If done effectively, interviews are a great means of assessing a candidate. We trust them to enable us to determine if our candidates have the attributes, traits, behaviours, skills, experience and personality to meet the role requirements.
Here’s the problem with traditional methods and where AI interview platforms come in. It is physically impossible to interview every candidate manually. So, we rely on CV screening as the first step, a process often augmented by AI interview software. A recruiter on average spends six seconds looking at the resume. In those six seconds, a snap judgement is made on shortcuts (biases).
At the starting block, the process has already failed. You cannot possibly pick qualities like grit and initiative from a CV, right? Then, of the people who applied for the job, around 13% of applicants may get an AI job interview. During C-19 times – you can more than half that number.
In this way, you realise the value of interviews without investing one-minute of your time in them.
Imagine this. Everyone has already been interviewed before you have read one CV. A pre-qualified, pre-assessed, high-quality shortlist before you have read ONE CV. That’s the dream! Because now you are not wasting time reading resumes of people who either can’t do the job, won’t do the job, or they just don’t fit. And, instead of flicking through 100 resumes for a puny 6 seconds each, you can take the space to consider the best. The best? Those candidates who have already been pre-selected for that grit and initiative you so badly want in your team.
You can try out Sapia’s FirstInterview experience here.
Time to hire measures recruiting efficiency. It is the number of days between the first contact with a candidate to the day the candidate accepts the offer. Screening is your first time-to-hire bottleneck.
Even if you’re using an ATS you may be able to easily rank resumes, but you still have to consider them. And there’s your block.
A new generation of interview automation is here so that you can have every candidate interviewed in a flash. Of course, it integrates and works seamlessly within your ATS. It saves recruiters from screening resumes and boosts the efficiency of your recruiting process.
Reducing time to hire is great for candidates who get the job faster (or can move onto the next job). It is terrific for recruiters who get the reward of quicker placements and attaining their metrics. It is a relief for hiring managers who get their team to a full complement and can get back to their actual job.
Interviewing automation makes your recruiting process much faster – usually around 90% faster.
Hiring managers want their best team. They want people who can do the job, who will do the job and who will perform. With interview automation, Ai assesses traits, communication skills, optimism and temperament prior to you getting involved.
As a Recruiter, you get a complete picture of a candidate beyond what is written on their CV. You learn a lot of information about the candidate. Ai will rank and grade all your candidates for you. It pre-qualifies those who are a fit to move forward.
Have you ever thought to yourself: “If only I could hire 10 more Julie’s!” (*insert name)? With Ai, you can. And, as far as quality goes, this is the distinction from all other forms of pre-employment.
AI learns what a successful hire looks like and pin-points more like them. AI bases this learning on your historical recruiting decisions and then applies that knowledge to new candidates to automatically screen, grade, and rank them.
Interviewing automation gets you to the best of your talent pool much quicker resulting in, on aggregate, much better quality in your hires.
Diversity and Inclusion have been on the HR agenda for a long time. And in more recent years, it’s made its way onto the Business agenda too. In 2020, global management consulting company McKinsey again confirmed that companies with both ethnic and cultural diversity and gender diversity in corporate leadership are outperforming non-diverse companies on profitability. They found: “The most diverse companies are now more likely than ever to outperform non-diverse companies on profitability”
Diversity improves employee productivity, retention and happiness. Settled then. We want businesses that are diverse and fair.
Here’s the King of Recruiter biases: The Dunning-Kruger Effect. It’s where we lack the self-awareness to accurately assess our own skills meaning that we overestimate our ability. You think you are a brilliant totally unbiased Recruiter, right? You may well be, but it’s not uncommon to think you’re smarter or better than the average person. Haven’t we all skipped over candidates who don’t have the requisite ‘Big 4’ employer on their resume, or the ‘right kind of degree’?
Even when we don’t mean to be, human bias is pervasive. We keep these biases alive, through our relentless refusal to admit our shortfalls. And unfortunately, this isn’t great when it comes to hiring for diversity.
The reason for this is you can test, adjust and get rid of biases. The good news is Ai doesn’t resist stubbornly while claiming absolute fairness and denying any bias. This means that undesirable machine learning biases will tend to decrease over time. In Sapia’s case, its blind screening at its best. Nothing that typically influences human bias is introduced into the algorithms – no CV’s, no socials, no videos, no facial recognition – it’s just the candidate and their text answers. Much fairer for candidates of course and a richer experience where they can just be themselves.
Interviewing automation makes your recruiting process much fairer and your hiring decisions far more diverse.
Your ability to hire cost-effectively will be hampered if you don’t have the right tools. Make sure that all your recruitment technology is pulling in the same direction – to make hiring as seamless, streamlined and stress-free as possible – rather than working against you. The money you invest in the right technology will soon pay off when it comes to time and efficiency savings.
Significant costs are borne by an organisation when an employee voluntarily leaves.
These include replacement costs such as costs associated with advertising, screening and selecting a new candidate. A study conducted by the Australian HR Institute in (AHRI) 2018 across all major industry sectors in Australia (Begley & Dunne, 2018) found that on average companies face an annual turnover rate of 18%. Within the age group of 18 to 35 it worsens significantly, at 37%. That is, more than 1 in 3 people in the youngest age group leave an organisation within a year.
Imagine if you could predict those with a likelihood of churning before you had met them? Then think about the enormous savings that would be derived across your organization if you could do so.
If you haven’t yet automated your interviews, you are spending too much on hiring.
Chances are that reading CV’s and running interviews are not the hardest part of your job but are the most time-consuming. What if you could have available time for those high-value tasks. Like managing your stakeholders. Getting to know the business better. Improving your business partnership skills. Learning the essence of what Hiring Managers actually want. Networking and improving talent pools, particularly for those hard-to-fill roles.
So, if interview automation can take care of all of your first interviews for you then ask yourself:
Of how much value am I when buried knee-deep in screening? Visualise less of that and more of the buzz you get when you find the perfect fit. There’s no better feeling than knowing you’ve helped someone further their career AND helped your Hiring Manager find someone who ‘just fits’ and will perform. Nothing can replace the collaboration and empathy that you as a live person can extend.
According to this Sapia research paper published by IEEE: Structured interviews (where the same questions are asked from every candidate, in a controlled conversation flow and evaluated using a well-defined rubric) have not only shown to reduce bias but also increase the ability to predict future job performance. With interview automation, the questions asked in a structured interview are derived using a job analysis as opposed to interviewer preference and are typically based on past behaviour and situational judgement.
Interviewing automation frees up recruiter’s time to perform higher-value tasks with far greater output.
With interview automation you can move from an elongated process that leaves candidates in the dark, not knowing where they stand, to a super-efficient experience that feels empowering.
According to the Society for Human Resource Management (SHRM), 82% of candidates report the ideal recruiter interaction is a mix of innovative technology and personal, human interaction.
Improving your candidate experience is so much easier by adopting technology that is inclusive, personalised and relatable. Sapia’s interview automation offers a mobile-first, chat interview that interviews everyone in-depth and at scale. Giving every candidate personalised feedback.
Here is what interview automation offers above a manual interview process for candidates:
Interviewing automation enhances candidate experience, with no further time investment from you.
Download the 2020 Candidate Experience Playbook here
Gartner predicts by 2021, 50% of enterprises will spend greater budget on chatbot creation and bots than traditional mobile app development.
Businesses are adopting Sapia’s chat interviews across various job families – especially in front-line customer service roles. The quickest payback you will get on an investment in interview automation is to apply it to your high-volume roles first. Interview automation can truly enhance your high-volume recruitment process and help you make it more efficient (and pleasant) for everyone involved. This will help you get your time-back really quickly and release the budget for automation in other areas of recruiting.
The future of all first interactions between candidates and your business will be through automation. The only decision, for now, is where you will adopt interview automation first.
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You can try out Sapia’s FirstInterview right now, or leave us your details here to get a personalised demo.
If there was ever a time for our profession to show humanity for the thousands that are looking for work, that time is now.
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.
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.
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
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.”
“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
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.
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.
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
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.
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.
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.
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?
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.
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 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.
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.
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.