To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.
By Jennifer Hewett, Australian Financial Review, 31 January
The online questionnaire, part of the Employsure jobs process, wants to know whether I respect and comply with authority. I get five options – strongly agree, agree, neutral, disagree, or strongly disagree. I tick “neutral”. Well sort of, sometimes, I think to myself, considering whether this might affect my chances on the Employsure portal.
The same choice presents itself for whether I am good at finding fault with what’s around me at work. I tick “neutral” again, guiltily acknowledging it’s just possible my editor might have a different opinion about whether I am far too good at that particular skill.
The choice seems less ambiguous when I am asked whether I forget to put things back in their proper place. I hover over “strongly agree” or “agree” and tick the latter – perhaps a little optimistically, wondering is Employsure worth it and if their interview intelligence system would pick up on my honesty.
And on it goes for 90 questions, with slight variations in the possible answers, as devised by an AI (artificial intelligence) algorithm. My responses to the bot will determine whether I get to the next stage of actually being interviewed for a job by a real person. AI approves who you should interview.
I soon get an encouraging email from Michael Morris, chief executive of Employsure – a company which provides advice on workplace relations and health and safety issues to small businesses. The Employsure contact method was straightforward, and Morris’s message clear. If I ever give up journalism, Morris tells me, I can try for a new career at Employsure. AI has approved me. Despite my deep scepticism about the process, I can’t help but feel a little pleased by the bot’s assessment.
That is because my rather self-serving answers to random personality questions fit those of the best performers at Employsure. There’s no possibility of ageism or sexism or any other latest “ism” influencing that. No old schoolmates or university or sporting framework, no biases about looks or clothes or mannerisms or personal history.
Instead, I participated in what is a variation on a personality test – based on the algorithmic analysis provided by another company, Sapia, operating in Europe and Australia and with 20 clients.
Morris says Employsure tested the performance of employees selected by Sapia’s algorithm against the choices of Employsure’s own human recruitment team for much of last year.
The fast-growing company hired around 450 people in 2018 with a workforce now totaling more than 800. Morris wanted good people and those more likely to stay.
A significant difference with AI
The experience convinced him that rather than using more traditional CVs to screen applicants, it was worth paying Sapia for its AI technology as Employsure continues to expand its numbers this year. Employsure now only interviews the 10-15 per cent of those who are graded “yes” or “maybe” by the bot.
“The overlay of AI made a significant difference in overall performance, productivity and tenure,” Morris says. “And it means the recruitment team can have a head start on engaging in better conversations with those who have interviews.” This is still a distinct minority view among Australian businesses which have been generally reluctant to embrace the promise of AI when it comes to hiring.
The trend to make greater use of AI in business generally is inevitable and accelerating. Just consider all those online “conversations” we now have about customer service and products as the ever-patient bot nudges us this way and that.
Just as inevitably, it is leading to community concerns about whether AI will be used to replace too many people’s jobs. According to a study by the McKinsey Global Institute, intelligent agents and robots could eliminate as much as 30 per cent of human labour by 2030. The scale would dwarf the move away from agricultural labour during the 1900s in the United States and Europe.
Of course, the record of technology shifts over centuries always ending up creating many more other types of jobs does not completely soothe fears that this time it’s different. Even if such alarm is overstated, dramatic changes in technology can certainly prove socially and economically disruptive for long periods. AI can also be scary.
But this version of AI is more about filling new jobs more efficiently. Many large global companies already use it to filter job applicants, especially those coming in at lower levels. Its advocates argue it efficiently eliminates bias or the tendency for people to hire in their own image.
Immediate payback with AI
Not that this always goes smoothly – even for the most digitally sophisticated businesses. Amazon abandoned its own AI hiring tool last October when management realised it had only introduced more bias into the process. Its AI system was based on modelling the CVs of those already at the company – who tended to be male. Naturally, that made prospective hires more likely to be male too. So much for gender-diversity targets.
Sapia’s chief executive is Barb Hyman, formerly a human resources executive for the online real estate advertising company REA Group. She says the system doesn’t work for those companies that don’t measure the performance of their existing employees but the data becomes more and more accurate as more information is added.
By matching responses of applicants against only those employees who are already doing well, it can be extremely efficient with immediate payback – especially for larger companies. The data can also be used to change the culture in an organisation by screening the types of personalities who are hired.
Not surprisingly, Hyman says the data demonstrates how different personalities are better fitted to different sorts of roles. So those who do well in caring jobs tend to be reliable and demonstrate traits of modesty and humility. Good salespeople are focused, somewhat self-absorbed, disorganised and transactional. Those who are involved in building long-term business relationships need to be more adaptable, resilient and open.
Sounds more like common sense than AI. But there’s less and less of that around anywhere. AI beckons instead.
Related
Blog
Mirrored diversity: why retail teams should look like their customers
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.
Blog
The Diversity Dashboard: Proving your DEI strategy is working
Why measuring diversity matters
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.
What is the Diversity Dashboard?
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:
- Demographic filters – Switch between gender, ethnicity, English as an additional language, First Nations status, disability, and veteran status. View age and ethnicity in standard or alternative formats to match regional reporting needs.
- Representation highlights – Identify the top five represented sub-groups for each demographic, plus the three fastest-growing among underrepresented groups.
- Track trends over time – See month-by-month changes in representation over the past 12 months, compare to earlier periods, and connect the data back to your EVP and attraction spend.
- Candidate experience metrics – Measure CSAT (satisfaction) and engagement rates by demographic to ensure your hiring process works for everyone. Inclusion is measurable.
- Hiring fairness – Compare representation in your applied, recommended, and hired pools to spot drop-offs. Understand not just who applies, but who progresses — and why.
From insight to action
With the Diversity Dashboard, you can pinpoint where inclusion is thriving and where it’s falling short.
- See if your EASL candidates are applying in high numbers but not progressing to live interview.
- Spot if candidates with a disability report high satisfaction but have lower offer rates.
- Track the impact of targeted campaigns month-by-month and adjust quickly when something isn’t working.
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.
Built on science, backed by trust
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.
Blog
Neuroinclusion by design. Not by exception.
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.
Shifting from retrofits to inclusive-by-design
Over the last two decades, hiring practices have slowly moved away from reactive accommodations toward proactive, human-centric design. Leading employers began experimenting with:
- Sharing interview questions in advance
- Replacing group exercises with structured simulations
- Offering a variety of assessment formats
- Co-designing assessments with neurodiverse candidates
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.
Insight 1: The next frontier of hiring equity is universal design
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:
- No time limits — Candidates answer at their own pace
- No pressure to perform — It’s a conversation, not a spotlight
- No video, no group tasks — Just structured, 1:1 chat-based interviews
- Built-in coaching — Everyone gets personalised feedback
It’s not a workaround. It’s a rework.
Insight 2: Not all “friendly” methods are inclusive
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.”
Insight 3: Prediction ≠ Inclusion
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.
Where to from here?
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:
- Doesn’t rely on disclosure
- Removes ambiguity and pressure
- Creates space for everyone to shine
- Measures what matters, fairly
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.