How to identify resumes created by AI or ChatGPT

Artificial intelligence (AI) is now a standard part of the hiring landscape.

Many candidates use tools such as ChatGPT, Copilot and AI-powered resume builders to help refine their applications. They use them to improve structure and grammar, and some AI resume writers can even tailor content to a job description and highlight relevant skills.

This makes job applications with AI-generated resumes become increasingly common. For employers and hiring managers, this raises an important question: how can you tell when a resume has been heavily shaped by AI, and does it matter?

Rather than focusing solely on whether AI has been used, today’s employers should focus on whether a job application accurately reflects the candidate’s experience, achievements and suitability for the role.

Understanding how AI-assisted resumes are created can help hiring teams assess applications more effectively and make better hiring decisions.

AI-assisted resumes are now part of recruitment

Candidates have always looked for ways to strengthen their applications. Professional resume-writing services have been available for years. AI tools have simply made that support more accessible.

Today's AI platforms can analyse job descriptions, suggest improvements, identify relevant keywords and help candidates present their experience more clearly.

In many cases, that's not necessarily a problem. A well-written resume doesn't automatically mean a candidate lacks the skills or experience they're describing.

The challenge for hiring managers is understanding whether the quality of the application reflects the quality of the candidate.

As AI becomes more widely used, the focus is shifting from identifying AI-generated resumes to validating the experience behind them.

Understanding how AI creates resumes

AI models are trained on large volumes of text, including human-written resumes, job descriptions and professional profiles.

When a candidate uploads their experience and a target job description, the AI can identify common patterns and recommend language that aligns with the role.

This helps candidates save time during their job search by quickly creating tailored content for different positions.

Many AI-powered resume builders can:

• Analyse job descriptions
• Suggest relevant keywords
• Improve readability
• Refine formatting
• Tailor content to specific roles

This often results in polished, professional-looking resumes that are optimised for both recruiters and applicant tracking systems (ATS).  

While these tools can improve presentation, they cannot replace genuine experience, achievements or technical expertise. 

Signs a resume may have been heavily AI-generated

There is no single sign that confirms AI use. However, you may notice certain patterns that often appear in AI-assisted applications when reviewing multiple resumes.

1. Generic professional language

AI is designed to produce polished and professional content. As a result, resumes can sometimes sound similar regardless of the candidate's background.

Common examples include:

• “Results-driven professional”
• “Proven track record of success”
• “Strong communication and leadership skills”
• “Highly motivated individual”

These phrases are not necessarily a concern. The question is whether they are supported by evidence or simply included to sound impressive.

Strong candidates typically explain how they delivered results rather than simply stating that they did.

2. Broad achievements without supporting detail

One of the most common characteristics of an AI-assisted resume is a lack of specificity.

Examples of generic accomplishments used include:

• “Improved operational efficiency”
• “Increased business performance”
• “Delivered growth across key accounts”
• “Enhanced customer satisfaction”

These statements sound positive but provide little information about what was actually achieved.

Look for measurable outcomes, project details and clear examples of impact.

3. Content that sounds polished but lacks depth

AI can produce well-written content quickly. However, it can sometimes struggle to capture the context behind a candidate's achievements.

A resume may describe responsibilities clearly while offering limited insight into:

• How challenges were overcome
• Why decisions were made
• What role the candidate personally played
• What business outcomes were achieved

The strongest resumes connect responsibilities to outcomes and provide enough context to understand a job seeker’s contribution.

4. Overuse of keywords

Many AI tools are designed to optimise resumes for ATS in hopes that recruiters can filter candidates more easily through skill-based search.

As a result, some resumes contain repeated keywords pulled directly from job descriptions.

While this can improve searchability, it can also make a resume feel formulaic or overly tailored.

If every key term from the job posting appears multiple times, it may be worth exploring the candidate's knowledge of those areas during the interview process.

5. Unnatural wording

I writing has improved significantly in recent years, but awkward phrasing can still appear.  

Examples include:  

• Disconnected statements: Increased sales performance and highly skilled in stakeholder management.  
• Vague language: Experienced in various responsibilities across multiple business functions.  
• Overly formal wording: Utilised competencies to facilitate revenue enhancement outcomes.  

Most candidates will review AI-generated content before submitting it. However, wording that feels unnatural or inconsistent can still be a useful signal.

What employers should focus on instead

The bigger question is not whether AI was involved.

It's whether the candidate can demonstrate the experience and skills described in the application.

1. Focus on evidence over wording

Well-written resumes are useful, but evidence matters more.

Look for:

• Quantifiable results
• Business outcomes
• Project examples
• Career progression
• Specific contributions

Strong evidence is often a more reliable indicator of capability than polished language. Looking beyond a candidate's resume and taking a broader view of their contributions can also help employers make more informed hiring decisions.

2. Use interviews to validate experience

Interviews remain one of the best tools for assessing authenticity.

Ask candidates to explain:

• Their role in a project
• The decisions they made
• The challenges they faced
• The results they achieved

Candidates with genuine experience are usually able to discuss details confidently and consistently beyond their resume content.

3. Build a structured screening process

As resumes become more polished, structured hiring processes become even more important.

Combining resume reviews with interviews, skills assessments and stakeholder input can help employers develop a more complete view of a candidate's capabilities. A structured and consistent approach can also help organisations assess candidates more fairly throughout the hiring process and reduce the risk of costly hiring mistakes.

This approach reduces reliance on the resume alone and leads to more informed hiring decisions.

4. Use AI resume detectors carefully

AI detection tools can provide additional signals, but they should not be treated as definitive proof that AI has or hasn't been used.

The technology continues to evolve rapidly, and results can be inconsistent.

Professional human judgement, structured interviews and practical assessments remain more reliable ways to evaluate candidates.

AI is changing applications, not the fundamentals of hiring

As AI tools continue to evolve, employers will see more polished and more tailored applications.

That's likely to become the norm rather than the exception.

Organisations still need to assess whether candidates have the skills, experience and potential to succeed in a role. The most effective hiring decisions will continue to come from understanding the person behind the application, not just the quality of the resume itself.

AI adoption may be changing how resumes are written, but it hasn't changed what employers need to evaluate.

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