To find out how to use Recruitment Automation to hire faster, reduce bias and save, we also have a great retail industry eBook on Ai in HR.
AI RECRUITMENT TOOLS
Artificial Intelligence. AI recruitment tools. Machine learning. Conversational AI recruiting. Chatbots.
Artificial Intelligence (AI) and AI recruitment tools are no longer just buzzwords in the realm of HR. Machine learning and chatbots, especially in the realm of conversational AI recruiting, are reshaping many industries, including HR.
While the possibilities of technology always felt like some distant future, there’s no denying that AI’s impact on recruiting within HR is evident now. Every day, technology touches and enhances our lives in ways we rarely even pause to think about. Machine learning recruitment tools, algorithms, apps, and digital automation continue to redefine how we shop, connect, bank, and more, including how HR departments operate.
It’s changed the ways we access customer services and the ways we can connect with our tribes across social platforms. In the age of COVID-19, AI-powered recruitment tools have even enabled ways of efficient remote working that few thought could be possible, proving to be a game-changer for HR professionals. AI in HR is not just about automating tasks; it’s about enhancing the human experience, making recruitment processes more efficient, and enabling a more connected and adaptive workforce.
Recruitment and Ai – We’ve only just begun
With the rise of automation and artificial intelligence (AI) across every industry sector, how AI is changing the game for recruiting is evident. AI recruitment tools are now rapidly reshaping the essential functions of hiring. These tools serve 3 key functions in the hiring process: sourcing, screening, and interviewing of candidates. Employing the latest advances in AI-powered recruitment, machine learning, and big data practices is delivering new efficiencies and better outcomes for businesses, recruiters, and candidates alike.
Text and chat interview automation with conversational AI recruiting
Conversational AI recruiting is a type of Ai that lets businesses have dynamic and meaningful conversations at scale with customers, staff, business partners and candidates.
Conversational Ai uses Natural Language Processing (NLP), a sub-field of Ai that’s focused on enabling computers to understand and process human languages. Through machine learning recruitment, it aims to get computers closer to a human level of understanding of language.
Conversational Ai uses NLP to discern meaning from both written and spoken word:
- Voice-activated systems – NLP is used in digital assistants you’re probably familiar with: Siri on iPhone, Google Home or Amazon Alexa, for example. These follow instructions to play music, to control connected devices throughout the home, find web-based information and resources and more. On an enterprise-level, you’ll be familiar with voice-driven customer service over the phone.
- Text driven systems – online or on mobiles, chat text discerns meaning in the written word.
How conversational AI recruiting tools are changing the recruitment conversation
Sometimes referred to as chatbots or textbots, Ai-based conversational tools, part of the suite of AI recruitment tools, continue to evolve and be applied in new and extraordinary ways. Our own peer-reviewed research shows how personality traits can be accurately inferred from answers to standard interview questions captured via a text chat.
AI recruitment works best in high volume recruitment such as customer-facing retail or service team roles. Conversational AI recruiting can be helpful for profiling personalities in candidates or existing employees without the time and costs of conducting lengthy psychometric profiling.
Conversational Ai can be helpful for profiling personalities in candidates or existing employees without the time and costs of conducting lengthy psychometric profiling. Add video into the mix and machine learning can add additional layers of meaning through analysis of facial expressions and profiles, body language and more.
Video interviewing continues to divide opinion as many believe it allows for unconscious (or not so unconscious) bias to remain front and centre of the hiring process. In text-based Ai interviews, many of the usual bias cues or triggers an be effectively eliminated at the candidate screening stage.
Automated interviews support remote working and remote hiring
In a post-COVID or COVID-normal economy, AI-powered recruitment tools will be pivotal. As more people compete for potentially fewer jobs, finding and engaging the best candidates will be even more challenging.
Ai-powered interviews can help recruiters cast their net wider to reach a bigger pool of candidates and find better-qualified candidates.
Mobile-first puts the power in candidates’ hands
People know text and are comfortable with text. So by providing a text chat-based mobile-first experience for candidates, improves the user experience and addresses communication challenges.
Chat-text provides an easier and less confronting interview process for many candidates.
Everyone has a story that’s bigger than their CV and Ai recruitment interviews give every candidate an opportunity to tell theirs. Candidates can choose when and where they complete their interview and standardised interview questions ensure a level playing field for all candidates.
Sapia’s text chat interview automation is blind screening at its best. We’ve removed possible factors that can influence human bias – no CVs, no socials, no videos, no facial recognition and no time limit. It’s just the candidate and their text answers, providing a fairer and richer experience where candidates feel comfortable just being themselves.
Recommender systems – How AI recruitment tools support people making people decisions
One of the most well-known applications of Ai, data science and machine learning recruitment is Recommender systems or Recommender engines.
In hiring, Recommender Systems use predictive modelling to recommend the most-likely best matches of applicants for a role.
Recommender systems guide decision-making by using machine learning to analyse all the data available through the HR lifecycle. From job advertising and clicks, through interviewing and hiring, to employees’ job satisfaction and tenure, data can be analysed to reveal predictive patterns and insights.
Data can find connections that humans don’t, providing valuable insight into what an ideal candidate looks like or where you’re likely to find them.
Predictive intelligence draws a picture of your ideal candidate
Recommender systems can cut through the ‘noise’ by providing a shortlist of top-ranked candidates. This is without burning time, sorting and reviewing potentially hundreds or even thousands of applications. Predictive intelligence shares additional insights on candidates’ values, traits, personality and communication skills. It helps to simplify the selection and guide faster talent decisions.
Machine learning is not infallible. One important consideration is questioning whether the data being used in machine learning recruitment is not inherently biased. It’s always important to have real people making decisions about people.
Interviews – it’s not where you finish, it’s where you start
Reviewing CVs of all candidates can be the most time-consuming part of a recruiter’s job. Especially for large-scale briefs such as retail or customer service teams. In defining a shortlist of potential candidates to proceed to the interview stage it can be hard to differentiate between CVs. It’s also easy to make decisions that may be based on personal biases.
But what if you could start the hiring process with all the benefits of an interview process, without investing your time in them? And what if in the time it would take to properly review just a handful of CVs, thousands of candidates could be screened by interview?
With Ai recruitment tools you can.
Five top ways conversational Ai tools are changing the recruitment game
When it comes to recruiting and hiring, the ability to read the mood as well as the words is a game-changer in candidate assessment. Here are our top five benefits for your business:
1.Reducing time to hire, improving the quality of candidates with AI-powered recruitment.
Without even having to consider CVs upfront, an upfront screening interview reduces time to hire by providing a shortlist of candidates with the best fit to move forward.
Ai interview automation looks beyond the CV to assess the skills, traits and temperament of candidates. Based on past hires, Ai learns what a successful candidate for your business looks like and joins the dots to find others that match that profile.
Recruiters and hirers can save time reviewing and assessing CVs. With the ability to complete briefs faster, build teams sooner and achieve business metrics, you can be on to the next job sooner. Or free yourself to concentrate on what you do best: building relationships, delivering a better hiring experience or enhancing the onboarding process.
2. Reduce bias & build diversity
Ai-enabled interviewing helps reduce the effects of unconscious bias – the inherently human prejudices, personal preferences, beliefs and world-views that shape our assessment of others. Our biases can easily have a negative impact on candidates and mean you’re potentially missing out on the best candidates for the job. It can also mean employers are missing the opportunity to cultivate workplace diversity and all the benefits it delivers.
Diversity improves employee productivity, retention and happiness. Time and again, research shows that diversity – of background, gender, experience and more – improves employee productivity, tenure and job satisfaction. In 2020, global management consulting company McKinsey confirmed that “The most diverse companies are now more likely than ever to outperform non-diverse companies on profitability”.
3. Cut costs of every hire
Companies that have automated part of their candidate screening and interviewing are not only reaping the benefits of a more streamlined and stress-free process but report an immediate pay-off in time and efficiency savings.
Get your time back quickly and reallocate budgets towards higher-value investments and automation in other areas of recruiting.
Calculate your RoI on interview automation
Use Sapia’s free calculator to:
- Calculate your costs of hiring
- Calculate the costs of your annual turnover
- See the financial benefits of using automation for hiring
- Avoid unnecessary revenue losses
4. Increase the productivity of every recruiter and hirer
Everyone has one part of their job that they could do better if they had more time. Like managing stakeholders. Improving business partnership skills. Or networking to improve talent pools with a focus on those high-end and hard-to-fill roles. Whatever yours might be, interview automation can give you back time to focus on high-value tasks.
Reviewing CVs and managing interviews might not be the biggest challenge in your role, but they are likely to be the most time-consuming. Automate those upfront interviews using the tools and process of Ai recruitment and you can focus on the bigger picture of finding the best fit for every role and meeting every brief with confidence.
5. Give candidates a better experience
While this one’s last on our list of the benefits of Ai interview automation, it could equally be the most important.
Ever since job boards hit the market, recruiters have been inundated with candidate applications. While that’s been good news for potential employers as well as recruiters, it’s not so good for candidates. Too often candidates make the effort to apply for a position, but then due to the sheer volume of applications they never hear a thing from the recruiter or hirer. It’s called “ghosting” for obvious reasons.
Ghosting is not just a bad look, it can be bad for business. Candidates can easily share a negative experience on social media. They may also be less inclined to apply again or accept a job offer now or in the future.
With interview automation, you can turn every candidate engagement into an efficient, empowering and enjoyable experience.
About Sapia
Sapia’s award-winning interview automation offers a mobile-first, text chat interview. At scale, it delivers an engaging and relatable, in-depth interview, followed up with personalised feedback for every candidate. Here’s how Ai automation provides a superior experience to a traditional interview process:
- A familiar and accessible, mobile-first text experience
- No confronting questions or videos
- Candidates can be themselves, completing questions related to role attributes where and when it suits
- Blind-screening at its best with no gender, age or ethnicity revealed
- Candidates are motivated by personalised feedback, insights and coaching tips… and the opportunity to provide their feedback on the process
Find out more about Sapia’s Ai-powered recruitment tool and how we can support your recruitment needs today.
You can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo
Related
Blog
Humanising hiring: the largest study of AI candidate experience ever
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.
The largest research study of its kind
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.
The findings are bold and unprecedented
- 9.05/10 average candidate satisfaction across all groups and industries
- 81.8% of candidates left written feedback — engagement at this scale has never been seen before in hiring research
- 8 in 10 candidates would recommend an employer just because of the interview
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30% more women apply when told AI will assess them, resulting in a 36% closure of the gender gap
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98% hiring equity for people with disabilities through a blind, untimed, mobile-first interview design
Candidate voices
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.”
Expert validation
“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
Proof that AI can be human
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:
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Every candidate gets the same structured, role-relevant questions.
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Interviews are untimed, so candidates can answer at their own pace.
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Bias is monitored continuously under our FAIR™ framework.
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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.
Why it matters now
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.
Download the report
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.
Blog
What’s More Ethical: Measuring Skills or Guessing Them?
Barb Hyman, CEO & Founder, Sapia.ai
Why skills data matters for HR and CHROs
Every CHRO I speak to wants clarity on skills:
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What skills do we have today?
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What skills do we need tomorrow?
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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.
Two very different approaches to skills analysis
1. Skills inference from digital traces
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.
2. Skills measurement through structured conversations
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.
The risks of skills inference HR leaders must confront
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Surveillance and trust: Do your people know their digital trails are being mined? What happens when they find out?
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Bias: Who writes more Slack updates, introverts or extroverts? Who logs more Jira tickets, engineers or managers? Behaviour is not the same as skills.
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Explainability: If an algorithm says, “You are good at negotiation” because you sent lots of emails, how can you validate that?
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Agency: If a system builds a skills profile without consent, do employees have control over their own career data?
A more human approach: skills measurement
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.
Questions every HR and CHRO should ask
When evaluating skills solutions, ask:
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Is this system measuring real skills, or only inferring them from proxies?
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Would I be comfortable if employees knew exactly how their skills profile was created?
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Does this process give people agency over their data, or take it away?
The real test of ethics in the skills-based organisation
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.
FAQs
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
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.