More and more candidates are using AI to polish their CVs, and more and more companies are using AI to sort and evaluate those same CVs. AI in recruitment is creating a paradox where it often works against itself. We'll show you where AI in recruitment genuinely helps, why a nicely written CV no longer means a quality candidate, and how to still keep track of candidates' real skills.
What are you interested in?
- How is AI changing the first steps of the hiring process?
- What do the numbers show, or how AI is changing recruitment on both sides
- AI vs AI: what does this mean for recruiters in practice?
- Why is the value of a traditional CV declining?
- Where does AI in recruitment actually help?
- How should you work with AI in recruitment?
- How to verify candidates' real skills
- Save time with AI that understands recruitment
- Summary
How is AI changing the first steps of the hiring process?
AI in recruitment today often enters the process on both sides at once. A candidate uses artificial intelligence to tailor their CV or cover letter precisely to a specific position, while the company uses AI recruitment tools to sort and score those same CVs. In the first steps of the hiring process, it can essentially become a contest between the candidate's AI and the recruiter's AI.
Why might general AI tools in recruitment not be enough?
There's nothing wrong with this in itself, the problem arises only when we start mistaking a better-written text for a better candidate. If a generic tool ranks applications purely by keyword match with the job ad, dozens of similarly polished CVs can distort the ranking rather than clarify it.
This is exactly why it matters what kind of AI tool a recruiter has at their disposal. The AI in the Datacruit ATS system is not a generic keyword-matching tool, but technology built specifically for recruitment that understands the context of the position, the experience, and the connections between them. This helps distinguish truly relevant candidates, not just those who have the "right" words in their CV.
What do the numbers show, or how AI is changing recruitment on both sides
To make clear this isn't just a theoretical phenomenon, let's look at some concrete numbers. The scale of AI use in recruitment is confirmed by data from recent surveys, both on the candidate side and the company side.
According to a survey by Gartner:
- 39% of candidates have already used AI during the hiring process,
- of whom 54% used it to help with their CV text and 50% with their cover letter,
- yet only 26% of candidates believe AI will evaluate their application fairly.
A similar pressure is confirmed by data from the recruitment platform Ashby, based on more than 100 million applications, according to which the number of applications per successful hire has roughly tripled since 2021.
TIP: If you're interested in more current data on AI in recruitment, also read How AI Is Transforming Recruitment: Key Data and Trends.
AI vs AI: what does this mean for recruiters in practice?
The rise in the number of applications is directly linked to how easily candidates today can adjust their CVs. Thanks to AI, it takes only a moment to tailor a CV to a specific role, so it pays off for candidates to respond to many more varied job offers than before. Recruiters, in turn, reach for AI in HR for the same reason, just in reverse, in order to process a significantly larger volume of data and keep an overview of recruitment.
In practice, this means two things at once. Recruiters can no longer afford to ignore that a large share of the CVs and cover letters they receive have been edited using AI, and at the same time they need to be aware that candidates are watching how transparently and fairly companies use AI in selection. Companies that get this balance right gain an advantage not only in recruitment efficiency, but above all in their ability to correctly assess who is truly a quality candidate.
Why is the value of a traditional CV declining?
The value of a traditional CV may be declining because AI today can produce a grammatically flawless, well-structured, keyword-rich CV in seconds, without it reflecting the candidate's actual abilities. The easier it becomes to create a perfect-looking CV, the less this document distinguishes a quality candidate from someone who simply knows how to use an AI tool well. Recruiters therefore need to rely on other signals besides the form of the text.
In practice, this means that two candidates with completely different levels of experience can end up with an almost identical, AI-polished CV, full of the same keywords and similarly "professionally" written sentences. A recruiter who decides based only on the form and structure of the text risks inviting to interview whoever prompted the AI better, rather than whoever actually has the most relevant experience for the role.
Where does AI in recruitment actually help?
AI in recruitment helps most where a recruiter needs to quickly process a large amount of information, not where a decision is being made about a specific person. It saves time on screening, matching, and working with the candidate database, but the final decision should always remain with the recruiter.
In practice, this most often covers the following areas of AI use in recruitment:
- CV screening and pre-selection – AI quickly goes through a large volume of applications and flags the ones that best match the position's criteria.
- Candidate matching – AI recruitment tools compare a candidate's experience and skills with the role's requirements and suggest the best matches.
- Summarizing interviews and notes – AI can condense long interview transcripts or hiring managers' notes into a concise overview.
- Semantic search in the candidate database – AI can find suitable candidates by meaning, not just by exact keyword match, which helps surface talent that would otherwise be overlooked.
TIP: The Czech ATS system Datacruit offers all of these AI features. This AI is also developed specifically for recruitment needs, so it understands the context of CVs, positions, and the specifics of the local market. See how AI in Datacruit can specifically save you time in your everyday work with candidates.
How should you work with AI in recruitment?
While artificial intelligence brings a lot of benefits to recruitment, for example handling huge amounts of data, it's still a human who decides on a candidate's real suitability. Motivation, way of thinking, cultural fit, or the ability to react to specific situations simply can't be reliably read from CV data alone. Recruiters and hiring managers should therefore see AI as a helper that saves them time, not as a tool to which decision-making can be handed over.
It's equally important how AI and candidate data are handled from a security and GDPR perspective. If you want to know what to watch out for when choosing and setting up AI tools in recruitment, read our article How to use AI safely in recruitment: a practical guide to working with candidate data.
How to verify candidates' real skills
Given the growing use of AI by candidates, it's necessary to place even greater emphasis on verifying a candidate's real experience and skills. The most effective practical tips include:
- Structured interviews with specific questions about experience – instead of general questions, ask about specific situations from the candidate's past experience and how they handled them.
- A practical test task – a short sample of work (e.g. a real task from daily operations) quickly reveals how a candidate actually thinks and works.
- Samples of previous work or a portfolio – for many roles (not just creative ones) you can ask for a specific output from previous work that can't easily be generated using AI.
- Reference calls with previous managers – direct verification of the candidate's experience and working style from people who actually worked with them.
- Combining multiple sources of information – no single tool or method gives a complete picture; only a combination of interview, task, and references reveals a candidate's real level.
Save time with AI that understands recruitment
Is your inbox full of CVs and do you have less and less time to properly go through them? AI in Datacruit speeds up screening, matching, and interview summarization, so you can focus on the candidates who genuinely interest you instead of admin work. The decision about who's the right fit always stays with you, AI just gives you a faster overview.
- Proprietary AI – not a generic solution, but technology developed directly by Datacruit.
- Built specifically for recruitment – understands CVs, positions, and the specifics of the local market.
- Secure – runs on its own infrastructure, customer data never leaves the Datacruit ATS environment.
Want to talk about how AI in recruitment can save you time? Schedule a no-obligation consultation with Zdeněk Bajer, who will be happy to answer your questions and show you the system in practice.
Summary
AI in recruitment today affects hiring on both sides. Candidates use AI to improve their CVs, while companies use AI to evaluate them, which lowers the informational value of the traditional CV.
Recruiters should therefore use AI where it genuinely saves time, namely in screening, matching, or summarization, while verifying candidates' real skills through interviews, practical tasks, or references. The final decision about a candidate must remain with a human.
