AI Hiring Software Shouldn't Ask You to Just Trust the Score

You search for a candidate and your AI hiring software gives you a 91% match. That sounds useful. But what gave them 91%? A match score can help you work through candidates faster, but the number alone doesn't tell you very much. If you still need to open the CV and work out why the candidate appeared in your results, the AI has only done part of the job.

Recruiters need some context behind the score.

Why AI Match Scores Need More Context?

• Imagine two candidates receiving match scores of 89% and 91%. 
• You'll probably look at the 91% candidate first. But that small difference could come from experience, skills, education, or something else in their CV. Without knowing what influenced the result, it's difficult to judge how useful that difference actually is. 
• And ultimately, the recruiter is still the person making the recommendation. If a client asks why, you've shortlisted someone, "the AI gave them 91%" isn't much of an explanation. 
• Good AI hiring software needs to provide enough information for recruiters to make sense of the results they're seeing. 

Why Explainable AI Matters in Recruitment?

There's also a regulatory side to this. Under the EU AI Act, certain AI systems used for employment and recruitment are classified as high-risk. Human oversight and data governance are important parts of the requirements surrounding these systems.

But human oversight isn't particularly meaningful if the person reviewing an AI result has no idea what influenced it.

Recruiters don't need to understand every technical calculation happening in the background. They need information they can actually use when deciding whether a candidate is a good fit.

How EdgeTal Explains Candidate Matches

• EdgeTal doesn't currently provide a complete plain language "why this match" explanation for every candidate. That's still being developed. 
• What recruiters can see today is the match percentage alongside information showing which part of the candidate's profile matched their search. 
• EdgeTal also uses semantic search. Instead of depending entirely on exact keywords, it looks at the meaning behind a candidate's experience. 
• Someone might write that they "led sprints and automated workflows," for example, without using the exact terms "Agile" and "Python." Semantic search can recognize the relationship between that experience and a relevant search. 
• This gives the recruiter some context for why that candidate appeared rather than leaving them with a percentage on its own. 

What Makes a Good AI Recruiter? Meet EdgeTal

Every “AI recruiter” you have used or come across today must have promise you to make your hiring faster and easier. But the real question is, what actually makes an AI recruiter good? Some tools focus on faster searching. Others focus on better dashboards, more features, or automation. But recruiters don’t just need another tool with more buttons. They need something that fits into the way they already work, saves time, and solves the problems they actually face. So, what makes a good AI recr

Knivok Private Limited (DBA Knovik)Knivok Private Limited (DBA Knovik)

Can Recruiters Disagree With AI Results?

AI results aren't always going to get it right. EdgeTal allows recruiters to provide feedback on results rather than simply accepting whatever the AI returns. That matters because the recruiter remains the person making the judgement. If a result doesn't make sense, they should be able to say so.

The AI is there to help with the search and evaluation process, not make the final decision for them.

How EdgeTal Makes AI Performance Checkable

• The same idea applies beyond candidate matching. 
• EdgeTal has a Benchmarks feature that lets recruiters check the app's performance directly on their own device. 
• Rather than simply making a claim about how fast the AI is, EdgeTal gives users a way to test that performance themselves. 
• It's a small part of the app, but it follows the same principle: when something can be checked, users should be able to check it. 

How EdgeTal Protects Candidate Data with On-Device AI

Understanding an AI result matters, but so does knowing what happens to the candidate data being analyzed. EdgeTal runs its AI directly on the device. Candidate CVs don't need to be sent to a cloud server for AI processing, so the data stays on the recruiter's device.

Once the AI model has been downloaded, EdgeTal can also work offline. Recruiters can search and evaluate candidates without needing a constant internet connection. For recruiters, that means more control over the process, both in understanding the results they're seeing and knowing where their candidate data is being processed.

Final Thoughts

AI match scores can make candidate screening faster, but they shouldn't be something recruiters are expected to blindly trust. Recruiters still need context, especially when they're responsible for deciding which candidates move forward. That's what EdgeTal is working towards: AI that helps recruiters search and evaluate candidates while keeping the final judgement where it belongs, with the recruiter.

FAQs

What is an AI match score in recruitment?

An AI match score shows how closely a candidate matches a recruiter's search based on information such as their skills and experience.

Why is AI explainability important in recruitment?

AI explainability helps recruiters understand why a candidate was matched instead of relying only on a percentage or score.

How does EdgeTal help recruiters understand candidate matches?

EdgeTal shows a match percentage alongside information about which part of the candidate's profile matched the recruiter's search.

Does EdgeTal make hiring decisions for recruiters?

No. EdgeTal helps with candidate search and evaluation, while the recruiter remains responsible for the final hiring decision.