This piece was originally created by Data Root Labs, edited and republished here with permission.
HR is one of those “human” jobs that will be hard to replace with AI. Akin to psychology, it requires a high level of EQ (quotient of emotional intelligence) and profound personal touch. The common preconception is that it’s very hard to augment, let alone automate. Over the last half-decade, this line of logic has come under fire, with data-driven approaches penetrating more and more human resource practices.
With the cost of AI adoption plummeting and the data science community growing by the minute, business leaders are starting to reach out to process automation and augmentation opportunities in the people operations realm. Gartner predicts that by 2022 (three years from now!) one in five workers engaged in non-routine tasks will rely on AI to do their jobs.
The key drivers fueling the growth of HR tech market include increasing need for managing the widespread workforce, growing demand for replacing the legacy systems, the increasing importance of candidate experience and technological proliferation in Big Data analytics, Machine Learning, Artificial Intelligence (AI), and Internet of Things (IoT). Thus, new report by Grand View Research, Inc. projects the global human resource management market to reach USD 30.01 billion by 2025, registering a CAGR of 11.0% from 2019 to 2025.
PwC forecasts that 20% of U.S. companies with AI initiatives will roll out AI across their business this year to both re-imagine jobs and work processes as well as grow profits and revenue.
A lot of AI use cases revolve around eliminating the tedious and routine tasks, while HR managers handle the most important side of the job – human interaction. We have identified the following key problems that AI can solve:
- Efficiency improvement: automating repetitive tasks.
- Recruitment and candidate assessment: more efficient and less biased hiring.
- Employee development: coaching and engaging employees to enable personal growth.
- Culture maintenance and HR management: identifying cultural issues and key areas for improvement.
Let’s look at those cases one by one:
Efficiency improvement
Automating repetitive tasks.
AI in HR and recruiting gets people to move away from repetitive tasks not to waste their talents. As a result, they can target their energies on more high-level tasks, such as finding promising employees and working to keep them with the company. HR staff will focus on being a strategic partner to business divisions rather than crunching data as a task processor. AI will empower companies to make faster decisions by:
- Accessing up-to-date information.
- Spotting trends through pattern recognition.
- Using machine learning to identify past mistakes to avoid and accelerating processes.
Recruitment and candidate assessment
More efficient and less biased hiring.
One of the major disruptors in candidate hiring is HireVue’s artificial intelligence platform. It identifies and analyzes the tone, word choice, body language, question context, and answers of candidates who have recorded video interviews to determine if they’re a good fit – by skillset and culture. Their quantifiable score compares all the candidates, ensuring HireVue makes the optimal unbiased hiring decisions – all thanks to AI and Machine Learning.
AI helps companies through the process of pre-hire assessments. While assessments are nothing new, in the era of AI, a company can predict which candidate will be a better hire in the future. Sample this, a candidate applies for a role in a company by entering his resume. An AI-powered system analyses the resume and compares it to the successful employees in the same role.
A chatbot reaches out to the candidate and asks some pre-screening questions. They collect candidate data, and AI uses it to score the candidate and present the result to a recruiter.
Pymetrics uses AI-based gamified assessment to screen candidates. One of their customer’s hiring success rate has gone up by over 30% while eliminating all the “educational pedigree bias” inherent to the recruitment process faced by almost all companies out there. AI in recruitment is already huge.
Another player in the HR assessment game, Sapia, helps big brands to get the candidate experience right. They already have text data on 15% of the Australian population that helps identify with 85% accuracy the personality profile of applicants into all customer-facing roles (retail, sales, customer service, etc.). To reduce the hiring bias, the company doesn’t use CV data, nor it builds data models off the existing employees. They only use the text data ensuring that everyone gets a fair go at the role. That allows their clients to hire for the right values and behaviors. In addition, Sapia provides personalized personality reports to every applicant for every role. Amid low unemployment and the rule of social media, this is particularly important to consumer brands who measure the impact of poor candidate experience on customer attrition.
Employee development
Coaching and engaging employees to enable personal growth.
Learning and development (L&D) is a young HR practice and yet the global L&D industry is worth over $200B. Nearly half of the L&D opportunities organization forget, inappropriately apply, or waste on people that don’t want or need it.
Companies like Fuse are now building AI-based coaching tools that request feedback, read comments, and glean sentiment from employees and entire teams. They use data to match these individual and team issues against higher performing teams, giving managers and supervisors the requisite tools to do better.
As part of it, HR undertakes activities such as talent acquisition, employee management, performance management, succession management, etc.
For example, organizations like Greenhouse Software are integrating IBM-AI capabilities through the IBM Watson Candidate Assistant. It is a suite of AI-powered tools that matches jobs to the candidates and vice-versa based on their personalities, skills and interest areas. Greenhouse collects candidate data through various funnels including social media.
It observes minute details such as whether an employee submitted their work sample through LinkedIn or Glassdoor. It maintains scorecards for all the employees based on its own analysis with zero human intervention. This helps the interviewers sort through the applications ahead of time and keep the talent funnel ready.
Culture maintenance and HR management
Identifying cultural issues and key areas for improvement.
AI can look at organizational network data like email traffic, survey results and sentiment of comments to identify areas of stress, arising ethical dilemmas, and various forms of spreading toxicity within a company culture. This helps HR managers identify red flags faster and act in a preventive rather than reactive way.
Employee mental health is extremely important. People are the foundation of your company and they better be happy if management aims to achieve some lofty goals. To remedy some ongoing cultural issues, AI now identifies behaviors that cause poor work performance and disrupt the balance of your working environment. A new breed of intelligent chatbots can ease these situations by providing interactions in an intelligent and easy-going manner while alerting the HR department of any cases that go beyond the red line and need in person handling.
The above are some of the key cases that new technologies enable. For a deeper understanding of the innovation happening in HR tech, take a look at the following infographic by Will Saborio at Silicon Salsa.
Many of these companies already have AI and Big Data components.
(fig. 1) The early-stage HR tech landscape
M&A activity in HR sector
The mergers and acquisitions activity in the past year has been on the rise in HR tech, characterized by both more deals and bigger volume of deals. The trend for consolidation is strong as companies look to increase scale, add new customers and product lines, and penetrate new geographies.
From Recruit acquiring Glassdoor for $1.2B and K1 Investment Management acquiring Jobvite for $135M to SAP’s acquisition of Qualtrics for $8B in cash, there is no lack of jaw-dropping deals in HR tech from both financial and strategic buyers.
What are the most important factors for the buyers? The buyers are willing to pay more for high growth, SaaS product offering, dominance in a particular vertical or geography, ability to scale current solution, sticky enterprise customers, and clean financials. Yet the ultimate factor that determines the highest price possible is the 2nd (or even 3rd) acquisition offer on the table forcing buyers compete for a given company.
With a changing and developing technology landscape, we predict a continuous increase in HR tech M&A activity. In the table below, we summarize the key recent M&A events in HR tech:
| Company | HQ / year founded | Amount Raised, $ | Deal Amount, $ | Acquirer | Deal Rationale |
| Get BoxSuite Pty | Australia / 2009 | N/A | 1.4M | ELMO Software | Acquiring cutting edge native SaaS, cloud-based technology which will disrupt the large and growing rostering and time & attendance market. |
| Imaginatik | US / 1994 | 2.6M | 1.7M | Planbox | The new combined company will expand Imaginatik’s UK and US operations. |
| Scannel Solutions | Ireland / 1998 | N/A | 4.5M | Ideagen | Acquiring a leader in Environmental Health, Safety and Quality solutions, which it offers via a SaaS platform, will enable Ideagen to grow both SaaS capabilities and accelerate EHSQ offering. |
| The Sage Group (Sage Payroll Solutions) | US / 2016 | N/A | 94M | iSolved HCM (Accel-KKR Company) | Sage’s payroll processing SaaS solutions will accelerate iSolved’s growth in HCM industry, specifically targeted toward the midmarket, while increasing its licensee and partner network as well. |
| Jobvite | US / 2006 | 256M | 135M | K1 Investment Management | Jobvite, a provider of analytics-based recruitment management SaaS for businesses. K1 and Jobvite also announced the acquisition of Talemetry, RolePoint, and Canvas. The investment by K1 and acquisitions will enable Jobvite to create a comprehensive, end-to-end talent acquisition platform. |
| Workmarket | US / 2010 | 66M | 400M | ADP | To add agile tool to convince enterprises to use it as part of a larger system of workforce products and compete with smaller companies. |
| Glassdoor | US / 2007 | 204.5M | 1200M | Recruite | Acquiring a leading job and recruiting company well known for providing greater workplace transparency. |
| Ultimate Software | US / 1990 | 19.1M | 11000M | Hellman & Friedman Capital Partners | PE deal. The acquisition will allow the company to utilize financial and strategic advice to bring new features and services to the market more quickly. |
| ThinkHR | US / 2005 | 82.5M | N/A | Mammoth | To expand Mammoth product and service offerings, leverage complementary capabilities and expertise. |
| ePoise | India / 2013 | 0.5M | N/A | Zoho | Likely, an acquihire of a hiring automation product startup’s team. |
| Aasaanjobs | India / 2004 | 6.5M | N/A | OLX | To strengthen OLX position in the online job search segment by adding blue collar job vertical. |
| Le & Associates | Vietnam / 2001 | N/A | N/A | Trust Tech | 44.42% stake in L&A investment corporation, which owns Vietnam HR company Le & Associates. The acquisition comes as part of Trust Tech’s plan of expanding its businesses in different countries which is part of its strategy in its medium-term management plan. |
| Zugata | US / 2014 | 10.2M | N/A | Culture Amp | Zugata’s acquisition allows Culture Amp to bring an increasingly sophisticated use of data across the employee lifecycle. |
| Rallyteam | US / 2013 | 8.6M | N/A | Workday | Rallyteam, a talent mobility platform that uses machine learning to help companies better understand and optimise their workforces by matching a worker’s interests, skills, and connections with relevant jobs, projects, tasks, and people. |
| Jibe | US / 2009 | 41M | N/A | iCIMS | iCIMS acquires Jibe to provide employers best-in-class candidate engagement and recruitment marketing capabilities. Jibe’s talent and jobs matching capability is powered by Opening, a company later mentioned in this article. |
Startups and investments
In Q2 2019 alone, VCs have poured $1.448B of VC investment into HR tech. The categories that saw a spike in investments are Wellness (Gympass, $300M round ), Benefits (Collective Health, $205M), and Core HR (HR Path, $112.5M, Payfit $78.6M). When it comes to AI-focused startups, the results are also impressive. In the table below we summarize the biggest rounds and most interesting deals around companies using AI in HR:
| Company | HQ / year founded | Amount Raised, $ | Investors | What they are doing |
| Visier | Canada / 2010 | 91.5M D | Sorenson Capital, Adams Street Partners, Summit Partners | Visier People™, the leading people analytics and workforce planning solution, provides with answers to hundreds of pre-built, best practice questions about workforce, across HR and business topics to strategically manage a complex workforce. |
| Wrkit | Ireland / 2016 | N/A | Enterprise Ireland | Wrkit is a one stop shop to inspire better, healthier, working environments. With the help of AI and automation, wrkit specialises in the creation of better, healthier working environments using our online suite of data driven Employee Engagement & Retention tools. |
| Sapia | Australia / 2013 | 3M A | Capital Zed, Rampersand | Sapia is an online platform which takes a data-first approach to help businesses hire the right people. By leveraging the power of technology, Sapia helps quickly evaluate a large number of applications and narrow down the list to those with suitable profiles and ensuring quality candidate experience along the way. |
| Lumity | US / 2013 | 33M B | Social Capital, True Ventures, Threshold, Rock Health | Lumity simplifies the pain of company health plan decisions with data-driven recommendations that drive cost savings and improve outcomes. |
| Jumpstart | US / 2017 | 4.2M Seed | Michael Lynton, Joshua Steiner, Glenn Dubin | Jumpstart is a machine learning platform that enables students to learn, discover and connect with the most innovative companies in the world. The company aims to create equal opportunity for students in a highly competitive and biased industry by learning about a students interests, values and experiences and making intelligent matches using data and technology. |
| PredictiveHR | US / 2016 | 1M Seed | Trendata | AI Powered platform helps aggregate and normalize data across disparate systems to create rich visualizations and predictive people analytics. |
| HireVue | US / 2004 | 93M E | Sequoia Capital | Combining predictive, validated industrial/organizational science with artificial intelligence allows recruiting professionals to augment human decision-making in the hiring process, delivering higher quality talent, faster. HireVue has hosted over six million interviews for more than 700 customers worldwide. |
| Pymetrics | US / 2013 | 56M B | General Atlantic | Pymetrics develops neuroscience-based assessment and prediction technology to transform the way companies hire, retain, and develop their employees. It offers cognitive and emotional assessment solutions; and a personalized and dynamic recommendation engine for recruiting/hiring, retaining, and developing talent. |
| JobRocker | Austria / 2015 | 1.83 A | Surplus Invest | Online job search portal that connects applicants’ CVs with job openings using a proprietary algorithm and further human-driven consulting. |
| MoBerries | Germany / 2015 | 1.8M E | High-Tech Gründerfonds | Automated ranking system that matches applicants with companies searching for new hires. The goal now is to build a screening bot for selecting candidates before interviews, as the founders deeply believe the candidates’ pre-filtering phase can be fully automated. |
| Productive Mobile | Germany / 2014 | 3.4M E | HV Holtzbrinck Ventures | Human Process Augmentation (HPA). Their software disrupts the way enterprise software workflows are built, optimized and automated because of its fast implementation and lower costs, making humans more productive. |
| MeetFrank | Estonia / 2017 | 1M E | Hummingbird VC, Karma VC, and Change Ventures | Сhatbot that interacts directly with applicants, using AI and machine learning. The app analyzes the needs of users and proposes job advertisements that match with the candidates’ profile and abilities, from the jobs pool. If the user is interested in one of the suggested positions, he or she can start a private and anonymous chat with the company. |
| Opening | Ireland / 2015 | $600K Seed | NDRC | Opening builds cognitive talent and jobs matching solutions and helps HR technology vendors, enterprises and staffing agencies leverage the power of natural language understanding to create smarter talent solutions in days, not months. Opening’s core technology, Baikal AI, is the world’s deepest and clearest data lake for talent and jobs data. Baikal AI, combines the key innovations in deep learning and natural language understanding, and simplifies the deployment of talent and job matching models. |
| Mya Systems | US / 2011 | 32.4M B | Foundation Capital | A conversational AI equipped with both natural language understanding and natural language generation. Mya aims to automate sourcing, screening, and scheduling for recruiters, initiating conversation with candidates right after they apply and assess them for baseline requirements with real dialogue. |
| Textio | US / 2014 | 29.5M B | Scale Venture Partners | Textio’s ‘augmented writing platform’ helps companies create better, more effective job listings. Textio’s predictive engine analyzes global hiring data from over 10 million jobs and their associated hiring outcomes every month, to uncover the language patterns that lead to successful job postings. It then uses this intelligence to make real-time recommendations as you craft your listing, predicting its performance and guiding you to an ultimately solid job post. |
| Entelo | US / 2011 | 40.7M C | U.S. Venture Partners (USVP) | Entelo identifies those candidates who are most likely to be open to new opportunities, removing the pre-qualification layer from recruiters’ responsibilities. Additionally, the Entelo platform includes a robust candidate search database; recruiter email tracking, management, and analytics; algorithm and search filters built specifically for diversity initiatives, and more. |
| Restless Bandit | US / 2014 | 10M A | Toba Capital | An artificial intelligence tool that finds both passive and active qualified talent from a candidate pool of over 100 million, and engages them and only them. Using discovery and rediscovery algorithms, Restless Bandit searches for candidates externally and within your ATS, respectively. It also intelligently and automatically retargets top prospects. |
| Hire Abby | US / 2018 | to watch | Hire Abby helps companies gather applicant intel and predict a candidate’s potential fit for the company. majorly improves the candidate experience, while also helping the business make better, faster hiring decisions. | |
| Paradox | US / 2016 | 13.3M A | Paradox’s AI recruiting assistant, Olivia, takes the focus on candidate experience to a new level. She uses advanced natural language processing to answer all your applicants’ questions; she has real, one-to-one conversations with them through the channel of their choosing — web. | |
| Jobiak | US / 2018 | to watch | Jobiak provides the industry’s first AI-based recruitment marketing platform that is designed to quickly and directly publish job postings to Google for Jobs, maximize their visibility and accelerate the flow of qualified candidates. | |
| Harver | US / 2013 | 14M A | Insight Venture Partners | The company’s TalentPitch predicts which applicant performs the best. The experience is tailor-made for organizations that give a realistic preview of the job while collecting success-predicting data. Harver algorithms calculate the likeliness of success for each applicant. |
| Hackajob | UK / 2014 | 8M A | AXA Venture Partners, Downing Ventures | Hackajob is a data-driven and engaging recruitment platform that matches top digital talent with exciting companies. |
| Uncommon | US / 2015 | 18M A | Spark Capital, Zeev Ventures, Canaan Parners | Uncommon Co. uses artificial intelligence to identify the requirements for job postings and matching those jobs to qualified applicant. |
| Astound | US / 2016 | 11.5M A | Pelion Venture Partners, Vertex Ventures US | The future of AI for employee service: support automation using NLP and machine learning. |
| Stella.ai | US / 2016 | Seed | Pete Flint | Stella is an online recruitment agency that focuses on reducing time to hire with the use of artificial intelligence. The company helps to speed up hiring by 80% for any position using artificial intelligence to pre-qualify talent. |
| Scoutible | US / 2015 | 6.5M Seed | Learn Capital, Mark Cuban | Scoutible is a game-based hiring platform, using immersive mobile games to pinpoint perfect-fit candidates for jobs. Scoutible’s patent-pending technology identifies players’ unique cognitive and personality traits through gameplay, then spots opportunities where players’ attributes match those of companies’ proven top performers. |
| Headstart | UK / 2016 | 1.6M Seed | Plug & Play, Momentum, FoundersX, Tenaya Capital, others | Headstart is diversity recruiting software focused on breaking the cycle of exclusion. |
| Ambit Analytics | US / 2017 | 1.1M Seed | Romulus Capital | Ambit Analytics helps leaders build collaborative teams through insights on how they talk and listen. |
| Beaconforce | US / 2017 | 800K Pre-seed | Beaconforce has developed a methodology and SaaS platform that combines Artificial and Emotional Intelligence to create challenging, motivating, and productive work environments. | |
| Censia | US / 2017 | 7.6M Seed | Streamlined Ventures, Plug&Play, X Factor Ventures | Censia empowers talent acquisition by equipping recruiters with the power of artificial intelligence to eliminate low-value work, error and bias. The result is substantially better, faster hiring decisions that ultimately drive revenue with every hire. |
| Remesh | US / 2014 | 13.8M A | General Catalyst, others | Remesh empowers researchers and executives to have a dynamic conversation with up to 1,000 participants- online and in real-time. The Remesh platform uses AI to understand, analyze, and segment the vast amount of open-ended responses pouring in- in a matter of minutes. |
| Leena AI | India / 2015 | 2M Seed | Y Combinator, angels | Leena is smart AI powered HR companion dedicated towards engaging employees. Leena is powered by ChatterOn, a cutting-edge AI chatbot development platform with self- learning cognitive capabilities, which leverages 10 Mn+ conversational data points from over 12,000 businesses. |
| Enboarder | Australia / 2012 | 12M A | Greycroft, Next Coast Ventures, Stage 2 Capital, Thrive Global, Venmo, others | Enboarder is an onboarding and engagement platform that focuses on new hire experience and engagement rather than just tasks, forms and paperwork. |
| dotin | US / 2012 | 1.2M Seed | Amar Chokhawala, Bishop Ranch Intelligence Innovation Accelerator, Net One System, Ganesh Iyer. | dotin.us is a dedicated to understanding the art of decisions made by the subconscious mind to yield powerful business outcomes. By using the science of psychological, structured/unstructured social or enterprise data and machine learning, the company taps into the subconscious mind of humans enabling to capture the true digital personality fingerprint of every user. |
| Helena by Woo | US + Israel / 2015 | 7M A | Lord David Alliance, Acecap, Microsoft Scaleup TelAviv, others | Woo, the marketplace for matching employers and ‘passive’ job seekers, has launched Helena, an AI-driven headhunter that automatically scouts, approaches and sources the best candidates on behalf of employers. |
| SmartDreamers | Romania / 2014 | 2.1M Seed | Gapminder VC, Catalyst Romania, 3TS Capital Partners | SmartDreamers is a Recruitment Marketing Automation platform that empowers recruitment teams to smartly advertise jobs across the web. Integrated with Facebook, Google Ads, YouTube, Snap, Instagram, publishers and niche websites, SmartDreamers streamlines the recruitment marketing processes. SmartDreamers helps companies such as Uber, Vodafone, Siemens, Orange, IBM and many others to smartly recruit talent. |
| Botbot.AI | Singapore / 2017 | to watch | Botbot.AI is an enterprise productivity solution that uses chat as an interface to automate business processes and workflows in order to move people away from low-value, menial and transactional work and refocusing them on high-cognition, high-value tasks, driving enterprise productivity and elevating the level of engagement. | |
| Ambit Analytics | US / 2017 | 1.1M Seed | Romulus Capital | Ambit Analytics helps leaders build collaborative teams through insights on how they talk and listen. A spin-off from SRI International, the birthplace of Apple’s Siri and Nuance, Ambit leverages world-class audio AI technology to quantify verbal communication and uses those metrics to train people to become better communicators. |
| Talespin | US / 2015 | 5.6M A | Talespin is disrupting the future of work through radical change in enterprise tools. By leveraging the power of artificial intelligence (AI), virtual reality (VR), and augmented reality (AR) Talespin is changing the way people engage, educate, and empower the next generation of the workforce. | |
| AmazingHiring | US / 2012 | 800K | AltaIR Capital, SMRK, Starta Ventures | AmazingHiring is a web application for technical talents acquisition. It automatically searches for the right candidates across 50+ sources. AI-based technology helps to save time on candidate pre-screening. Powered by AI technology, trusted by 6000+ recruiters. Clients already include VMware, Nvidia, Dell, Intercom, Capgemini, and ThoughtWorks. |
Final thoughts and real cases
The human-AI collaboration model is essential for a people-oriented domain like HR. It’s unlikely that AI will replicate the nature of human relationships and its nuance. That said, advantages of AI in HR can help us attune to people operations and make better decisions supported by solid data.
Since AI is developing and new opportunities are opening up, the ways companies use AI and the impact of AI in HR and recruiting will also change. The future of AI in HR processes is clear – AI will affect every organization. The question is how companies adapt and which processes they choose to reinvent or improve.
“Companies will need to be mindful of existing biases and work to ensure that AI does not perpetuate the problem”
We at DataRoot Labs work with various HR-tech enterprises and startups. We help them build out AI-powered MVPs or transform enterprises by reinventing their HR systems with AI. Below, you may find practical cases on how we have solved real HR challenges with AI technologies:
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Sapia.ai Wrapped 2024
It’s been a year of Big Moves at Sapia.ai. From welcoming groundbreaking brands to achieving incredible milestones in our product innovation and scale, we’re pushing the boundaries of what’s possible in hiring.
And we’re just getting started 🚀
Take a look at the highlights of 2024
All-in-one hiring platform
This year, with the addition of Live Interview, we’re proud to say our platform now covers screening, assessing and scheduling.
It’s an all-in-one volume hiring platform that enables our customers to deliver a world-leading experience from application through to offer.
Supercharging hiring efficiency
Every 15 seconds, a candidate is interviewed with Sapia.ai.
This year, we’ve saved hiring managers and recruiters hours of precious time that can now be used for higher-value tasks.
Giving candidates the best experience
Our platform allows candidates to be their best selves, so our customers can find the people that truly belong with them. They’re proud to use a technology that’s changing hiring, for good.
Leading the way in AI for hiring
We’ve continued to push the boundaries in leveraging ethical AI for hiring, with new products on the way for Coaching, Internal Mobility & Interview Builders.
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Situational Judgement Tests vs. AI Chat Interviews: A Modern Perspective on Candidate Assessment
Choosing the right tool for assessing candidates can be challenging. For years, situational judgement tests (SJTs) have been a common choice for evaluating behaviour and decision-making skills. However, they come with limitations that can make the hiring process less effective and less inclusive.
AI-enabled chat-based interviews, such as Sapia.ai, provide organisations with a modern alternative. They focus on understanding candidates as individuals and creating a hiring experience that is both fair and insightful while enabling efficient screening and selection.
This shift raises important questions: Are SJTs still a tool that should be considered for volume hiring? And what do AI assessments offer in comparison?
1. The Static Nature of SJTs
Traditional SJTs use predefined multiple-choice questions to assess behavioural tendencies and situational knowledge. While useful for screening, these static frameworks lack the flexibility to adapt based on real-world performance data or evolving role requirements.
Once created, SJTs don’t adapt to new data or evolving organisational needs. They rely on fixed scenarios and responses that may not fully reflect the dynamic realities of modern workplaces, and as a result, their relevance may diminish over time.
AI-enabled chat interviews, on the other hand, are inherently adaptive. Using machine learning, these tools can continuously refine their models based on feedback from real-world outcomes such as hiring or turnover data. This ability to evolve ensures the assessments align with organisations’ needs.
2. Richer Data Through Open-Ended Responses
One of the main critiques of SJTs is their reliance on multiple-choice responses. While structured and straightforward, these options may not capture the full scope of a candidate’s thinking, communication skills, or problem-solving ability. The approach is often limiting, reducing complex human behaviour to a few predefined choices.
AI-enabled chat interviews work more holistically and dynamically. These tools provide a more complete picture of a person by allowing candidates to answer questions in their own words. Natural language processing (NLP) analyses their responses, offering insights into personality traits, communication skills, and behavioural tendencies. This open-ended format lets candidates express themselves authentically, giving employers a deeper understanding of their potential.
3. The Candidate Experience: Stressful or Supportive?
SJTs often include time constraints and rigid formats, which can create pressure for candidates. This is especially true when candidates feel forced to choose options that don’t fully reflect how they would actually behave. The process can feel impersonal, even transactional.
In contrast, chat-based interviews are designed to be conversational and low-pressure for candidates. By removing time limits and adopting a familiar chat interface, these tools help candidates feel more at ease. They also frequently include personalised feedback, turning the assessment into a valuable experience for the candidate, not just the employer.
4. Addressing Bias and Fairness
Traditional SJTs are prone to transparency issues, as candidates can often identify and select the “best practice” answers without revealing their true tendencies. Additionally, static test designs can unintentionally embed bias; due to the nature of the timed test, SJTs have been found to disadvantage some groups.
AI chat interviews, when developed ethically within a framework like Sapia.ai’s FAIR Hiring Framework, eliminate explicit bias by relying solely on the content of a candidate’s responses. Their machine learning models are continuously validated for fairness, ensuring that hiring decisions are free from subjective judgments or irrelevant demographic factors.
5. An Assessment That Improves Over Time
Workplaces are constantly changing, and hiring tools need to keep up. SJTs’ fixed nature can make them less effective as roles evolve or organizational priorities shift. They provide a snapshot but not a dynamic view of what’s needed.
AI-enabled chat interviews are built to adapt. With feedback loops and continuous learning, they incorporate real-world hiring outcomes—like retention and performance data—into their models. This ensures that assessments stay relevant and effective over time.
Rethinking Candidate Assessment
As hiring demands grow more complex, so does the need for tools that can capture the whole person, not just their response to hypothetical scenarios. While SJTs have played an important role in hiring practices, they are increasingly being replaced by tools like AI-enabled chat interviews.
These modern approaches provide richer data, adapt to changing needs, and create a richer and more engaging experience for candidates. Perhaps most importantly, they emphasise fairness and inclusivity, aligning with the growing demand for unbiased hiring practices.
For organisations evaluating their assessment tools, the question isn’t just which method is “better.” Understanding the specific needs of your roles, teams, and candidates will help you choose tools that help you make decisions that are both informed and equitable.
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Keeping Interviews Real with Next-Gen AI Detection
It’s our firm belief that AI should empower, not overshadow, human potential. While AI tools like ChatGPT are brilliant at assisting us with day-to-day tasks and improving our work efficiency, employers are increasingly concerned that they’re holding candidates back from revealing their true, authentic selves in online interviews.
As an assessment technology provider, we are responsible for ensuring the authenticity and integrity of our platform. That’s why we’re thrilled to unveil the latest upgrade to our flagship Chat Interview: the AI-Generated Content Detector 2.0. With groundbreaking accuracy and a candidate-friendly design, this innovation reinforces our mission to build ethical AI for hiring that people love.
Artificially Generated Content (AGC) is content created by an AI tool, such as ChatGPT, Claude, or Pi. We initially rolled out the first version of our AGC detector last year and have continued to improve it as our data set has grown and these AI tools have evolved.
What’s New?
Our updated AGC Detector 2.0 achieves an impressive 98% detection rate for AI-assisted responses, with a false positive rate of just 1%. This gives organisations peace of mind that they’re getting the most authentic assessment of every candidate.
This cutting-edge system builds on Sapia.ai’s proprietary dataset of over 2 billion words, derived from more than 20 million interview question-answer pairs spanning diverse roles, industries, and regions. It’s trained on real-world data collected before and after the release of tools like ChatGPT, ensuring it remains robust and reliable even as AI tools evolve.
The Challenge of AI in Chat-based Interviews
Our data shows that around 8% of candidates use tools like GPT-4 to generate responses for three or more interview questions. While these tools may offer a quick way for candidates to complete their interview, they can inadvertently hide a person’s true personality and potential – qualities our customers are most interested in understanding through our platform. In fact, research from Sapia Labs shows that these tools have their own personality traits, which may be quite different from the candidate applying for the role.
For Candidates: Enabling Authenticity
When a response is flagged as potentially AI-generated, the system doesn’t disqualify candidates. Instead, a real-time warning pops up, allowing them to revise their answers or submit them as-is. This ensures that candidates are encouraged to present themselves authentically, reflecting their unique communication styles and sharing their genuine experiences.
For Hiring Teams: Actionable Insights
Responses flagged as AI-generated are highlighted in the candidate’s Talent Insights profile, accessible via Sapia.ai’s Talent Hub or ATS integrations. These insights give hiring teams the transparency to make informed decisions, fostering trust while accelerating hiring timelines.
Built on Unmatched AI Interview Expertise
“Our detection model’s strength lies in its foundation of real-world interview data collected from diverse roles and regions,” says Dr Buddhi Jayatilleke, Sapia.ai’s Chief Data Scientist. This depth of understanding enables the AGC Detector to maintain its industry-leading accuracy – even when candidates subtly modify AI-generated answers to appear more human.
Why This Matters
The AGC Detector 2.0 embodies Sapia.ai’s commitment to ethical AI that amplifies human potential. As our CEO Barb Hyman explains:
“The hiring landscape has fundamentally changed since ChatGPT, but our commitment remains clear: AI should amplify human potential, not penalise it. This breakthrough fosters authentic hiring conversations. Our real-time warning system helps candidates make better choices and gives enterprises confidence in their selection decisions.”
Testing and Validation of the AGC Detector 2.0
The new detector has been rigorously tested on over 25,000 interview responses generated by humans and leading AI models like GPT-4, Claude-3.5, and Llama-3. The results speak for themselves, reinforcing the reliability and fairness of this game-changing technology.
Fairness & Transparency in AI-Enabled Hiring
By detecting AI-generated content while allowing candidates to correct their responses, our AGC Detector 2.0 ensures every applicant has the chance to put their best, most authentic foot forward when applying for a role powered by Sapia.ai. For enterprises, it provides confidence in the integrity of their hiring decisions and ensures they’re connecting with real candidates at scale.