In recent years, a flood of pre-employment talent assessment tools has come into the market.
From automating initial candidate interviews to conducting online skills or personality testing, these tools help recruiters look beyond the CV to find the best candidates for every job.
In today’s competitive world of work, recruiters and hiring managers want to be sure that every decision is the right decision. As competition between companies for the very best talent has increased and as more candidates apply for fewer roles, just filling a role is no longer an option. Reviewing CVs and assessing candidates is time-consuming and costly, and recruiters need to be confident that they are delivering value to their clients in both costs and the quality of candidates.
That’s why recruiters and employers alike are seeking ways to take the guesswork out of the process in identifying talent who will be the best fit for the team, work most productively and stay in the role longer.
In this guide, Sapia explores the types of tools available, the insights they can provide and how they can benefit your business. We’ll also provide some guidelines for helping you to assess which tools could deliver the best return on your investment.
Why use talent assessment tools?
Pre-employment assessment of candidates is, of course, the very reason that recruiters exist.
Talent assessment tools have been developed to help make that process easier, faster and more cost-effective. The tools leverage technology to more accurately identify the best talent for a role and predict their fit and performance in that organisation.
The benefits of candidate evaluation software can include:
- Go beyond the CV – Leverage technology to focus on skills as well as things such as cultural fit, aptitude, cognitive abilities and more to identify candidates “most likely” to be successful.
- Increase productivity – Spend less time on manual screening and more time on higher-value briefs and candidates.
- Decrease costs – Automated processes can reduce the costs of manual talent review and assessment, dramatically reducing overall hiring costs. Redirect savings to investments in people or technology.
- Remove bias from the process – Data-driven tools can take unconscious bias out of the assessment equation to focus on skills and fit. Sapia’s Ai-enabled text interview automation platform, for example, offers blind screening at its best to help build workplace diversity.
- Build deeper talent pools – Use technology to extend your reach to more candidates. The best tools integrate with your applicant tracking system to seamlessly run hiring processes and build ‘ready to go’ talent capabilities.
- Fill roles faster – With the ability to screen more candidates in less time you can confidently begin interviewing sooner.
- Be successful – With the right talent assessment tools working for your business, you are more likely to achieve the best talent outcomes every time.
- Improve the candidate experience – Provide an engaging and enjoyable experience for candidates. Some tools including Sapia’s platform automate personalised feedback that is always appreciated by candidates.
- Know what candidates want – Using data to understand candidates, their motivations and their expectations can help managers be better prepared for onboarding. Building profiles of successful candidates will also provide insight for the next similar brief.
- Make hiring decisions with confidence – Objective evidence and data-driven findings can help make every decision a better decision.
Types of talent assessment tools
The wide range of available talent assessment tools can be generally grouped into three areas of assessment: Work behaviours; Knowledge, skills and experience; Innate abilities and attributes.
Some tools may focus on a single attribute such as coding abilities or English competency while others can combine a range of tests and interview capabilities within one platform.
Once the requirements of a role are understood, the right tools can be chosen to assess those competencies.
1. Learnt knowledge, skills and experience assessments look at candidates’ specific job knowledge, qualifications and work experience. Assessed against the agreed capabilities required for the role, these assessments can be an extremely accurate and effective predictor of a candidate’s performance in the role. Some tools may focus on specific sectors and roles – eg sales, HR, health, hospitality, programming, engineering – while other platforms will cover a range of these with tests that can be customised to specific requirements
Some examples:
- Job knowledge assessments: This type of test measures specific areas of knowledge or skills – often technical – that are considered minimum requirements for a role.
- Skills assessments: Through mobile-driven text conversations, video interviews, multiple-choice quizzes or even online ‘games’, job-specific and general work skills or soft skills can be assessed.
- Coding assessments: There are many tools designed specifically to test and assess candidates’ coding abilities and technical skills. These assessments can be used at the screening stage to filter candidates or during later interview stages where full-scale coding challenges could reflect actual work or challenges the candidate would encounter as an employee. Tools can be a platform and industry-specific.
- General skills: Tools can also address general work skills such as literacy and numeracy, basic typing and data entry, ability to follow instructions, and more.
- Work behaviour assessments: observe actual behaviours and simulations that match and help predict real on-the-job requirements. Job simulation exercises and work sample tests give candidates an opportunity to demonstrate their abilities and skills. They allow employers to assess job-specific skills and analyse candidates’ capabilities in decision-making and prioritising, multi-tasking or their ability to work under pressure. Tasks can be highly customised to specific responsibilities of the role and of the organisation.
2. Innate abilities and attributes assessments focus on traits that are not job-specific such as personality, interests and cognitive abilities including problem-solving, logic skills, reading comprehension and learning ability. These universal human traits have proven to be effective indicators of job performance and cultural fit. Softskill testing: Tools can be used for talent evaluation across a range of qualities and personality traits such as teamwork, sales ability, good judgement, integrity, curiosity, impact, ownership and independence.
Some examples:
- Automated Interviews: AI-driven platforms can automate interview processes and provide a better experience for recruiters, hirers and candidates alike. Platforms like Sapia’s automated text interview can provide a true advantage, especially at the screening stage for large volume recruitment briefs such as customer-facing retail or service teams.
- Candidate ranking: Powered by artificial intelligence and machine learning, many assessment tools will analyse results to grade and rank candidates. Rankings around different criteria can save time and provide the confidence that you are focused on the right candidates.
- Cognitive screening: These tools provide insight into how candidates think, solve problems and learn. Insights can help hirers understand future management needs to prepare and support new employees to be successful in their role.
- Integrity assessments: Assessing attitudes and experiences relating to honesty, reliability and trust.
- Psychographic screening: Insights into a candidate’s personality, values and interests can help assess their fit within a team and within an organisation’s culture and values.
- Bias-free screening: Unconscious bias removed from the process so candidates are assessed on their skills and decisions are not influenced by a candidate’s gender, age, ethnicity and other personal credentials that do not affect their ability to do the job. Sapia’s mobile-first, text interview platform is an industry leader in blind interviewing.
10 questions to help you choose the best talent assessment tools
Saving time and money, filling roles with better quality candidates. That’s the key reason talent assessment tools are indispensable across the recruitment industry and in every employment sector. But with the plethora of tools available, how do you decide which ones are right for your organisation? Which talent assessment tools will best contribute to your success?
Before you invest, Sapia’s talent assessment tool checklist can help:
1) What do you need to know?
As an experienced recruiter, you can probably already recognise where your talent assessments sometimes fall short or you think they could be better. The data insight that can support your recruitment and hiring processes will be different for everyone and will vary according to:
- industry or sector specialisation
- experience level of candidates – entry-level to management and C-suite roles
- qualifications, skills or personality traits required for roles
- nature of brief– specialist technical roles or large volume team roles
When you know what you need to measure, you can start narrowing your search to identify the tools that can give you what you’re looking for.
2) How will the findings be presented?
Consider the format and depth of the feedback that different tools can provide. Is a numerical ranking of candidates sufficient or will in-depth analysis, comparisons and recommendations better serve your needs?
3) Do assessments support the hiring organisation’s brand values and strategy?
Consider whether the tools positively support an organisation’s employment policies and practices such as workplace diversity and inclusion, language or numeric competencies and minimum skills requirements.
4) Do tools remove bias from talent assessment?
Removing unconscious bias from the talent assessment process is a priority for organisations looking to improve workplace diversity and inclusion. While a text-based chat platform (such as Sapia) can effectively take bias out of the equation, video submissions bring the opportunity for bias front and centre of the process.
5) Do the tools support the interview process?
Few, if any, hiring decisions should ever be made solely on the basis of talent assessment tools rankings or findings. Make sure tools can provide meaningful data that will enhance the interview process. Many tools will help identify areas that should be explored further in the interview process and even suggest questions to help shape the interview.
6) How will the tool integrate with existing systems?
The best tools will integrate with your existing systems and processes and with other tools. You want to be sure that you can combine data from different tools to create meaningful reports and records. Tools that integrate with your existing ATS (Applicant Tracking System) are likely to deliver the best savings in time and effort.
7) What will candidates think?
Every candidate deserves a fair and positive experience, whether they are successful or not. Choose tools that are easy and engaging to use, appropriate for the role and tools that will enhance, not undermine, your employer brand.
The best tools also deliver value by allowing candidates to provide feedback on their engagement with tools after the assessment process.
https://sapia.ai/blog/predictivehire-is-named-candidate-experience-solution-of-the-year/
8) How do I find out what tools are best?
Ask your industry colleagues for recommendations and search the web for reviews and guides like this one that can help you navigate a very crowded market. When you think you’ve found the tools that will work best for you, your clients and your candidates, ask vendors to show you how their assessment tools can deliver with a personal demonstration or even a free trial.
9) Have you analysed the costs?
You want to be sure that your investment will pay its way. Take the time to consider the value of the candidate feedback or assessment of different tools will provide. Many vendors provide online calculators to help you estimate the return on your investment.
10) Do the tools support best practice?
Talent assessment tools can provide objective, measurable insights that other more traditional recruitment methods can’t provide. But technology has its limits too. Make sure that a positive candidate experience remains a priority – nobody wants to feel discriminated against or feel embarrassed or violated by intrusive personality testing.
Make sure also that in focusing on one key skill or trait, you’re not missing a candidate’s true strengths. In short, don’t use your talent assessment tools as the recruitment tool, use them in conjunction with all the other methods, tools and skills in your recruitment toolbox.
The Buyers Guide to Navigating Ai Hiring Solutions
Leveraging objective data to augment decisions like who to hire and who to promote is critical if you are looking to minimise unconscious preferences and biases, which can surface even when those responsible have the best of intentions.
The greatest algorithm on earth is the one inside of our skull, but it is heavily biased. Human decision making is the ultimate black box.
Only with data, the right data alongside human judgment can we get any change happening. And clearly, what your employees and candidates are now looking for, is change. We hope that the debate over the value of diverse teams is now over. There is plenty of evidence that diverse teams lead to better decisions and therefore, business outcomes for any organisation.
This means that CHROs today are being charged with interrupting the bias in their people decisions and expected to manage bias as closely as the CFO manages the financials. But the use of Ai tools in hiring and promotion requires careful consideration to ensure the technology does not inadvertently introduce bias or amplify any existing biases. To assist HR decision-makers to navigate these decisions confidently, we invite you to consider these 8 critical questions when selecting your Ai technology. You will find not only the key questions to ask when testing the tools but why these are critical questions to ask and how to differentiate between the answers you are given.
This guide is presented by Sapia whose AI-powered, text chat talent assessment tool has a user satisfaction rate of 99%.
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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.
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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.
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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 👇