The secret to securing great talent is a first-rate candidate experience. If you have been in any way entangled in the aftermath of 2021’s Great Resignation, you know that even an attractive remuneration package, with compelling benefits, is not enough: Now, more than ever, prospective hires will want to see the best of your organisation, and that includes the best of you. You must be fast, decisive, and flexible, from the point of first contact.
This is a problem amplified by scale. If you’re responsible for hiring 100,000 employees per year, for instance, you may find you are required to provide a top-notch candidate experience for that many prospects. You could decide that it is better to do things the old fashioned way, but it is more and more likely that, in doing so, you will miss out on great talent. The cost of such losses is best avoided.
Automation, be it through an assessment tool, conversational Ai platform, or Applicant Tracking System (ATS), is the simple key to solving volume hiring in a chaotic market. However, understandably, many high-volume hiring managers tend to think that automation comes at the cost of personalisation and human contact. If, for instance, you’re processing 5,000 prospects to fit 300 job openings, how do you ensure your candidates are met with the high-touch journey they expect? Is an automated Ai conversation, in the minds of candidates, not just as impersonal as older methods of qualification?
What ‘high-touch’ actually means, and its purpose
On the face of it, ‘high-touch’ implies an emphasis on person-to-person, face-to-face contact in your hiring process. If you can see your candidates, if you can greet them warmly and exalt your free-breakfast policy, you can make them feel special. Sending an email or a link to a form is impersonal, outmoded, and risks alienating the people you want to attract.
What if, instead, high-touch is a stand-in for meaningful contact, instead of lots of contact? What if you could conduct a smooth, quick, and painless interview process that:
- Asked the best from candidates, and allowed them to provide thoughtful responses in their own time
- Explored the human aspects of their personality, and not just the line items on their CV
- Ignored, by design, the aspects of candidates prone to bias (such as appearance, ethnicity, age, and so on)
Is that not more effective than a by-the-book interview in which you smiled a lot, engaged in forgettable small talk, and discussed a laundry list of perks?
Woolworths, Australia’s largest private employer, adopted the smart-touch automated hiring approach, and won handsomely for it. They used our Chat Interview (chat-based) and Video Interview (video-based) solutions to assess nearly 9,000 candidates, achieving a candidate satisfaction score of 9.2 out of 10. We saved the hiring team time and money, helped give each of their candidates the fairest possible go, and best of all, helped them achieve their hiring targets.
Woolworths wanted the equivalent of a high-touch candidate experience, and judging by these candidate testimonials, they certainly got it:
“The chat makes you feel like you’re in a safe space – it gives everyone an equal opportunity instead of an in person interview as people can get extremely nervous”.
“I found the process to be reflective and I liked how they wanted to know about me”.
“Everything was amazing! By far the best interview system I’ve encountered! It allowed me to be comfortable and be myself, it really allowed me to take my time with my responses rather than stutter over my words”.
“It was great. I like the potential to retake videos and how quick you’ve responded”.
There you have it: That is how a small hiring team can process nearly 10,000 candidates, using conversational Ai, and offer a truly high-touch candidate experience. But the benefits don’t stop there.
With a smart-touch automation solution, Talent Analytics can heighten your touch
When you entrust your hiring process to Smart Interviewer, our smart interviewer, you automate the process of meaningful data collection. That data is then transformed into actionable insights that help you improve your hiring processes. With TalentInsights, you could learn:
- Your average time to hire
- Estimated time saving in hours (incidentally, we’ve helped our customers save a total of 530,000 hours that would have been spent in cumbersome, high-touch interviews)
- The quality of your candidate pool overall, or by gender
- Overall candidate engagement scores
And much more. Suddenly, you have the numbers to back your wider hiring strategies, be they focussed on DEI, or fairness, or another goal. You can show your business that you are making real, quantifiable strides, and leading the way in efficiency and social responsibility.
The appetite for good, actionable data in HR is higher than it has ever been. Hiring managers are waking fast to the realities of the Great Resignation – that we just don’t know as much as we should about what constitutes good talent and candidate experience. In other words: We don’t really know why people are leaving, and we don’t really know why they do or don’t choose us in the first place.
According to a recent study by Madeline Laurano, founder of Aptitude Research, only 50% of the companies that invest in Talent Analytics actually trust the source of their data. When you consider that around 80 million American workers are hourly workers, one of the hardest-to-recruit employment segments of the moment, it becomes clear that the need for useful data is absolutely critical.
What approach will you take? What kind of experience will you provide your candidates, before and after hiring? What kind of data will guide your decisions? Remember: The choice to do nothing is still a choice, and it has an indeterminate cost.
Related
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.