I live in Melbourne, Australia. When I speak to customers overseas they all sympathize with the restrictions imposed on us as a result of COVID-19. We are the State that that just can’t seem to take our eyes off the numbers, being used as an invisible algorithm to drive decisions like when we can see our friends and families again, go to the footy, or have a drink at the pub.
Scott Galloway talks of Covid-19 being an accelerant, not a change agent. Organisations who were already on the path of disrupting their own business models have surged ahead. Those with unfit practices might have been able to do a fun run, but what we have now is an ultra-marathon.
Organizations need a new playbook. We humans need a new playbook. COVID-19 is transformational for organizations, and it requires transformational thinking and responses.
The lack of deep thinking on this is reflected in the exhaustion we are all feeling right now. Many of us find ourselves spending 12 hours a day on back-to-back zoom calls. We are missing out on the key benefit of flexibility, which is unleashing productivity. Which means doing more in fewer hours, not doing more by working longer hours.
Few of us have made the transformational changes required to accommodate true remote work. One of those changes has to be to embrace asynchronous working norms.
Asynchronous work needs asynchronous communication. This simply means that work doesn’t happen at the same time for everyone. Productivity and flexibility for employees come when we don’t all have to get in a room, virtual or otherwise to do our work. This usually means communicating in writing, not video.
The other change that needs to happen is less vertical decision-making, less requiring decisions to ‘go up’ to be made – and more pushing them down to the individual level as much as possible. It’s time to really empower your people. Leaders need to set the vision and trust their people to solve how to get there. This means creating cultures of trust and leaving behind cultures of control.
The good news is that a by-product of remote work will be a natural increase in accountability for performance. The reality is you can’t fake it or fudge it as easily when your actual work output, not your personality, is what is most visible to everyone. The talkers vs the doers are quickly exposed. The big ‘P’ personality types won’t survive as long as there is no place for them to entertain us with their stories and their charisma.
This new reality won’t work for everyone and demands transparency around performance and expectations from both sides. For many, this may lead to a loss of confidence and validation that they would normally get from being part of a visible tribe in the office. When you don’t have a team or a manager around you to mentor you, notice your good work, or your bad work, you need to do the noticing yourself. Self-awareness becomes crucial. As does self-motivation, the discipline to see a task through without much pushing or oversight.
Organizations need to give way more attention to hiring and promoting these qualities that will enable individuals to be independently productive. It may even mean evolving your values to reflect those kinds of new survival traits.
What makes that shift especially tough for many organizations is that we have all been doing the opposite for years. To coin a phrase from Johnathan Haidt, we have been guilty of coddling our kids and our employees. Haidt, author of “The Coddling of the American Mind’ notes the impact of all that coddling and the resulting culture of ‘safetyism’, which stunts the development of that life skill- resilience, a trait critical for all of us right now.
Simon Sinek, a speaker/writer on cooperation, trust, and change says developing better managers can help young people build better resilience. This becomes harder in a world where you’re not spending time with your manager. Rather, the individual needs to take on more responsibility for their own learning and for their own motivation and engagement.
So how do you create more individual and organizational resilience? How do you hire for and build the skill of accountability?
It requires creating an expectation via explicit conversations about the need for you to own your own work, your own career. It demands hiring people who have heightened self-awareness, to know what they need help with, to ask for what they need.
Which jobs are better suited to me? What am I good at, not good at? How do others see me so I can better manage my relationships at work or at home? What part of me is helping me or hindering me in life?
The problem is that not every type of person will do that comfortably and this is where Covid-19 risks creating another privileged class of people who do better in that environment. This is where I advocate for technology as an essential co-pilot for employees to understand themselves better and help coach them to level the playing field. Technology that can draw out the best in people and help them find their strengths and agency.
The new playbook already has a few chapters written by some well-known disruptors. For example, Jeff Bezos banning PowerPoint from meetings, Google’s money-ball approach to hiring and promotion, virtually inventing people analytics. The text-only interviews of Automattic, the company behind WordPress, with 1000+ remote workforce in 73 countries.
In short, to leaders of all domains: move to the new playbook.
Get on with experimenting with fundamentally new ways of working. And, recognise that technology will be your co-pilot in that change.
Source: Barbara Hyman, Recruiting Daily, 1 October 2020
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A new study has just confirmed what many in HR have long suspected: traditional psychometric tests are no longer the gold standard for hiring.
Published in Frontiers in Psychology, the research compared AI-powered, chat-based interviews to traditional assessments, finding that structured, conversational AI interviews significantly reduce social desirability bias, deliver a better candidate experience, and offer a fairer path to talent discovery.
We’ve always believed hiring should be about understanding people and their potential, rather than reducing them to static scores. This latest research validates that approach, signalling to employers what modern, fair and inclusive hiring should look like.
While used for many decades in the absence of a more candidate-first approach, psychometric testing has some fatal flaws.
For starters, these tests rely heavily on self-reporting. Candidates are expected to assess their own traits. Could you truly and honestly rate how conscientious you are, how well you manage stress, or how likely you are to follow rules? Human beings are nuanced, and in high-stakes situations like job applications, most people are answering to impress, which can lead to less-than-honest self-evaluations.
This is known as social desirability bias: a tendency to respond in ways that are perceived as more favourable or acceptable, even if they don’t reflect reality. In other words, traditional assessments often capture a version of the candidate that’s curated for the test, not the person who will show up to work.
Worse still, these assessments can feel cold, transactional, even intimidating. They do little to surface communication skills, adaptability, or real-world problem solving, the things that make someone great at a job. And for many candidates, especially those from underrepresented backgrounds, the format itself can feel exclusionary.
Enter conversational AI.
Organisations have been using chat-based interviews to assess talent since before 2018, and they offer a distinctly different approach.
Rather than asking candidates to rate themselves on abstract traits, they invite them into a structured, open-ended conversation. This creates space for candidates to share stories, explain their thinking, and demonstrate how they communicate and solve problems.
The format reduces stress and pressure because it feels more like messaging than testing. Candidates can be more authentic, and their responses have been proven to reveal personality traits, values, and competencies in a context that mirrors honest workplace communication.
Importantly, every candidate receives the same questions, evaluated against the same objective, explainable framework. These interviews are structured by design, evaluated by AI models like Sapia.ai’s InterviewBERT, and built on deep language analysis. That means better data, richer insights, and a process that works at scale without compromising fairness.
The new study, published in Frontiers in Psychology, put AI-powered, chat-based interviews head-to-head with traditional psychometric assessments, and the results were striking.
One of the most significant takeaways was that candidates are less likely to “fake good” in chat interviews. The study found that AI-led conversations reduce social desirability bias, giving a more honest, unfiltered view of how people think and express themselves. That’s because, unlike multiple-choice questionnaires, chat-based assessments don’t offer obvious “right” answers – it’s on the candidate to express themselves authentically and not guess teh answer they think they would be rewarded for.
The research also confirmed what our candidate feedback has shown for years: people actually enjoy this kind of assessment. Participants rated the chat interviews as more engaging, less stressful, and more respectful of their individuality. In a hiring landscape where candidate experience is make-or-break, this matters.
And while traditional psychometric tests still show higher predictive validity in isolated lab conditions, the researchers were clear: real-world hiring decisions can’t be reduced to prediction alone. Fairness, transparency, and experience matter just as much, often more, when building trust and attracting top talent.
Sapia.ai was spotlighted in the study as a leader in this space, with our InterviewBERT model recognised for its ability to interpret candidate responses in a way that’s explainable, responsible, and grounded in science.
Today, hiring has to be about earning trust and empowering candidates to show up as their full selves, and having a voice in the process.
Traditional assessments often strip candidates of agency. They’re asked to conform, perform, and second-guess what the “right” answer might be. Chat-based interviews flip that dynamic. By inviting candidates into an open conversation, they offer something rare in hiring: autonomy. Candidates can tell their story, explain their thinking, and share how they approach real-world challenges, all in their own words.
This signals respect from the employer. It says: We trust you to show us who you are.
Hiring should be a two-way street – a long-held belief we’ve had, now backed by peer-reviewed science. The new research confirms that AI-led interviews can reduce bias, enhance fairness, and give candidates control over how they’re seen and evaluated.
It’s time for a new way to map progress in AI adoption, and pilots are not it.
Over the past year, I’ve been lucky enough to see inside dozens of enterprise AI programs. As a CEO, founder, and recently, judge in the inaugural Australian Financial Review AI Awards.
And here’s what struck me:
Despite the hype, we still don’t have a shared language for AI maturity in business.
Some companies are racing ahead. Others are still building slide decks. But the real issue is that even the orgs that are “doing AI” often don’t know what good looks like.
The most successful AI adoption strategy does not have you buying the hottest Gen AI tool or spinning up a chatbot to solve one use case. What it should do is build organisational capability in AI ethics, AI governance, data, design, and most of all, leadership.
It’s time we introduced a real AI Maturity Model. Not a checklist. A considered progression model. Something that recognises where your organisation is today and what needs to evolve next, safely, responsibly, and strategically.
Here’s an early sketch based on what I’ve seen:
AI is a capability.And like any capability, it needs time, structure, investment, and a map.
If you’re an HR leader, CIO, or enterprise buyer, and you’re trying to separate the real from the theatre, maturity thinking is your edge.
Let’s stop asking, “Who’s using AI?”
And start asking: “How mature is our AI practice and what’s the next step?”
I’m working on a more complete model now, based on what I’ve seen in Australia, the UK, and across our customer base. If you’re thinking about this too, I’d love to hear from you.
For too long, AI in hiring has been a black box. It promises speed, fairness, and efficiency, but rarely shows its work.
That era is ending.
“AI hiring should never feel like a mystery. Transparency builds trust, and trust drives adoption.”
At Sapia.ai, we’ve always worked to provide transparency to our customers. Whether with explainable scores, understandable AI models, or by sharing ROI data regularly, it’s a founding principle on which we build all of our products.
Now, with Discover Insights, transparency is embedded into our user experience. And it’s giving TA leaders the clarity to lead with confidence.
Transparency Is the New Talent Advantage
Candidates expect fairness. Executives demand ROI. Boards want compliance. Transparency delivers all three.
Even visionary Talent Leaders can find it difficult to move beyond managing processes to driving strategy without the right data. Discover Insights changes that.
“When talent leaders can see what’s working (and why) they can stop defending their strategy and start owning it.”
What it is: The median time between application and hire.
Why it matters: This is your speedometer. A sharp view of how long hiring takes and how that varies by cohort, role, or team helps you identify delays and prove efficiency gains to leadership.
Faster time to hire = faster access to revenue-driving talent.
What it is: Satisfaction scores, brand advocacy measures, and unfiltered candidate comments.
Why it matters: Many platforms track satisfaction. Sapia.ai’s Discover Insights takes it further, measuring whether that satisfaction translates into employer and consumer brand advocacy.
And with verbatim feedback collected at scale, talent leaders don’t have to guess how candidates feel. They can read it, learn from it, and take action.
You don’t just measure experience. You understand it in the candidates’ own words.
What it is: The percentage of candidates who exit the hiring process at different stages, and how to spot why.
Why it matters: Understanding drop-off points lets teams fix friction quickly. Embedding automation early in the funnel reduces recruiter workload and elevates top candidates, getting them talking to your hiring teams faster.
Assessment completion benchmarks in volume hiring range between 60–80%, but with a mobile-first, chat-based format like Sapia.ai’s, clients often exceed that.
Optimising your funnel isn’t about doing more. It’s about doing smarter, with less effort and better outcomes.
What it is: The percentage of completed applications that result in a hire.
Why it matters: This is your funnel efficiency score. A high yield means your sourcing, screening, and selection are aligned. A low one? There’s leakage, misfit, or missed opportunity.
Hiring yield signals funnel health, recruiter performance, and candidate-process fit.
What it is: Insights into how candidate scores are distributed, and whether responses appear copied or AI-generated.
Why it matters: In high-volume hiring, a normal distribution of scores suggests your assessment is calibrated fairly. If it’s skewed too far left or right, it could be too hard or too easy, and that affects trust.
Add in answer originality, and you can track engagement integrity, protecting both your process and your brand.
To effectively lead, you need more than simply tracking; you need insights enabling action.
When you can see how AI impacts every part of your hiring, from recruiter productivity to candidate sentiment to untapped talent, you lead with insight, not assumption. And that’s how TA earns a seat at the strategy table.