AI tools like ChatGPT, Claude, Gemini, Copilot and Perplexity are changing how candidates approach the job search.

Increasingly, candidates are using AI to write and refine CVs, tailor applications, prepare for interviews, and articulate complex experience more clearly. And in many ways, that’s a positive shift.

Better applications.
Clearer communication.
Stronger first impressions.

But there’s a growing issue hiring managers and recruiters are starting to notice across the tech sector:
Candidates look strong on paper, but struggle to back it up in interviews.

Can (and should) you use AI for job applications?

Yes - and increasingly, it’s expected. AI can help you:

• structure your CV more effectively
• simplify complex technical experience
• tailor applications to specific roles or industries
• prepare for behavioural and technical interviews

But there’s a clear line between enhancing your communication and outsourcing your thinking.

Is using AI in your job search a risk?

It can be - particularly in technical and specialist roles like Cyber Security, Data & Analytics, AI & Machine Learning, Fintech, CX & Marketing Technology, Application Software, and tech sales roles.

The more complex your role, the easier it is for AI-generated content to sound convincing… but lack depth.

We’re seeing candidates:

• present highly polished technical experience they can’t fully explain
• use generic language that doesn’t reflect real-world application
• struggle to go deeper on architecture, decisions, or outcomes
• rely on templated answers that don’t hold up under scrutiny

In areas like Cyber Security, Data, AI, and Software, this becomes obvious quickly, because hiring managers will test for depth of knowledge, real-world application, problem-solving ability, and decision-making rationale.

If the story doesn’t hold up, credibility drops fast.

How to use AI in your job search (without undermining yourself)

AI should make you clearer - not more generic. Here’s how to use it properly.

1. Start with real experience (especially for technical roles)

Before using AI, document:

• projects you’ve worked on
• tools, platforms, or environments used
• specific challenges and how you solved them
• measurable outcomes

For example:

• What problem were you solving?
• What decisions did you make?
• What was the impact?

Then use AI to refine how you communicate it.

2. Be specific about your contribution

Avoid vague statements like:

“Worked on a cloud migration project”

Instead, be clear on:

• your role in the project
• technologies used (e.g. AWS, Azure, Snowflake, Salesforce, etc.)
• scale and complexity
• outcomes achieved

AI can help structure this - but it shouldn’t invent it.

3. Use AI to simplify, not oversell

One of AI’s biggest strengths is helping candidates simplify complex technical concepts, communicate clearly to non-technical stakeholders, and structure answers logically.

That’s valuable. But oversimplifying or exaggerating technical depth will get exposed quickly in interviews.

4. Prepare for both technical and behavioural interviews

AI is highly effective for:

• generating technical interview questions
• practicing behavioural responses
• structuring answers (e.g. STAR method)
• identifying gaps in your experience

But don’t rely on scripted answers. Hiring managers will typically probe deeper.

5. Practice explaining your experience clearly

This is where many candidates fall down. Make sure you can:

• explain complex work in simple terms
• talk through decisions you made
• describe trade-offs and challenges
• adapt your explanation for different audiences

If AI has written it, you still need to own it.

6. Keep your voice and thinking

AI can make applications sound polished - but also interchangeable.

Across all roles, hiring managers are assessing how you think, how you approach problems, and how you communicate. Not just what’s written on your CV.

What do recruiters in tech think about AI-generated CVs?

Most specialist recruiters (including Kaliba) expect candidates to use AI tools. What matters is:

• accuracy
• consistency
• depth of knowledge
• ability to explain your experience

A strong CV gets you into process. But your ability to validate and expand on it is what gets you hired.

And keep in mind...

AI is becoming part of the hiring process. Candidates who use it well will have an advantage. But the goal isn’t to create a more impressive version of yourself. It’s to present a clear, credible, and confident version of your real experience. Because ultimately, you’re not hired for how well you write a CV - you’re hired for how you think, solve problems, and deliver outcomes.