Here’s a hot take: The science of Emotional Intelligence (EQ) is dubious, confusing, and anything but settled. When it comes to talent identification, that can be a problem.
We tend to measure EQ in the same way we do IQ: Using a test with a series of questions. But emotion and cognitive ability are totally different, and as sciencealert.com points out, ‘It’s much more difficult to measure EI scores as often emotion-based questions do not have one correct answer.’ Add to this the fact that many EQ tests rely on self-reported data, and you can see how IQ and EQ are not simply two equal sides of the coin that make up a person.
That’s not to say that Emotional Intelligence doesn’t exist, just that it’s a roundabout way of measuring personality traits and behaviours that other mechanisms, such as the HEXACO personality inventory, do more reliably and effectively. EQ also carries the issue of ranking certain traits as more desirable or ‘better’ than others – for example, extraversion, agreeableness, and openness.
When we say someone has good or high EQ, what we tend to mean is that they’re friendly, kind, self-aware, and generally speaking, extraverted. They can adjust their tone and approach depending on who they’re talking to. They’re not known to be rude, or brash, or talk too much.
That’s an estimation of someone with good EQ, and this is the problem: It’s an empirical judgment. And while we think we’re describing someone who is emotionally intelligent, we’re really describing someone who is high in agreeableness, emotionality, openness, and other more valid measures of personality. Sounds like a great person, sure, but not necessarily a better type of person for every situation.
Consider this: Many studies have shown that disagreeable people tend to perform better over their career than people who are polite, kind, and friendly. A great proportion of CEOs, be they women or men, are high in disagreeableness. It’s easy to see why: though there are many downsides to disagreeableness, it pays, in many situations, to possess the ability to be combative, straightforward, and brutally honest. To think of disagreeableness as inherently worse than agreeableness is misguided and, at worst, discriminatory.
And even if that is not true, and all of the varied and ever-changing definitions of Emotional Intelligence lead to better job performance, how do we even measure it accurately?
In the context of hiring, EQ is often used as a gut-feel heuristic we apply to people with whom we gel. Even in structured face-to-face interviews, it can be very difficult to assign as score to the different measures of EQ.
Imagine someone is sitting across from you in an interview. By sight, they appear to be an average person in every way. So, by your questions and their responses, how do you measure their:
Again, aside from face-value judgments of agreeableness and social tact, it’s near-on impossible to assess EQ in any fair or meaningful way. That’s not even accounting for the many biases we, as humans, bring to the hiring process. You might, with some accuracy, be able to appraise a person’s EQ once it’s been proven, but that’s not useful at all in recruitment. In hiring, you’re hedging against unknowns, hoping for the best.
That’s what makes accurate personality assessment so critical – and why we built our Ai Smart Interviewer. It finds you the people you need based on an accurate, HEXACO-based assessment of their personality. One interview, via chat, is all it takes.
We look at the critical power skills – communication, emotionality, empathy, openness, and so on – and profile all candidates fairly against one another. So you’re ranking suitability on objective and repeatable measures. No guesswork involved. No bias.
You bet it works. 94% of the 2+ million candidates we’ve interviewed found their personality insights accurate and valuable. On average, 80% of the candidates who experience our interview process recommend you as an employer of choice, even if they don’t get the job.
Someone with an ostensibly high EQ is, in most cases, someone you might want. But appearances can be deceiving, and humans, by nature, are not good at objectively assessing personality. We’re just not, period.
Get the help you need, and you’ll quickly hire the people you want.
Walk into any store this festive season and you’ll see it instantly. The lights, the displays, the products are all crafted to draw people in. Retailers spend millions on campaigns to bring customers through the door.
But the real moment of truth isn’t the emotional TV ad, or the shimmering window display. It’s the human standing behind the counter. That person is the brand.
Most retailers know this, yet their hiring processes tell a different story. Candidates are often screened by rigid CV reviews or psychometric tests that force them into boxes. Neurodiverse candidates, career changers, and people from different cultural or educational backgrounds are often the ones who fall through the cracks.
And yet, these are the very people who may best understand your customers. If your store colleagues don’t reflect the diversity of the communities you serve, you create distance where there should be connection. You lose loyalty. You lose growth.
We call this gap the diversity mirror.
When retailers achieve mirrored diversity, their teams look like their customers:
Customers buy where they feel seen – making this a commercial imperative.
The challenge for HR leaders is that most hiring systems are biased by design. CVs privilege pedigree over potential. Multiple-choice tests reduce people to stereotypes. And rushed festive hiring campaigns only compound the problem.
That’s where Sapia.ai changes the equation: Every candidate is interviewed automatically, fairly, and in their own words.
With the right HR hiring tools, mirrored diversity becomes a data point you can track, prove, and deliver on. It’s no longer just a slogan.
David Jones, Australia’s premium department store, put this into practice:
The result? Store teams that belong with the brand and reflect the customers they serve.
Read the David Jones Case Study here 👇
As you prepare for festive hiring in the UK and Europe, ask yourself:
Because when your colleagues mirror your customers, you achieve growth, and by design, you’ll achieve inclusion.
See how Sapia.ai can help you achieve mirrored diversity this festive season. Book a demo with our team here.
Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.
Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.
Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.
Organisations invest heavily in their employer brand, career sites, and EVP campaigns, especially to attract underrepresented talent. But without the right data, it’s impossible to know if that investment is paying off.
Representation often varies across functions, locations, and stages of the hiring process. Blind spots allow bias to creep in, meaning underrepresented groups may drop out long before offer.
Collecting demographic data is only step one. Turning it into insight you can act on is where real change and better hiring outcomes happen.
The Diversity Dashboard in Discover Insights, Sapia.ai’s analytics tool, gives you real-time visibility into representation, inclusion, and fairness at every stage of your talent funnel. It helps you connect the dots between your attraction strategies and actual hiring outcomes.
Key features include:
With the Diversity Dashboard, you can pinpoint where inclusion is thriving and where it’s falling short.
It’s also a powerful tool to tell your success story. Celebrate wins by showing which underrepresented groups are making the biggest gains, and share that progress with boards, executives, and regulators.
Powered by explainable AI and the world’s largest structured interview dataset, your insights are fair, auditable, and evidence-based.
Measuring diversity is the first step. Using that data to take action is where you close the Diversity Gap. With the Diversity Dashboard, you can prove your strategy is working and make the changes where it isn’t.
Book a demo to see the Diversity Dashboard in action.
Why neuroinclusion can’t be a retrofit and how Sapia.ai is building a better experience for every candidate.
In the past, if you were neurodivergent and applying for a job, you were often asked to disclose your diagnosis to get a basic accommodation – extra time on a test, maybe the option to skip a task. That disclosure often came with risk: of judgment, of stigma, or just being seen as different.
This wasn’t inclusion. It was bureaucracy. And it made neurodiverse candidates carry the burden of fitting in.
We’ve come a long way, but we’re not there yet.
Over the last two decades, hiring practices have slowly moved away from reactive accommodations toward proactive, human-centric design. Leading employers began experimenting with:
But even these advances have often been limited in scope, applied to special hiring programs or specific roles. Neurodiverse talent still encounters systems built for neurotypical profiles, with limited flexibility and a heavy dose of social performance pressure.
Hiring needs to look different.
Truly inclusive hiring doesn’t rely on diagnosis or disclosure. It doesn’t just give a select few special treatment. It’s about removing friction for everyone, especially those who’ve historically been excluded.
That’s why Sapia.ai was built with universal design principles from day one.
Here’s what that looks like in practice:
It’s not a workaround. It’s a rework.
We tend to assume that social or “casual” interview formats make people comfortable. But for many neurodiverse individuals, icebreakers, group exercises, and informal chats are the problem, not the solution.
When we asked 6,000 neurodiverse candidates about their experience using Sapia.ai’s chat-based interview, they told us:
“It felt very 1:1 and trustworthy… I had time to fully think about my answers.”
“It was less anxiety-inducing than video interviews.”
“I like that all applicants get initial interviews which ensures an unbiased and fair way to weigh-up candidates.”
Some AI systems claim to infer skills or fit from resumes or behavioural data. But if the training data is biased or the experience itself is exclusionary, you’re just replicating the same inequity with more speed and scale.
Inclusion means seeing people for who they are, not who they resemble in your data set.
At Sapia.ai, every interaction is transparent, explainable, and scientifically validated. We use structured, fair assessments that work for all brains, not just neurotypical ones.
Neurodiversity is rising in both awareness and representation. However, inclusion won’t scale unless the systems behind hiring change as well.
That’s why we built a platform that:
Sapia.ai is already powering inclusive, structured, and scalable hiring for global employers like BT Group, Costa Coffee and Concentrix. Want to see how your hiring process can be more inclusive for neurodivergent individuals? Let’s chat.