A few weeks ago, I had the privilege to attend Sir Ken Robinson’s opening keynote speech – ‘The Pulse of Innovation’ – at HR Tech World Congress in London.
(You might recognise Sir Ken Robinson from his Ted Talk, ‘Do schools kill creativity?’, which has been viewed almost 45 million times so far.)
As expected, Sir Ken’s speech was filled with equal parts of humour, inspiring stories and thought-provoking ideas around creativity and innovation at work.
Sir Ken opened by highlighting that the average lifespan of organisations is now shorter than it ever has been, and he stressed the importance of continuous innovation and adaptation to external factors in order for organisations to survive – quoting the famous example of Kodak as a company that failed to do so.
Given the context of his speech, particularly focusing on the advancements in HR tech and AI in HR, it came as little surprise that he stressed the importance of HR’s role in facilitating innovation by identifying and refining talent, and he brought forward one key point which I found particularly interesting.
Sir Ken’s point, especially relevant in the era of companies using AI in HR, is that talent is not something that we can easily identify; it is hidden within individuals, and it is HR’s role, now increasingly supported by AI in HR tech, to ‘mine’ for that talent.
“Human talent is highly diverse and it’s often buried. Human resources are like natural resources, you have to go and find them, cultivate them, refine them. If you do this you find that people are capable of extraordinary things.” Sir Ken Robinson
Everyone has potential but it can be quite difficult to see it amongst all the noise and stereotypes we bring with us.
To illustrate this point, Sir Ken cited his own experience interviewing Sir Paul McCartney and George Harrison, both members of a band I think you might know the name of.
During the interview, Sir Ken was surprised to find out that neither of these immensely talented musicians was recognised by their music teacher as ‘top of the class’ – yes, they happened to have the same music teacher in school.
This truly highlights the limitations of our ability to be able to determine what talent looks like (the poor music teacher must really have had to re-evaluate his assessment protocol!).
One of the reasons for this is that we are all inherently bias. While this bias is not conscious, it does affect decisions we make every day.
The ability to categorise or stereotype is an important developmental and evolutionary process that helps humans make sense of the world.
Stereotypes help us make judgements quickly without having to source all pieces of information, but it is detrimental when applied to identifying human talent and hiring decisions.
A basic example; in recruitment and talent acquisition, if successful salespeople in our organisation have all previously had red hair, we might decide that we should only hire red-haired sales assistants.
As human beings, when we try to identify what good ‘looks like’ we concentrate on a few aspects of an individual, and may end up ignoring other important factors that lead to success.
This was further highlighted in a recent Harvard Business Review article, where it was found that 40% of individuals in their study of 1,964 ‘high potentials’ (employees in the top 5% of the organisation) were incorrectly classified as belonging in that category.
In other words, almost half of those identified by managers were not high potentials at all.
42% were below average, with 12% actually being in the bottom ranks with regards to leadership effectiveness.
The point clearly illustrated here is the inability of managers to correctly identify high potentials by not concentrating on the right traits and skills of an individual – they are only human after all.
Sir Ken Robinson spoke in detail about the success of the Beatles and how it was due to the diversity within their group – something that is almost impossible to achieve when allowing subjectivity to guide hiring decisions.
One way of addressing subjectivity and unconscious biases in the hiring process is to make use of data-driven technologies.
Using data to inform hiring decisions means HR can take into account the traits and skills that actually lead to performance, rather than keep focusing on hiring based on subjective stereotypes of success.
At Sapia, we develop predictive models, powered by artificial intelligence, that can predict the likelihood of candidates performing well in organisations based on their behaviour – not on the stereotype they fit into.
Our algorithms and questions are created so that everyone is given an equal opportunity to succeed and be considered, based on what actually drives performance – regardless of age, gender or nationality.
Through adopting AI and data science in the HR field, we can get one step closer to bias-free hiring and increased diversity within organisations.
Whilst AI does take the human out of some part of the hiring decision, the outcomes ensure the human is at the forefront with more opportunities for all.
If you would like to learn more about how AI can impact hiring outcomes in your organisation, feel free to get in touch with our sales team. You can also try it out here for yourself right now!
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.