Research shows that automation can make recruitment more human
To find out how to use Recruitment Automation to ‘hire with heart’, we also have a great eBook on recruitment automation with humanity.
New insights from Aptitude Research suggests Ai 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, something Sapia has long advocated
Aptitude Research has published a new paper showing that when you shift the focus in automated Talent Acquisition from an employer-driven view to a candidate-first then it is possible to reduce bias in hiring, and improve the overall human element of recruitment.
The research, sponsored by Sapia , an Australian technology company that has pioneered transparent Ai-assisted hiring solutions, shows that humanistic automation creates a personal connection at scale, and works to reduce bias, something no other technology or even human-centred solution can deliver.
Madeline Laurano, CEO of Aptitude comments “The misperception that candidates do not want automation and prefer to keep the current talent acquisition is one of the most significant misperceptions in talent acquisition. Candidates want a fair recruitment process and consistency in communication. Automation can support all of these initiatives and enhance the humanity of the experience.”
There are four main ways that talent acquisition is made more human with automation when the candidate is the focus, rather than simply moving candidates through the process:
- Automation can understand what candidates want: Ai considers the unique expectations and experiences of candidates and adapts to them as it learns. Collecting feedback about the recruitment experience and continually improving the candidate journey can help candidates feel connected and heard.
- The correct data can interrupt bias early in the process: By creating a consistent and fair experience for candidates early in the process, and not relying on CV data as the determinate of job suitability, companies are more successful at reducing bias and increasing inclusivity.
- Trust can be built through transparent data: Both employers and candidates need to trust the data and methodologies for the technology that they are using, something that can be achieved through transparency. Companies looking at automation should consider providers that will partner with them and provide transparency.
- Provide feedback to every candidate: Though natural language processing every candidate receives personalized feedback and messaging. Leaving unsuccessful candidates feedback they can use for future job searches is empowering and a big leap from ‘ghosting’ or a standard rejection email.
The research can be downloaded here https://sapia.ai/recruitment-automation-humanity/
About Aptitude Research
Aptitude Research Partners is a research-based analyst and advisory firm focused on HCM technology. We conduct quantitative and qualitative research on all aspects of Human Capital Management to better understand the skills, capabilities, technology, and underlying strategies required to deliver business results in today’s complex work environment.
About Sapia
Sapia has become one of the most trusted mobile-first Ai recruitment platforms, used by companies across Australia, India, South Africa, UK and the US, with a candidate every two minutes engaging with their unique Ai chatbot Smart Interviewer.
What makes their approach unique in its a disruption of three paradigms in recruitment -candidates being ghosted, biased hiring and the false notion that automation diminishes the human experience.
The end result for companies – bias is interrupted at the top of the funnel, your hiring managers make more objective decisions empowered by Smart Interviewer their co-pilot, inclusivity is enhanced, and your hired profile starts to look more like your applicant profile.
Media contacts
Barb Hyman, CEO Sapia
barb@sapia.ai
Madeline Laurano , Researcher Aptitude Research
madeline@aptituderp.com
About Author
