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
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Reinventing the Competency Framework: A Data-Driven Approach for the AI Era
We can’t hide from reality anymore. Talent needs are shifting overnight, and AI is redefining what it means to work. Traditional talent frameworks are no longer fit for purpose. At Sapia.ai, we believe the future of talent strategy lies in a smarter, fairer, and more adaptive way of defining what great looks like.
Our AI hiring platform is built on the largest proprietary dataset of interview answers globally – we’re a data company at heart, and we’ve seen the power of data-driven people methodology in transforming how organisations hire and retain good talent.
So, when it came to building a new Competency Framework that could be leveraged globally for hiring for any role at any scale, of course, we used a ground-up, data-led methodology that bridges the gap between organisational psychology and AI.
Why Rethink Competency Frameworks?
Conventional frameworks are typically crafted through expert interviews and focus groups. While valuable, they tend to be subjective, static, and too slow to keep pace with evolving job demands. As roles become more fluid and technology augments or replaces task-based skills, organisations need a new way to understand the human capabilities that genuinely matter for performance.
We wanted to identify enduring, job-agnostic competencies that reflect what drives success in a modern workplace – capabilities like adaptability, resilience, learning agility, and customer orientation.
(Why competencies and not just skills? Read why here.)
Our Approach: Where AI Meets I/O Psychology
Sapia.ai’s methodology is rooted in the science of human behaviour but powered by cutting-edge AI. We asked two core questions:
- Can we make competency discovery agile, scalable, and evidence-based?
- Can we use AI to automate the process without losing the rigour of traditional psychology?
The answer to both: yes.
We began with a rich dataset of over 37,000 job descriptions across industries and role types. Using large language models (LLMs) and advanced NLP techniques, we extracted over 200,000 behavioural descriptors. These were distilled down through a four-step process:
- Behavioural Descriptor Extraction
- Clustering and Labeling
- Cluster Analysis by I/O Psychologists
- Thematic Categorisation and Definition of Competencies
This resulted in a refined list of 25 human-centric competencies, each with clear behavioural indicators and practical relevance across a wide range of roles.
Built to Scale. Built to Adapt.
Our framework is intelligent, but importantly, it’s adaptive. Organisations can apply this methodology to their own job descriptions to discover custom competencies. This bottom-up, role-data-led approach ensures alignment to real work, not just theoretical models.
And because the framework integrates directly with our AI-powered hiring tools, you get a connected system that brings your talent strategy to life.
Our framework comes to life in the following tools:
- Job Analyser – Starting with a job description, it creates a unique competency profile for each role to build tailored structured interviews in seconds.
- Structured Chat-based Interviews that assess candidates’ responses according to the competency profile for consistent candidate assessment.
- Talent Insights Reports from every interview with deep reasoning and explainability for fair and objective hiring decisions.
- Phai Career Coach for internal mobility and employee growth that considers their competency strengths and career aspirations.
The Future of Talent Acquisition & Development is Competency-First
Skills alone cannot predict success. Competencies do. As AI continues transforming how we work, Sapia.ai’s Competency Framework offers a scalable, scientific, and fair foundation for hiring and developing the talent of tomorrow.
Want to see how it works? Download the full framework.
Blog
It’s Time to Stop Hiring for Skills, and Start Hiring for Competencies
If you’re a CHRO or Head of Recruitment at an enterprise today, chances are you’ve been inundated with messages about the importance of “skills-based hiring.” LinkedIn’s recent Work Change Report (2025) is full of compelling data: a 140% increase in the rate at which professionals are adding new skills to their profiles since 2022, and a projection that by 2030, 70% of the skills used in most jobs today will have changed.
This is essential reading. But there’s a missed opportunity: the singular focus on “skills” fails to acknowledge the real metric that talent leaders need to be using to future-proof their workforce — competencies.
Skills vs Competencies: The Crucial Distinction
- Skills are task-specific capabilities. Think Python programming, Excel, or even negotiation.
- Soft skills refer to interpersonal or behavioural qualities like adaptability, communication, and resilience.
But skills on their own — even soft ones — are generic, disjointed, and often disconnected from real-world performance. In contrast:
- Competencies are clusters of skills, knowledge, behaviours and abilities that are observable, measurable, and context-specific.
Put simply, competencies answer the all-important question: Can this person apply the right skills, in the right way, at the right time, to deliver results in our environment?
Why Competencies Matter More Than Ever
The Work Change Report outlines a future where job titles are fluid, roles evolve quickly, and AI is a constant disruptor. This creates three massive challenges for hiring at scale:
- Roles are changing faster than static skill frameworks can keep up
- Job candidates may have non-linear, cross-functional backgrounds
- The shelf-life of technical skills is shrinking rapidly
Skills alone don’t tell us whether someone can succeed in a role that will look different 12 months from now. But competencies can. Because they measure not just what a person knows, but how they apply it.
Adaptive Talent: The New Competitive Advantage
The LinkedIn report highlights a critical insight: organisations now prioritise agility in entry-level hiring. And there’s a good reason for that. With professionals expected to hold twice as many jobs over their careers compared to 15 years ago, adaptability is not just a nice-to-have. It’s core to success.
But you can’t measure agility with a keyword on a CV. You measure it by looking at competencies like:
- Learning agility
- Change resilience
- Cross-functional collaboration
- Problem-solving in ambiguous contexts
When you shift the focus away from skills to behavioural competencies that can be defined, observed, and assessed in structured ways, you open yourself up to a much more dynamic and more useful way of managing talent.
Building a Competency-Based Talent Framework
To hire effectively at scale, particularly in a technology-driven world of work, talent leaders must shift their lens:
- Define Role-Specific Competencies: Move beyond job descriptions based on qualifications or vague skill sets. Break roles down into measurable competencies that reflect current and emerging performance expectations. This step is crucial for organisations to be able to accurately assess role-fit in the next stages. Sapia.ai does this automatically, taking job descriptions and building role-specific competency models in seconds.
- Assess Competencies Fairly and Objectively: Use structured behavioural interviews, ideally at scale. These provide a much more accurate picture of a candidate’s readiness than self-reported skills or credentials. Sapia.ai’s AI powered interviews enable competency assessment, at scale.
- Build Pathways for Development and Internal Mobility: A competency framework makes it easier to identify transferable strengths, development gaps, and future-fit potential. It gives employees clarity on how to grow within the business. Using an AI-powered coach can help ensure that talent is being continuously developed against the organisation’s competency framework.
The Future of Work Requires Depth, Not Just Breadth
LinkedIn’s data shows that people are learning more skills more quickly than ever. But the real question for talent leaders like you is: Are those skills being applied in ways that drive value? Are we hiring for task proficiency or performance?
The truth is that the organisations that will thrive in an AI-driven, skills-fluid economy aren’t the ones chasing the next hot skill. They’re the ones designing systems to identify, develop and scale competence.
Keen to Shift to Competencies, but Lacking a Framework?
Sapia.ai has developed a comprehensive Competency Framework using a data-driven approach. Download the full paper here.
Blog
The AGC Debate: Are AI-Written Interview Answers a Red Flag or Smart Strategy?
Every day, we read stories of increased fake or AI-assisted applications. Tools like LazyApply are just one of many flooding the market, driving up applicant volumes to never-before-seen levels.
As an overwhelmed hiring function, how do you find the needle in the haystack without using an army of recruiters to filter through the maze?
At Sapia.ai, we help global enterprises do just that. Many of the world’s most trusted brands, such as Qantas Group, have relied on our hiring platform as a co-pilot for better hiring since 2020.
Our Chat Interview has given millions of candidates a voice they wouldn’t have had – enabling them to share in their own words why they’re the best fit for the role. To find the people who belong with their brands, our customers must trust that their candidates represent themselves. Thus, they want to trust that our AI is analysing real human answers—not answers from a machine.
The Rise of GPT
When ChatGPT went viral in November 2022, we immediately adopted a defensive strategy. We had long been flagging plagiarised candidate responses, but then, we needed to act fast to flag responses using artificially generated content (‘AGC’).
Many companies were in the same position, but Sapia.ai was the only company with a large proprietary data set of interview answers that pre-dated GPT and similar tools: 2.5 billion words written by real humans.
That data enabled us to build a world-first:- an LLM-based AGC detector for text-based interviews, recently upgraded to v2.0 with 99% accuracy and a false positive rate of 1%. An NLP classification model built on Sapia.ai proprietary data that operates across all Sapia.ai chat interviews.
Full Transparency with Candidates
Because we value candidate trust as much as customer trust, we wanted to be transparent with candidates about our ability to detect artificially generated content (AGC). As an LLM, we could identify AGC in real time and warn candidates that we had detected it.
This has had a powerful impact on candidate behaviour. Since our AGC detector went live, we have seen that the real-time flagging acts as a real-time disincentive to use tools like ChatGPT to generate interview responses.
The detector generates a warning if 3 or more answers are flagged as having artificially generated content. The Sapia.ai Chat Interview uses 5 open-ended interview questions for volume hiring roles, such as retail, contact centre, and customer service, and 6 questions for professional roles, such as engineers, data scientists, graduates, etc.
Let’s Take a Closer Look at the Data…
We see that using our AGC detector LLM to communicate live with candidates in the interview flow when artificial content has been detected has a positive effect on deterring candidates from using AI tools to generate their answers.
The rate of AGC use declines from 1 question flagged to 5 questions – raising the flag on one question is generally enough to deter candidates from trying again.
The graph below shows the number of candidates, from a total of almost 2.7m, that used artificially generated content in their answers.
Differences in AGC Usage Rate by Groups
We see no meaningful differences in candidate behaviour based on the job they are applying for or based on geography.
However, we have found differences by gender and ethnicity – for example, men use artificially generated content more than women. The graph below shows the overall completion ratios by gender – for all interviews on the left and for interviews where the number of questions with AGC detected is 5 or more on the right.
Perception of Artificially Generated Content by Hirers.
We’re curious to understand how hirers perceive the use of these tools to assist candidates in a written interview. The creation of the detector was based on the majority of Sapia.ai customers wanting transparency & explainability around the use of these tools by candidates, often because they want to ensure that candidates are using their own words to complete their interviews and they want to avoid wasting time progressing candidates who are not as capable as their chat interview suggests.
However, some of our customers feel that it’s a positive reflection of the candidate, showing that they are using the tools available to them to put their best foot forward.
It’s a mix of perspectives.
Our detector labels it as the use of artificially generated content. It’s up to our customers how they use that information in their decision-making processes.
This concept of having a human in the loop is one of the key dimensions of ethical AI, and we ensure that it is used in every AI-related hiring product we build.
Interested in the science behind it all? Download our published research on developing the AGC detector 👇