, override ability, and audit log can help ensure an automation error is visible rather than final.
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Common trade-offs
- ATS versus spreadsheets and email: An ATS offers central records, permissions, collaboration, auditability, and reporting, at the cost of software fees, setup, configuration, and training. Spreadsheets may suffice for very low-volume hiring but become harder to control as teams and applications grow.
- All-in-one HR suite versus specialist ATS: A suite can connect recruiting to employee records and onboarding with fewer vendors, but may offer less recruiting depth. A specialist ATS may provide richer hiring workflows and analytics but require more integrations and administration.
- Keyword search versus semantic matching: Keyword search is comparatively easy to understand but can miss synonyms and transferable experience. Semantic matching may surface related concepts, but can be harder to explain and needs careful monitoring for hidden assumptions or bias.
- Automation versus human review: Automation can reduce repetitive work, but it can also spread errors quickly. Employers should retain appropriate review, override controls, logs, and a route for correction or appeal.
Frequently asked questions
Can an ATS read a PDF?
Many systems can process PDFs, but file acceptance and parsing quality vary. A text-based PDF with selectable text is safer than a scanned image. Follow the employer’s requested file format.
Are tables or two-column resumes always bad?
No. Some parsers handle them, and others may read their contents in an unexpected order. A simple layout reduces uncertainty; keep essential information in ordinary text and verify the text order if you submit a PDF.
Can an ATS detect ChatGPT-written resumes?
Some platforms offer fraud, spam, or identity-related features, but those are not the same as reliably identifying AI-written prose. Do not assume every employer has such a tool or that a detector can determine authorship with certainty.
Can I apply twice?
That depends on the employer’s process and whether the second application is for the same or a different role. Avoid repeated submissions that create duplicate or conflicting records; contact recruiting if you need to correct an application.
How much does an ATS cost?
Pricing depends on vendor, hiring volume, seats, modules, implementation, and contract terms. Some providers publish pricing for particular plans while others quote individually. Compare the full cost of the required workflow and add-ons rather than relying on a headline price.
Is an ATS legally required?
There is no general requirement for every employer to use an ATS. Employers that do use recruiting software must still consider applicable employment, privacy, accessibility, and automated-decision rules for their location and use case.
What is the difference between an ATS and an HRIS?
An ATS manages recruiting and applications. An HRIS generally manages employee information and HR administration, though some HRIS products include recruiting modules and connect hiring records to onboarding.
What is an AEDT?
An automated employment decision tool is a legal or regulatory term used for certain tools that assist employment decisions. Its exact definition and obligations depend on the jurisdiction; it is not simply another name for every ATS.
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