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How AI Is Revolutionising CV Shortlisting and How to Make Your CV AI-Ready

  • Writer: Lynsey Skinner
    Lynsey Skinner
  • Nov 25
  • 3 min read

In 2025, AI isn’t just a buzzword in tech, it’s reshaping hiring. From parsing resumes to scoring candidates, AI is increasingly the first gatekeeper between you and your next job. This article isn’t about whether you agree with using AI in this way or not (which is understandably a controversial topic), but instead about understanding how these systems work and how to optimise your CV for them. The right tweaks and changes could be the difference between landing an interview or getting lost in the algorithm.


How AI Screens CVs Today


1. CV Parsing: AI automatically extracts structured data from unstructured CVs, job titles, skills, education, certifications and feeds this into Applicant Tracking Systems (ATS), saving hirers hours of manual work.

2. Matching & Scoring: Modern AI uses semantic analysis to understand context, mapping your experience against job descriptions to generate a relevance score.

3. Automated Ranking & Shortlisting: Once scored, candidates are ranked automatically, letting hirers focus on the top matches. Some companies report up to a 90% reduction in initial screening time.

4. Bias Reduction (Potentially): Well-designed AI can help remove unconscious human bias by anonymising demographic info or focusing on skills. However, AI can inherit biases from historical hiring data.

5. Advanced AI Screening: Next-gen tools use large language models to reason about CVs, contextualise skills and even bring in industry benchmarks, going far beyond simple keyword matching.


Real-World Tools Making Waves


  • CiiVSOFT: Fast CV parsing and ranking, integrated with ATS.

  • Rippling: AI-powered CV parsing and candidate scoring.

  • Sapia.ai: Uses structured chat assessments to shortlist candidates.

  • HireVue: AI-powered video interviews, analysing verbal and non-verbal cues.


Making Your CV AI-Ready


If AI could be the first “person” reading your CV, how would you write for it? Here’s a concise set of practical, ATS-friendly tips:


Structure & Formatting

  • Use simple, traditional formatting - no tables, columns, icons or text boxes.

  • Stick to standard section headings: Profile, Skills, Experience, Education, Certifications.

  • Keep key details (name, email, phone) out of headers and footers, parsers often miss them.

  • Use consistent date formatting: Jan 2021 – Mar 2024.

  • Save as PDF or Word, but avoid heavily designed templates from tools like Canva.


Keywords & Relevance

  • Mirror wording from the job description (e.g. “TypeScript” not “TS”).

  • Repeat critical skills naturally within role descriptions, repetition boosts relevance.

  • Include synonyms where appropriate (e.g. “Product Manager / Product Owner”).

  • Tailor for each role; AI matches your CV to a specific job, not a general one.


Skills & Tools

  • Add a clear, parser-friendly Skills section (comma-separated list).

  • Include both hard and soft skills if relevant, but prioritise role-specific technical terms.

  • Add a Tools & Tech block near the top: e.g. “AWS, Docker, Kubernetes, Figma.”


Experience & Achievements

  • Use a simple structure: Job Title | Employer | Dates.

  • Start bullets with strong verbs (Delivered, Built, Improved).

  • Use measurable outcomes (% improvements, time savings, revenue impact).

  • Incorporate tools/tech directly into your bullet points for better matching.


Content Quality & Integrity

  • Keep it concise and avoid unnecessary personal details.

  • Be truthful, inconsistencies can be flagged by both AI and humans.

  • Write for humans as well: once you pass the algorithm, a real recruiter still reads it.

  • Use AI tools for clarity and spell-checking, but personalise your CV yourself.


Key Takeaways

  • AI is now standard in modern hiring, your CV may be screened by a machine before a human.

  • Hirers gain efficiency, but oversight is essential to prevent bias.

  • Candidates who structure, optimise and tailor their CVs for algorithms and humans perform better.

  • Ethical questions remain, but AI will continue shaping the hiring process.

  • In today’s hybrid hiring world, the best candidates aren’t just qualified, they’re AI-ready and human-friendly.

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