When interviewing, asking the right questions can open the door to genuine insights and a better interview experience. So, which questions truly resonate with candidates? Our latest research, led by the Data Scientists at Sapia Labs, reveals the top five questions that candidates appreciate the most from our Chat Interview experience, that over 5 million candidates from 47 countries have completed.
Why is asking the right questions important?
The Live Interview is crucial to volume hiring. Having the opportunity to meet for the first time, to extend the connection already created online – it’s almost like the first date of the volume hiring experience. Showing up unprepared or asking questions that candidates can’t engage with is a waste of everyone’s time.
Asking questions candidates actually enjoy
Interviews can go sideways – either candidates feel like they’ve been part of a scripted exercise, where standard questions that don’t engender creativity or imagination are rolled out one by one; or, if the interviewer is underprepared, questions can appear out of the blue and feel largely irrelevant to the role.
But certain questions break the mould—they encourage authenticity, spark reflection, and sometimes even pride. Rather than prompting canned responses, these questions invite candidates to share real experiences that shaped them. After analysing feedback from thousands of candidates, here are the five most-loved interview questions and why they matter.
- Making a Difference
“Tell us about a time you went out of your way to make a difference for someone and improved their day.”
Why candidates love it: It’s a chance to talk about something positive they’ve done. People enjoy reflecting on moments that mattered, whether big or small, and this question lets them share proud memories. For the hiring team, it reveals a candidate’s potential to bring kindness, positivity, and empathy to your team and customers.
- Handling Difficult People
“Have you ever dealt with someone difficult? How did you handle the situation? Feel free to share examples from work, school, or any group activity.”
Why candidates love it: We’ve all had tough encounters, and this question lets candidates share how they navigated those situations. Their response can reveal resilience, tact, or empathy. Plus, every workplace has its challenges—this question lets them show their approach to handling them.
- Driving Change
“Tell us how you have been proactive in driving change that had a lasting impact.”
Why candidates love it: Everyone has had moments when they took initiative, big or small. This question gives candidates a chance to reflect on those times when they went beyond the status quo and made a real difference. It also reveals whether they see themselves as someone who can step up to make things better.
- Missing Deadlines
“Describe a time when you missed a deadline or personal commitment. How did that make you feel?”
Why candidates love it: This question is refreshingly human. We’ve all missed deadlines, and this question creates space for honesty, vulnerability, and growth – without the awkwardness of the classic “what are your weaknesses?” angle. It’s less about the setback itself and more about how a candidate understands, reflects and moves forward from it.
- Team Support
“Tell us about a time when you rolled up your sleeves to help out your team or someone else.”
Why candidates love it: This question highlights the power of teamwork. Candidates get to share the moments they stepped up and supported others. It shows both teamwork and leadership potential, indicating if this candidate is someone who’ll contribute something bigger than their individual tasks.
Why these questions are impactful
These interview questions tap into values that are universally meaningful. Candidates don’t just want to list their skills; they want to share stories that matter to them. When you ask questions like these, you’re inviting candidates to reflect on personal moments of challenge, motivation, and connection. They get to walk away feeling heard and appreciated – before they’ve even received a job offer.
Interviews, whether face to face or via chat, should be a positive experience for candidates. They’re a chance to connect with the person behind the application. That’s why we built our online assessment Chat Interview on a foundation of questions like these. So the first experience a candidate has with your brand is one of genuine connection.
Why you should consider questions like these in your interviews
Incorporating these questions shows candidates that you value their unique experiences. By making small adjustments to the questions you ask, you create a space where candidats can open up and share more meaningful responses. And that’s the first step in finding candidates who genuinely fit with your team and culture. Shifting to questions that candidates love can elevate your interview process, leaving candidates feeling inspired and excited about the prospect of working with you.
Transforming Interviews, One Question at a Time
This research underscores a core belief we hold: Interviews are an experience, not just an assessment. A good interview reveals job-related skills while also building trust and creating advocates for your brand.
At Sapia.ai, we know interviewing. Whether that’s giving your candidates an engaging interview over chat as their first experience with your brand; or enabling your team to conduct better live interviews, our platform enhances the end to end volume hiring process.
We’re proud to champion a new way of interviewing that prioritises candidate experience and genuine connection. After all, when candidates feel good about the questions you ask, they’re more likely to bring their best selves – helping you find the people that belong with your brand..
Curious to learn more? Get in touch to see how we’re reshaping hiring into a more human, meaningful experience – one great question at a time.
Related
Blog
New Research Proves the Value of AI Hiring
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.
The problem with traditional psychometric tests
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.
The Rise of Chat-Based Interviews
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.
Key Findings from the Latest Research
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.
Why Trust and Candidate Agency Win
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.
Blog
AI Maturity in the Enterprise
Barb Hyman, CEO & Founder, Sapia.ai
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.
You don’t need more pilots. You need a maturity model.
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:
The 5 Stages of AI Maturity (for real enterprises)
- Curious
- Awareness is growing across leadership
- Experimentation led by innovation teams
- Risk is unclear, appetite is cautious
- AI is seen as “tech”
- Reactive
- Gen AI introduced via vendors or tools (e.g., copilots, agents)
- Some pilots show promise, but with limited scale or guardrails
- Data privacy and sovereignty questions begin to surface
- Risk is siloed in legal/IT
- Capable
- Clear policies on privacy, bias, and governance
- Dedicated AI leads or councils exist
- Internal use cases scale (e.g., summarisation, scoring, chat)
- LLMs integrated with guardrails, safety reviewed
- Strategic
- AI embedded in workflows, not layered on
- LLM/data infrastructure is regionally compliant
- AI outcomes measured (accuracy, equity, productivity)
- Teams restructured around AI capability — not just tech enablement
- AI-Native
- AI informs and transforms core decisions (hiring, pricing, customer service)
- Enterprise builds proprietary intelligence
- FAIR™/RAI principles deeply operationalised
- Talent, systems, and leadership are aligned around an intelligent operating model
Why this matters for enterprise leaders
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.
Blog
Beyond the Black Box: Why Transparency in AI Hiring Matters More Than Ever
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.”
Metrics That Make Transparency Real (and Actionable)
🕒 Time to Hire
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.
💬 Candidate Sentiment, Advocacy & Verbatim Feedback
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.
🔍 Drop-Off Rates, Funnel Visibility & Automation That Works
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.
📈 Hiring Yield (Hired / Applied)
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.
🧠 AI Effectiveness: Score Distribution & Answer Originality
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.
From Metrics to Momentum
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.