A recent CNN story quoted only 12% of companies used AI last year to deliver not just a faster status quo, but a complete reinvention of the way they work. The automated learning that comes from AI solutions grounded in machine learning also delivers exponential returns to those who start early.
That same news story quantified those benefits as a 20% increase in cash flows over 10 years and the inverse is true as well – a 20% decline in cash flows for those that wait. These kinds of stats should trigger ‘FOMO’ for any enterprise business.
‘BC’ (before Covid-19), the motivation ‘to AI in HR’ might have been the automation of manual expensive HR processes, like recruitment, in a world of declining HR budgets and growing concerns about the bias we humans bring to those processes.
‘To AI’ your HR processes can also go beyond your bottom line. It’s a way to humanise your candidate experience. A way to reduce the asymmetry of recruitment, to empower both sides to make the right decisions. It gives you this kind of candidate feedback from a solution that looks like this.
Right now, curiosity about AI is being replaced by a burning platform for change. For those wearing the exhaustion of surge recruitment using old traditional processes (not to mention the increased chances of bias as a result), the case for change is obvious. For everyone else who does any volume of recruitment, 4 factors will accelerate the move to AI solutions.
1. The need for humanity in your people processes especially recruitment.
Even though tragically it will soon be an employers market as unemployment rises, any organisations, including government, that can make that experience better for job seekers is onto a winner. Nothing sucks more than having to line up at Centrelink, or fill out endless tedious application forms, and then hear nothing.
We ‘live’ on our smartphones, we expect convenience and immediate results, we want to be able to navigate a wide range of opportunities fast and make decisions fast. This applies to services we consume regularly (think Uber Eats, Afterpay, even banking services such as our next home loan). That immediacy and convenience is now the new norm for consumers, and candidates as a consumer of their next job are looking for the same experience.
Imagine if your applicants only needed to answer 5 engaging questions over a text conversation. Every applicant also receives their own personalised feedback which helps them prepare for future interviews!
Compare recruitment to applying for a bank loan where AI has been in use for a decade or more. That’s now a reality with AI in recruitment.
Use Sapia’s FirstInterview to see how easy it is for you to give every job seeker a fast, simple and empowering experience.
And read what job seekers think about it here.
2. The accessibility and affordability of AI solutions
We specialise in volume recruitment for those roles where it is even more critical to hire the right people now. Frontline roles like your customer service teams, carers and health care workers, sales consultants, and blue-collar workers. Our ready-made predictive models are instantly deployable enabling you to go live in under an hour. When using our AI saves you at least $20 on every applicant, (i.e. if you receive 1000 applications, that is a saving of $20,000), and deployment is as easy a sending a link to your applicants, AI offers value to any sized organisation.
3. The right AI tool can remove bias from your recruitment and deliver a more diverse workforce
No amount of bias training will make us less biased.
The ability to measure bias is one reason to use AI-based screening tools over traditional processes. The growing awareness that AI can be fairer for people prompted the California State Assembly to pass a resolution to use unbiased technology to promote diversity in hiring.
Avoiding bias is why we use text data to assess applicants. With 25 million words to draw upon in our data bank, across 10 critical volume hiring roles, our approach is both bias-free in its design and its execution. Our technology is built on the advances in ML and NLP that allow computers to gain valuable insights from large volumes of textual data. Our AI is entirely ignorant of race, age, gender or any of those irrelevant markets of job fit.
4. Knowing someone’s traits and values is a shortcut to hiring for culture
Marketing guru Seth Godin wrote a blog a few years ago on the ‘real skills’ that matter in hiring.
Whilst we all know what matters for our roles, our teams, our culture- real skills like resilience, curiosity, humility, drive and so on, these attributes are invisible in a CV and very hard to assess fairly and scientifically in a phone call or f2f interview.
Using text data, we can not only uncover standard personality traits such as extraversion, openness, humility but also real skills that matter such a drive, critical thinking, team player and accountability. Our data science team has recently uncovered that the language one uses in answering standard interview questions show a correlation to how likely they are to hop jobs. New hires that leave early cost significant time and money for organisations. Identifying such candidates early on can help companies make better hiring decisions.
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Blog
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.
Blog
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.
Blog
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.