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Careers & Technology

The ATS Problem: Why 75% of CVs Never Reach a Human Eye

Stephen Umurie
Head, Products and Technology · Scribble Green
|April 2026· 10 min read

Most job seekers assume their CV is being evaluated by a recruiter. In reality, it is usually evaluated by software first. Applicant Tracking Systems (ATS) act as the first filter — and most CVs do not pass.

This isn't because candidates are unqualified. It's because their CVs are not structured in a way that machines can interpret effectively. Research shows that up to 75% of applications are rejected by ATS before a human ever sees them.

What an ATS Actually Does

  • An ATS scans CVs for keywords, structure, and relevance. It ranks candidates based on how well their documents match the job description. The software parses your CV into a structured database, extracting key information like:
  • Contact information
  • Work experience and dates
  • Education and qualifications
  • Skills and certifications
  • Keyword matches against the job description

This means your CV is not being "read" in the traditional sense. It is being parsed, scored, and filtered before a human ever sees it. The system assigns a score based on how closely your CV aligns with the role requirements, and only candidates above a certain threshold move forward.

If your CV is not written for both humans and machines, it will likely reach neither.

Why Most CVs Fail

  • Understanding why CVs fail is the first step to fixing the problem. Here are the most common reasons candidates are filtered out:
  • Poor formatting that ATS cannot parse — complex layouts, text boxes, and images confuse the software
  • Missing or weak keyword alignment — not using the language and terminology from the job description
  • Use of graphics, tables, or columns — these break parsing algorithms and cause important information to be lost
  • Generic content — a one-size-fits-all approach that lacks role-specific relevance
  • Incorrect file format — .docx and .pdf are generally safest
  • Missing standard sections — not using conventional headings like "Experience" or "Education" makes parsing difficult

Even highly qualified candidates get filtered out at this stage simply because their CVs are not machine-readable. A study by TopResume found that 98% of Fortune 500 companies use ATS, making it essential to understand how these systems work.

How ATS Scoring Works

  • ATS systems typically score CVs based on several factors:
  • Keyword density — how frequently relevant terms appear (but beware of keyword stuffing)
  • Keyword proximity — how closely related keywords appear together in context
  • Section relevance — whether keywords appear in appropriate sections
  • Work history patterns — length of employment, career progression, and gaps
  • Education relevance — matching qualifications and institutions to requirements

The system also considers the overall structure and layout. A clean, well-organised CV with standard headings will generally score higher than a visually complex one, even if the content is the same.

Keywords Are Not Optional

ATS systems rely heavily on keywords pulled directly from the job description — skills, tools, qualifications, and responsibilities. The right way: use keywords naturally within meaningful descriptions of your experience — instead of just listing "Python", write "Developed data analysis pipelines using Python, Pandas, and NumPy to automate reporting processes." The wrong way is keyword stuffing — cramming as many keywords as possible without meaningful context, which can get your CV flagged as spam by more sophisticated systems.

Pro tip: Copy the job description text into a word cloud generator to identify the most frequently used terms. These are your priority keywords.

Structure Matters More Than Design

  • Many candidates prioritise visual appeal over functionality. While design matters for human readers, ATS systems prefer simplicity:
  • Use standard section headings — Experience, Education, Skills, Certifications
  • Avoid complex layouts — no tables, columns, text boxes, or graphics
  • Stick to clean, linear formatting — left-to-right, top-to-bottom reading order
  • Use standard fonts — Arial, Calibri, or Times New Roman are safest
  • Keep file names professional — "Firstname_Lastname_CV.docx" is better than "CV2_FINAL.docx"

In testing, a well-structured CV will outperform a visually impressive but unreadable one. The ideal CV is one that works for both machines and humans.

The Human Layer Still Exists

  • Passing the ATS is only the first step. Once your CV reaches a recruiter, it still needs to communicate value clearly and quickly. For the human layer, focus on:
  • Clear, compelling storytelling in your professional summary
  • Quantifiable achievements (e.g., "Increased sales by 30% in 6 months")
  • Relevant experience presented in reverse chronological order
  • A clean, readable layout with adequate white space
  • Error-free writing — typos and grammar mistakes undermine credibility

Common ATS Myths Debunked

  • Myth: "ATS can't read PDFs." Reality: Modern ATS can read PDFs, but they must be text-based, not scanned images.
  • Myth: "You need to include every keyword from the job description." Reality: Use keywords that genuinely apply to your experience.
  • Myth: "Longer CVs are better." Reality: Most ATS systems prefer conciseness. Two pages is typically the ideal length.
  • Myth: "Creative design helps you stand out." Reality: For ATS-filtered roles, simple and standard is more effective.

Final Thought

The hiring process has changed, but most CVs haven't. Understanding how ATS systems work is no longer optional — it is a basic requirement for navigating modern recruitment. Invest the time to optimise your CV for both machines and humans. It's one of the most high-impact actions you can take to improve your job search outcomes.

Stephen Umurie
Head, Products and Technology · Scribble Green

Technology leader focused on AI systems, automation, and digital hiring workflows. Leads the development of Scribble Green's CV optimisation tools and recruitment intelligence systems. With over a decade of experience in HR technology, Stephen has helped thousands of professionals improve their job search outcomes through smarter CV design and strategic application approaches.

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