The task of reaching, screening and selecting the right talent to fill the right position in the workplace intensifies each day for businesses around the globe.
A recent report from the Society for Human Resource Management, found that companies spent, on average, $4,129 to hire someone and the process took an average of 42 days.
Companies are exploring ways to make this process faster, easier and more economical, and they’re turning to the next-gen technologies of artificial intelligence (AI), machine learning and deep learning to do so. As data collection and analysis become cheaper – and as the size of human recruitment teams shrinks – companies can use data-driven techniques to improve the recruitment and hiring process.
Today’s recruitment process can be broadly divided into three main phases: sourcing, screening and matching.
In the sourcing phases, companies are using AI to help draft job descriptions that will reach a wide talent pool and eliminate any unconscious selection bias.
For instance, studies have shown that women do not apply to close-ended job descriptions that use a lot of masculine-themed adjectives and superlatives, such as “competitive,” “dominate” and “decisive.” They look for jobs that offer scope of growth, training and learning. Organizations looking to recruit more female candidates are shaping job descriptions to use more gender-neutral, balanced language or statements, with terms such as “responsible,” “dedicated,” “committed” and “dependable.” AI algorithms can assess written job descriptions and help articulate the message.
Organizations are also using AI to screen candidates as a way to speed up the process and remove any unconscious selection bias.
Repetitive preselection tasks, such as screening resumes, answering candidate queries and scheduling interviews, have high potential for automation. With these tasks out of the way, the recruiter can focus on higher-level tasks such as collaborating, engaging, personalizing and building relationships with candidates and hiring managers.
The application review process can also be automated with a combination of AI and Natural Language Processing. Recruitment chatbots can even ask a candidate a few screening questions, verify his or her qualifications and answer questions about company culture, policy and benefits. If these bots notice the candidate missing information or skills listed in the job description, they can get in touch with the applicant to seek details.
A number of chatbots on the market, including Mya, Arya and Olivia, are used in this way now by recruiters.
Screening and matching
Candidate screening is another frustrating and time-consuming exercise for recruiters. AI algorithms and bots can make the process easier by grading applicants against the experience and skills required for the position. They can also compare applicants against data from existing employees, looking at factors such as performance and turnover.
By combining this data with information from other sources, such as public data from previous employers and/or candidate’s social media profiles, the approach can paint a much more complete picture of an applicant.
AI algorithms can also be used to identify the strongest matches for open requisitions. AI can analyze multiple sources of data and evaluate applicants on various weighted factors, such as qualifications, recent activity, engagements, personality traits, passion projects, internship experience, interest/engagement levels, competency and other metrics, and rank candidates from most suitable to least. This saves time and effort, allowing the recruiter to focus on the interview and offer process.
With the use of AI and machine learning algorithms, recruiters can save hours on sourcing, screening and matching candidates, achieving higher-quality hires with lower turnover rates. The role of recruiter transitions to a strategic post, focused on talent acquisition and proactive hiring, rather than backfill.
Of course, for job applicants, this changes the game dramatically. The next time you apply for a job, your future may be in the hands of a bot! May the force be with you!
Annu Singh is an advisor at CSC. Connect with her on LinkedIn.