impress.ai
November 11, 2022
Artificial intelligence has already infiltrated many aspects of our lives, from how we live to how we work, and everything in between. Perhaps our work lives witness the bulk of it today, from making tasks easier to eliminating human intervention across processes completely. Consequently, the world of recruiting is no stranger to the privileges the technology brings and is now rapidly embracing this technology.
Screening candidates is one of the most arduous tasks that recruiters undertake, scouring through multitudes of applications to identify the right match for the organization. The sheer manual effort required to screen candidates prompts the need for solutions to automate mundane tasks and assist recruiters by augmenting their ability to discover talent.
This blog discusses how AI is changing how recruiters screen candidates and how they can make better hiring decisions.
While typically, virtual assistants are designed to handle simple tasks, recruiters are now leveraging VAs for screening candidates. These virtual assistants are designed to screen the information provided by job applicants, helping recruiters to find the best-fit candidates for the role.
VAs engage with prospective candidates, asking questions ranging from candidates’ relevant experience, qualifications, and other basic information to pre-screen them for a role. Further, the VAs can be used for fulfilling more complex responsibilities such as digging deeper into the candidate’s suitability for the job by analyzing various assessment metrics. AI-powered VAs can help recruiters shortlist ideal candidates, and offer insightful reports and dashboards to all stakeholders in the recruitment process.
Talent rediscovery solutions leverage complex AI algorithms to help recruiters identify talented candidates who may have been overlooked during the initial screening process. Consider candidates who probably dropped off or could not join the company before, even after being ideal for a role – these candidates already fit the bill, and retargeting them would reduce the effort and time spent by HR teams and recruiters to look for candidates. Recruiters can use talent rediscovery to find drop-off candidates with ease by allowing recruiters to re-look at the previous candidate pool and how they fair against any new role and helps the team initiate recruitment process with them again.
Identifying the right candidates from a pool of applicants available on the database of a job board or an aggregator is a massive effort. The sheer number of resumes available in a database is overwhelming for manually screening candidates, and therefore, recruiters need tools to help sort and assess applications for rejection or acceptance.
The AI resume database filters help recruiters identify qualified candidates easily. These filters use keywords and other criteria to scan resumes and identify those that match the job description. Further, the filters can screen candidates beyond keywords such as job-switching patterns, relevant experience, etc. to assess suitability.
Predictive analytics leverages AI and machine learning to understand several metrics and award suggestions. It can help recruiters identify candidates who will succeed in a given role and those who will fail or leave the organisation based on data from previous hiring decisions and the candidate’s previous work experience. Leveraging predictive analytics models, recruiters can screen and process candidates on parameters such as their likelihood of accepting the job offer, commitment to stay with the company, perceived productivity.
The use of AI for screening candidates has enabled organisations to circumvent the inherent biases of recruiters and hiring teams that may affect the hiring process. Since screening is one of the first steps during the recruitment process, using AI allows organisations to screen candidates that are most suitable for the role irrespective of their race, nationality, or gender.
The process removes several difficulties in hiring by considering virtually all applications without rejecting applications for irrelevant attributes, and as a result, it also significantly reduces the time to screen candidates since ideal candidates are now considered from a larger pool.
Conclusion
The recruitment function is constantly changing and evolving. One must be aware of the latest trends and technologies to stay ahead of the curve. AI is changing how recruiters find candidates, which is having a significant impact on organisations.
Recruiters need to be able to adapt to these changes to remain competitive and ensure that they can acquire the most sought-after talent.
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