CV generado con IA: cómo distinguir habilidad declarada de habilidad real
Un CV hecho con IA declara habilidades; no las demuestra. Aprende a separar lo declarado de lo evaluado y a decidir a quién entrevistar con evidencia comparable.
A CV generated with AI declares skills; it doesn’t demonstrate them. The way to distinguish declared skill from real skill isn’t to try to detect AI use in the text, but to evaluate the candidate for the role and compare everyone against the same criterion. What’s declared is written; what’s evaluated is observed. That observation is what gives you a reliable signal to decide who to interview.
Almost every CV that arrives today looks good. Clear structure, action verbs, quantified achievements. It makes sense: AI helps with the writing and the result is a polished text. The problem for whoever is selecting isn’t ethical, it’s practical: when every CV declares the same things, and just as neatly, the text stops being useful for telling people apart.
Declared isn’t the same as demonstrated
The key is to separate two things the CV blends together:
- Declared skill: what the candidate claims they can do. It’s a statement, and a statement can be polished, expanded, or presented in the best light, with or without AI.
- Evaluated skill: what’s observed when the person responds to a test designed for the role. It’s not what they say about themselves, but how they behave in a defined situation.
The distinction matters because the decision of who to interview should rest on the second, not the first.
Why “detecting AI in the CV” is the wrong path
Trying to guess which CV was written with AI is a weak, fragile clue: detection tools fail, generate false positives, and penalize candidates who only used legitimate writing assistance. On top of that, it doesn’t solve the underlying problem. Even if you knew for certain that a CV was written by hand, you still wouldn’t know what the person can do in the role.
The useful approach is a different one: stop asking the CV for a signal it can no longer give, and look for it where it actually is, in evaluated evidence.
How to separate the declared from the real, in practice
| Signal | What it tells you | How comparable it is |
|---|---|---|
| CV (declared) | How the career is narrated | Low: each account is different |
| Evaluation for the role | How they respond to defined situations | High: same yardstick for everyone |
| Interview with context | How they reason and communicate live | Medium-high, better if they arrive with prior evidence |
A concrete route:
- Define which competencies matter for the role before looking at candidates.
- Apply a short evaluation connected to your portal, the same for everyone.
- Compare results against a common criterion, not against loose impressions.
- Use the evidence to prepare the interview, not to skip it.
AI interprets, the person decides
On the recruiter’s side, Kokoro’s AI helps interpret and order the results according to the role, not to decide. It contributes signal and saves reading work; human judgment resolves who to interview and who to hire.
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A CV with AI is good at declaring and bad at demonstrating. The way out isn’t to chase AI use in the text, but to move the screen toward evaluated evidence: a comparable signal that separates real skill from declared skill. Explore how the product works, the science behind it, or the library of evaluations.