Hey everyone,
I’m Director of Talent at a regional hospital network, and we’ve recently started using Talantly to help with screening. I can definitely see the upside! It saves a ton of time, especially with the volume of CVs we get for clinical and administrative roles.
But here’s where I get stuck: how much do you actually trust AI when it comes to evaluating CVs? I’ve heard plenty of horror stories about AI tools exaggerating, misinterpreting, or even fabricating details. So far, Talantly’s been solid, but I can’t help second-guessing.
For example, if the tool flags someone as a strong fit, do you still go line by line through the CV yourself? Or do you rely on the analysis and only spot-check? I worry about missing something critical, especially since in healthcare, the difference between “nice-to-have” and “non-negotiable” skills can be huge.
Curious how others are handling this balance. Do you double-check everything the AI shows, or do you let it take the lead and focus your time elsewhere?
Oh wow, this hits home! I'm still pretty new to using AI for screening, but I totally get that trust issue - especially in healthcare where stakes are so high! What I've been doing is kind of a hybrid approach: I let Talantly do the initial heavy lifting (because honestly, going through 50+ CVs manually was killing me), but then I always do a focused review of their flagged candidates. I've found their analysis is usually spot-on for the obvious stuff, but you're absolutely right about those "non-negotiable vs nice-to-have" distinctions - that's where I still lean on my own judgment. I actually caught a case where someone looked great on paper for an admin role, but when I dug deeper, they were missing a specific certification that was mandatory for our state regulations. The AI flagged them as qualified, but it couldn't know our local requirements. So I guess I'm in the "trust but verify" camp - let the tool save you time on the bulk screening, but always do that final human check on your top picks!
Yeah, I'm definitely in that same "trust but verify" camp - the cost per screening adds up if you're double-checking everything, but missing something critical is way worse. I've found it's pretty solid for basic qualifications but you still need that human eye for the nuanced stuff, especially industry-specific requirements.
I've found that building trust in AI screening is really about establishing clear validation protocols upfront. We started with a hybrid approach - letting the AI handle initial filtering for obvious qualifications while our team focused manual review on the top candidates and any edge cases. The key insight for us was tracking where the AI's assessments diverged from our hiring managers' evaluations, which helped us calibrate our trust levels over time. In healthcare especially, I'd recommend maintaining human oversight on anything related to certifications, compliance requirements, or patient safety credentials - that's just too critical to automate completely.