Turns Out Your Best Hire Might Not Be the Most Skilled One

There’s a stat making the rounds in HR circles right now that should make every hiring manager pause before they finalize a job posting stacked with technical requirements.

According to a survey from Express Employment Professionals and The Harris Poll, 86% of hiring decision-makers say a candidate’s personality can outweigh a skills gap, and and 91% say personality matters just as much as skills in the first place.

That’s not a small finding. That’s a lot of people with hiring authority telling us the checklist we’ve been trained to build resumes around might be the wrong checklist.

What the Survey Found

The traits hiring managers and job seekers agreed mattered most weren’t flashy. They were reliability, honesty, adaptability, flexibility, and self-motivation. None of those show up as a bullet point on a resume. You can’t put “adaptable” through an applicant tracking system and get a clean match score back. These are traits you feel in a person, not traits you scan for in a PDF.

Bob Funk Jr., CEO of Express Employment International, put it well in the survey results: every employee shapes the workplace beyond whatever’s written in their job description, and the right personality builds trust, smooths change, and raises the bar for how a team works together. In his words, personality is representative of the business culture itself, not just a nice bonus during hiring.

This tracks with what other research has been saying for a while now. A TestGorilla report found that 78% of employers had hired someone with strong technical skills who ultimately didn’t fit well because they lacked soft skills. Nearly four out of five employers have watched a technically qualified hire fall apart for reasons that had nothing to do with their technical qualifications.

So here’s the uncomfortable question sitting underneath all of this. If personality is this predictive of success on the job, why do so many hiring and management processes still treat it as a gut feeling instead of something you can actually measure and act on?

How Employers Are Actually Judging Personality Right Now

Here’s where it gets a little uncomfortable, and worth sitting with for a second. The same Express Employment Professionals survey, fielded by The Harris Poll among more than 1,000 U.S. hiring decision-makers, found that 87% of hiring managers believe they can tell from the very first conversation whether a candidate will succeed at their company, and 38% strongly agree with that. That’s a snap judgment, made before a single reference is checked, carrying an enormous amount of weight.

And it isn’t happening through anything you’d call rigorous. The most common way hiring managers say they actually gauge personality fit is through informal moments outside the prepared interview questions, cited by 61% of them. Think small talk before the meeting starts, the tone of a follow-up email, how a candidate treats the receptionist on the way in. Job seekers can feel this happening too. Ninety-four percent say a company has evaluated their personality during hiring, most often through:

• Informal interactions, 47%
• Situational questions, 46%
• Behavioral interview questions, 45%
• Reference checks, 43%
• Formal personality assessments, only 37%

Notice what’s at the bottom of that list. The one method actually designed to measure personality with any consistency is the one employers seem to reach for least. Everything above it is some flavor of gut instinct dressed up in a process. No wonder 61% of job seekers say they worry about how their personality is coming across in an interview. They can sense they’re being read, just not through anything they could prepare for or contest.

So if personality is this predictive of success on the job, why do so many hiring and management processes still treat it as a gut feeling instead of something you can actually measure and act on?

The Trouble With Measuring What Can’t Be Faked on a Resume

Personality is hard to fake convincingly over the length of an interview, which is part of why it’s such a strong signal. But it’s also genuinely hard to measure well. A hiring manager’s read on someone’s reliability or adaptability after a 45-minute video call is, honestly, a guess dressed up as an assessment. A good guess sometimes. Still a guess.

That gap between “we know personality matters” and “we have a reliable way to measure it” is exactly where a wave of workplace technology has tried to step in. Emotion-recognition software. Sentiment analysis layered onto meetings. Wearables that track stress signals. Tools that watch facial expressions on video calls and try to infer whether someone is engaged, frustrated, or checked out.

The pitch behind all of it sounds reasonable on paper. If personality and emotional state matter this much to performance, shouldn’t employers use every available tool to understand them?

California lawmakers just answered that question with a fairly firm no, at least for a specific and important category of tools.

California’s New Line in the Sand

Assembly Bill 1883 cleared the California legislature and is now sitting on the Governor’s desk, with a signing deadline of September 30. If Newsom signs it, California employers will be barred from using AI systems that recognize, infer, or predict a worker’s emotional state. The bill goes further and also bans the collection of “neural data,” defined as information generated by measuring signals from a worker’s central or peripheral nervous system.

A few practical details worth knowing:

• The law doesn’t ban workplace monitoring across the board. Employers can still use surveillance tools for things like safety.
• Violations carry a penalty of $500 per instance, which sounds modest until you multiply it across an entire workforce over time.
• There are carve-outs for work tied to certain aircraft, and to products connected to national security, military, space, or defense purposes.
• California isn’t acting in a vacuum here either. The EU’s AI Act already prohibits this kind of emotion-recognition tech in workplace settings, and it took effect back in 2024.

For context on why lawmakers are drawing this line now, an incident that got attention this year involved Burger King’s rollout of an AI assistant called “Patty,” built into employee headsets and designed to flag when workers used phrases associated with friendliness. Whatever the intent, that’s a fairly clean example of exactly the kind of AI-based emotional inference this new law is aimed at.

A University of Michigan associate professor’s analysis, cited in HR Dive’s coverage, noted that emotion AI’s capacity to actually measure emotions correctly remains controversial and contested. In plain terms, we don’t have great confidence these tools even work as advertised, and now there’s a legal reason for California employers to steer clear of them regardless.

Where This Leaves HR and L&D Leaders

If you’re running people programs at a mid-sized company, this puts you in a strange spot. The data says personality is one of the strongest predictors of who succeeds on your team. The law, correctly, says you can’t use AI to guess at someone’s feelings by watching their face or reading signals from their nervous system to get there.

That’s not actually a contradiction, once you separate two very different approaches that tend to get lumped together under the umbrella term “AI in HR.”

Approach one: AI trying to infer emotion from behavior it observes. This is what AB 1883 targets. Facial analysis, voice tone detection, biometric or neural signal collection. The tool watches you and makes a prediction about what’s happening inside your head. That prediction is often unreliable, it’s collected without much say from the person being watched, and now, in California, it’s headed toward being flatly illegal in a workplace context.

Approach two: People sharing information about themselves, voluntarily, through a validated instrument. This is a fundamentally different category. Nobody is inferring anything by monitoring your face during a meeting. A person completes a structured, research-backed psychometric assessment because they choose to, and the resulting profile reflects what they told you about themselves, not a guess an algorithm made by watching them.

This is precisely the distinction we get into in an earlier piece on this blog, Your AI Coach Should Know Your People, Not Just Your Org Chart. The point there was that generic AI advice fails managers because it has never met the person on the other end of the conversation. The fix isn’t watching people more closely. It’s giving managers validated, self-reported data about who someone actually is, then delivering coaching built on that data at the moment it’s needed.

That’s the model Ask Aura runs on, and it’s why this new wave of surveillance restrictions doesn’t touch how the platform works.

Why Ask Aura Isn’t Caught Up in This

Ask Aura’s coaching starts with a roughly 10-minute assessment covering three layers: Behaviors, Motivators, and Work Energizers, often shorthanded as BMW. An employee takes it once, voluntarily, and answers questions about themselves. Nothing is inferred from a webcam. Nothing is pulled from a wearable. No signal is captured from anyone’s nervous system.

From there, the coaching layer takes that declared, structured data and turns it into specific guidance delivered where people already work, inside Slack, Teams, and Outlook. A manager prepping for a tough conversation gets a strategy built on what an employee has told the system about their own motivators and stress responses, not a prediction about what their face looked like on a call last Tuesday.

That distinction matters more with every new piece of legislation like AB 1883 that gets signed. Tools built around watching and guessing are going to keep running into legal trouble as more states follow California’s and the EU’s lead. Tools built around structured, voluntary self-disclosure sit outside of that entirely, because there’s no inference happening and no neural data changing hands.

We’d add one honest caveat here. We’re not attorneys, and this article isn’t legal advice. What we can say with confidence is that the category of concern in AB 1883, emotion inference and neural data collection, describes a different kind of tool than a voluntary, self-reported psychometric assessment.

Everything an AI Coach Like Ask Aura Actually Does

Given all of this, it’s worth laying out what a coaching platform built this way can offer HR and L&D teams, without wandering anywhere near the surveillance concerns lawmakers are now targeting.

• Manager coaching in real time. Specific, personalized guidance for one-on-ones, feedback conversations, and performance discussions, based on how a direct report is actually wired, not a generic script.
• Onboarding that starts smart. New hires get understood from day one instead of managers spending months learning someone’s working style through trial and error.
• Team dynamics insight. Leaders can see how personality types on a team complement or clash with each other, useful for staffing projects and resolving friction before it turns into a resignation.
• Recruiting support. Personality and motivator data can inform hiring conversations, directly addressing the exact gap this whole survey points to, without replacing structured evaluation of skills.
• Retention signals. Understanding what energizes versus drains someone helps managers catch disengagement early, before it shows up as a resignation letter.
• Delivery inside daily tools. Coaching shows up in Slack, Teams, and Outlook, not buried in a separate platform nobody opens after week one.
• Room for existing investments. Prior assessments like Predictive Index, Hogan, DISC, or CliftonStrengths can be integrated to inform a person’s coaching profile instead of getting thrown out and replaced.
• People analytics for leadership. Aggregate, anonymized insight into team composition and dynamics for leaders making staffing and structure decisions.
• None of it requires watching anyone. No facial analysis, no biometric tracking, no neural data collection. The entire system runs on information people choose to share about themselves.

The takeaway for HR and L&D teams isn’t complicated, even if the regulatory environment around workplace AI is getting more complex by the month. Personality is one of the strongest predictors of who thrives at your company. The way to act on that isn’t watching people more closely and hoping an algorithm guesses correctly what’s going on inside their heads. It’s asking, giving people a validated way to tell you, and then building coaching around the answer.