We’ve relied on interviews for centuries. They are an important step in the selection process.
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.
With interview automation, interviews are at the
start of your recruiting process – not midway through it.
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.
Okay, so here are the 6 reasons to start your recruiting process with interviews
You can try out Sapia’s FirstInterview experience here.
1. You will reduce your time to hire
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.
2. You will improve the overall quality of hires
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.
3. You will reduce bias and improve diversity
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.
The problem is that humans are inherently biased.
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.
Ai is far less bias than humans.
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.
4. You will reduce the cost of each hire
Those who have already automated their interviews have reallocated that spend toward higher-value investments.
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.
The real game-changer is that interview automation can also help you solve a churn problem.
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.
5. You will increase the productivity of every recruiter
What’s the toughest part of your job as a Recruiter? If you had more time, could you do that part better?
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.
We cannot discuss productivity without also giving mention to structured interviews.
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.
6. You will boost candidate experience (beyond imagination)
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.
If your mission is to provide the best experience possible to your candidates, interview automation should not be ignored.
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:
- Utterly relatable – An accessible, mobile-first ‘familiar’ text experience that candidates enjoy with no confronting videos or questionnaires. Questions are related directly to role attributes.
- Totally convenient – Completing it anywhere, anytime and in your own time with an untimed interview – giving candidates the space to be themselves.
- Wholeheartedly fair – Everyone gets an interview levelling the playing field for all. It’s blind screening at its best – no gender, age or ethnicity revealed.
- Unbelievably motivating – Following their FirstInterview all candidates receive an email with personalised insights. It’s delightfully surprising to receive something of such great value.
- Surprisingly beneficial – Candidates receive coaching tips that help them with their career, transforming the experience.
- Highly open – Candidate experience improves by 148% when candidates are asked for interview feedback. That’s why after their FirstInterview all candidates can rate their experience and give their input.
Interviewing automation enhances candidate experience, with no further time investment from you.
Download the 2020 Candidate Experience Playbook here
Taking the first step on automating your interviews: start with volume roles first.
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.
Read the Ultimate Guide to Interview Automation>
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Have you seen the 2020 Candidate Experience Playbook?
If there was ever a time for our profession to show humanity for the thousands that are looking for work, that time is now.
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Blog
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 👇