The difference between psych tests and predictive analytics

This is the state of hiring in 2025. Too often, candidates are ghosted, ignored, and reduced to a CV. Recruiters are forced to make decisions in data poverty, with scraps of information like grades, job titles, or where someone has worked before. Privilege gets rewarded; potential gets overlooked.

For the first time, we now have evidence that AI, when designed responsibly, brings humanity back to hiring.

The largest research study of its kind

Sapia.ai has released the Humanising Hiring report. The largest analysis ever conducted into candidate experience with AI interviews. The study draws on more than 1 million interviews and 11 million words of candidate feedback across 30+ countries.

Unlike surveys or anecdotal reviews, this research is grounded in what candidates themselves chose to share at one of the most stressful moments of their lives: applying for a job.

The findings are bold and unprecedented

• 9.05/10 average candidate satisfaction across all groups and industries
• 81.8% of candidates left written feedback — engagement at this scale has never been seen before in hiring research
• 8 in 10 candidates would recommend an employer just because of the interview

• 30% more women apply when told AI will assess them, resulting in a 36% closure of the gender gap

• 98% hiring equity for people with disabilities through a blind, untimed, mobile-first interview design

Candidate voices

Here’s what candidates themselves revealed:

“None of the other companies I’ve applied to do this sort of thing. It’s so unique and wonderful to give this sort of insight to people… whether we get the job or not, we can take away something very valuable out of the process.”

“That felt so personal, as if the person genuinely took the time to read my answers and send me a summary of myself… that was pretty amazing.”

Expert validation

“This study stands out as one of the most comprehensive examinations of candidate experience to date. Analysing over a million interviews and 11 million words of candidate feedback, the findings make clear that responsibly designed AI has the potential to fundamentally improve hiring — not just by increasing speed, but by advancing fairness, enhancing the human aspect, and leading to stronger job matches.”
— Kathi Enderes, SVP Research & Global Industry Analyst, The Josh Bersin Company

Proof that AI can be human

The research challenges the idea that AI dehumanises the hiring process. In fact, it proves the opposite: when thoughtfully designed, AI can restore dignity to candidates by giving them a real interview from the very first interaction, giving them space to share their story, and giving them timely feedback.

With Sapia.ai’s Chat Interview:

• Every candidate gets the same structured, role-relevant questions.

• Interviews are untimed, so candidates can answer at their own pace.

• Bias is monitored continuously under our FAIR™ framework.

• Every candidate receives personalised feedback.

This isn’t automation for the sake of speed. It’s intelligence that puts people first, and it works. Leading global brands, including Qantas, Joe & the Juice, BT Group, Holland & Barrett, and Woolworths, have all transformed their hiring outcomes while enhancing the candidate experience.

Why it matters now

Applicant volumes are exploding. Boards are demanding ROI on people decisions. And candidates expect fairness and agency. Sticking with the status quo — ghosting, inconsistent interviews, CV screening — comes at a real cost in brand equity, lost talent, and wasted time.

It’s time to move from data poverty to data richness, from broken processes to brilliant hiring.

Download the report

This is the first time candidate feedback on AI interviews has been analysed at such scale. The insights are clear: hiring can be brilliant.

👉 Download the Humanising Hiring report now to see the full findings.

Barb Hyman, CEO & Founder, Sapia.ai

Why skills data matters for HR and CHROs

Every CHRO I speak to wants clarity on skills:

• What skills do we have today?

• What skills do we need tomorrow?

• How do we close the gap?

The skills-based organisation has become HR’s holy grail. But not all skills data is created equal. The way you capture it has ethical consequences.

Two very different approaches to skills analysis

1. Skills inference from digital traces

Some vendors mine employees’ “digital exhaust” by scanning emails, CRM activity, project tickets and Slack messages to guess what skills someone has.

It is broad and fast, but fairness is a real concern.

2. Skills measurement through structured conversations

The alternative is to measure skills directly. Structured, science-backed conversations reveal behaviours, competencies and potential. This data is transparent, explainable and given with consent.

It takes longer to build, but it is grounded in reality.

The risks of skills inference HR leaders must confront

• Surveillance and trust: Do your people know their digital trails are being mined? What happens when they find out?

• Bias: Who writes more Slack updates, introverts or extroverts? Who logs more Jira tickets, engineers or managers? Behaviour is not the same as skills.

• Explainability: If an algorithm says, “You are good at negotiation” because you sent lots of emails, how can you validate that?

• Agency: If a system builds a skills profile without consent, do employees have control over their own career data?

A more human approach: skills measurement

Skills define careers. They shape mobility, pay and opportunity. That makes how you measure them an ethical choice as well as a technical one.

At Sapia.ai, we have shown that structured, untimed, conversational AI interviews restore dignity in hiring and skills measurement. Over 8 million interviews across 50+ languages prove that candidates prefer transparent and fair processes that let them share who they are, in their own words.

Skills measurement is about trust, fairness and people’s futures.

Questions every HR and CHRO should ask

When evaluating skills solutions, ask:

• Is this system measuring real skills, or only inferring them from proxies?

• Would I be comfortable if employees knew exactly how their skills profile was created?

• Does this process give people agency over their data, or take it away?

The real test of ethics in the skills-based organisation

The choice is between skills data that is guessed from digital traces and skills data that is earned through evidence, reflection and dialogue.
If you want trust in your people decisions, choose measurement over inference.

To see how candidates really feel about ethical skills measurement, check out our latest research report: Humanising Hiring, the largest scale analysis of candidate experience of AI interviews – ever.

FAQs

What is the most ethical way to measure skills?
The most ethical method is to use structured, science-backed conversations that assess behaviours, competencies and potential with consent and transparency.

Why is skills inference problematic?
Skills inference relies on digital traces such as emails or Slack activity, which can introduce bias, raise privacy concerns and reduce employee trust.

How does ethical AI help with skills measurement?
Ethical AI, such as structured conversational interviews, ensures fairness by using consistent data, removing demographic bias and giving every candidate or employee a voice.

What should HR leaders look for in a skills platform?
Look for transparency, explainability, inclusivity and evidence that the platform measures skills directly rather than guessing from digital behaviour.

How does Sapia.ai support ethical skills measurement?
Sapia.ai uses structured, untimed chat interviews in over 50 languages. Every candidate receives

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.

The missing link in retail hiring

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.

What mirrored diversity looks like

When retailers achieve mirrored diversity, their teams look like their customers:

• A grocery store team that reflects the cultural mix of its neighbourhood.
• A fashion store with colleagues who understand both style and accessibility.
• A beauty retailer whose teams reflect every skin tone, gender, and background that walks through the door.

Customers buy where they feel seen – making this a commercial imperative. 

How to recruit seasonal employees with mirrored diversity

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.

• Bias is measured and monitored using Sapia.ai’s FAIR™ framework.
• Outcomes are validated at scale: 7+ million candidates, 52 countries, average candidate satisfaction 9.2/10.
• Diversity can be measured: with the Diversity Dashboard, you can track DEI capture rates, candidate engagement, and diversity hiring outcomes across every stage of the funnel.

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.

Retail recruiting strategies in action: the David Jones example

David Jones, Australia’s premium department store, put this into practice:

• 40,000 festive applicants screened automatically
• 80% of final hires recommended by Sapia.ai
• Recruiters freed up 4,000 hours in screening time
• Candidate experience rated 9.1/10

The result? Store teams that belong with the brand and reflect the customers they serve.

Read the David Jones Case Study here 👇

Recruiting ideas for retail leaders this festive season

As you prepare for festive hiring in the UK and Europe, ask yourself:

• How much will you spend on marketing this Christmas?
• And how much will you invest in ensuring the colleagues who deliver that brand promise reflect the people you want in your stores?

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. 

FAQs on retail recruitment and mirrored diversity

What is mirrored diversity in retail?

Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.

Why is diversity important in seasonal retail hiring?

Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.

How can retailers improve their hiring strategies?

Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.