26 posts · page 2 of 3.
How to get CVs out of your email and into something you can actually screen, from a free filter rule to inbox-connected parsers, and how the options really differ.
One-click apply and AI mass-application tools have flooded hiring with poor-fit applications. The fix is to tighten intake at the source, then screen fairly.
Prompt, definite, and matched to the stage: the formula for a good rejection, plus ready-to-use templates and the lines that never belong in one.
Recruiters go slow because admin work crowds out communication, not because they don't care. Diagnose the bottleneck, remove it, and set a response standard.
AI CV screening is legal in the EU, but two laws apply: the GDPR and the EU AI Act. Both require a human, not the software, to make the decision. Here is what that means.
Identical CVs get different callbacks based on the name alone, and the gap has not moved in decades. Here is what the research shows and the fix that follows.
Four honest ways to track applicants without an applicant tracking system, what each one really costs, and how to pick by hiring volume rather than company size.
The four things a fast CV scan should check, why ten seconds should sort and never reject, and how to let a tool do it at scale without breaking the rules.
Rejection damage comes from silence and delay, not from the word no. Here is who gets what, how fast, and what the GDPR requires when you say it.
Most of your time to hire is waiting, not working. Here are the four queues that own the calendar, and which one to remove first.
The GDPR does not ban CV screening. It constrains your lawful basis, how much you collect, how long you keep it, and how much a machine may decide alone.
What blind screening hides, why it changes who makes the shortlist, and how to run it without losing the context you need to hire well.