To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.
New insights from Aptitude Research suggest recruitment automation can play a much greater role in talent acquisition than just improving efficiency for hiring managers, it can also make the interview process more human for candidates.
The research shows that when you shift the focus from an employer-driven view to a candidate-first view, then it is possible to reduce bias in hiring and improve the overall human element of talent acquisition.
For most companies, the value of automation is perceived through the recruiter and hiring manager experience, with the benefits to the candidate often ignored. However, recruitment automation has to be about more than simply moving candidates through the process quickly to have any significant benefit to a company.
When you focus on the impact and experience of the candidate, the benefits to both recruiters and candidates can significantly improve through recruitment automation. This approach has given rise to a movement called humanistic automation technology.
But humanistic automation sounds like an oxymoron right? Is it even possible?
The Aptitude Research showed not only is this possible, but that when Ai is used this way, it creates personal connection at scale, and works to reduce bias, something no other technology or even human-centred solution can deliver.
So, how exactly does it do this?
Here are four main areas of talent acquisition that candidate-focussed recruitment automation improves on,and how it achieves this:
1. Connection
There have been some slight improvements in building connections through the hiring process recently, but only 50% of companies have a single point of contact for communication, which results in candidates feeling engaged or valued through the process.
Recruitment automation with a candidate-focus means that communication is personalised for high-engagement with the ability for the conversation to adapt to what it learns about a candidate almost immediately.
As a candidate finding out that you are not successful is tough, and worse, most companies just ghost those they don’t wish to move ahead with. Automation can ensure that every candidate is engaged and cared for even when they are not moving forward in the process – and that doesn’t mean a standard rejection email. Ai can deliver highly personalised communication that builds connection even for those unsuccessful in their application.
2. Inclusivity
Although some companies have made efforts to remove bias from resumes, companies still have a lot of work to do on inclusion. For starters, many are relying on training programs, which have shown to be largely ineffective in delivering long-term change.
It’s true that recruitment automation can amplify bias, but automation that works to reduce bias is continually testing against biases in the system and has been shown to be effective in reducing the impact of bias in hiring decisions. Somethings humans cannot do (we’re inherently biased, whether we like it or not).
When you have the right data input gathered through blind screening and blind interviews – that don’t rely on CV data – then you can help companies achieve an equal and fair experience to all candidates.
Want to remove bias from recruitment and not just talk about it?
Download the Inclusive Hiring e-Book here
Inclusive hiring is not limited to gender and race. Companies need a broader view of diversity, equity, and inclusion that includes individuals with disabilities and neurodiversity. This requires the right digital tools and technology to ensure that candidates have a positive experience. In many cases, chat and text are more inclusive over video or even phone screening and interviews for these candidates.
3. Feedback
Most companies see feedback as a risky area and something they have no ability to do in a fair and timely manner. Essentially this is a lost opportunity for learning and development.
When you see feedback as a value proposition of an employer brand, its power in transforming your TA strategy becomes clear. Recruitment automation allows companies to deliver personalized feedback building trust and strengthening your employer brand.
Personalized feedback with tangible action items, means that candidates feel empowered even if they are rejected. Technology can help to deliver these action items in a human way, that even humans are not able to do at scale or even very well.
These insights are only made possible through natural language processing and machine learning that work in the background to reveal important information about the candidate. When a candidate feels like they are ‘seen’ that can be a transformational moment in their career paths.
Only recruitment automation can deliver individual feedback to everyone who takes time to do a job interview.
4. Trust
In an era of growing awareness around the privacy of data, only 1 in 4 candidates trust the data being will be used to drive hiring decisions. As companies look at recruitment automation through a candidate-centric lens, they must consider both the quality of the data they use and how to build trust between employers and candidates.
The biggest mistake that most companies make is using the wrong data. Resume data is not necessarily an indicator of performance or quality of hire.
Ethical Ai is something that hiring managers need to understand and use to evaluate providers. Providers using ethical Ai operate transparently, are backed by explanations, describe their methodology, and frequently publish their data.
Aptitude Research found that when data is transparent, it increases the trust in talent acquisition leaders, hiring managers, and senior leaders. With data transparency, 84% of talent acquisition leaders stated that they trust the data, and 78% of senior leaders trust the data.
Talent acquisition transformation has accelerated the demand for recruitment automation.
55% of companies are increasing their investment in recruitment automation this year. These companies recognise that automation can improve efficiency, lift the administrative burden, reduce costs, and enable data-driven decisions.
This report focuses on a new look at automation through the eyes of the candidate
After all, automation is more than moving candidates through a process quickly. It should also enable companies to communicate in a meaningful and inclusive way and build trust between candidates and employers.
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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.