Today’s competitive world makes it difficult to find the appropriate people quickly. Finding qualified applicants in the future will rely on how the hiring teams and recruiters automate their processes.
96% of recruiters believe AI can improve talent acquisition and retention, according to research. But as of 2018, just 13% of the HR staff has adopted AI in recruitment. However, AI in recruiting has a lot of promise because, by 2023, more than 55% of recruiters expect to use it.
This article explains how AI in Talent Acquisition will assist businesses in the long term and boost efficiency among hiring managers and recruitment teams.
Some of the key characteristics of AI in talent acquisition are described below.
One of the most difficult responsibilities for recruiters is the screening of candidates. Recruiters get more than 250 resumes for a single position, and 75% of them are unqualified. For one vacant position, a recruiter screens applicants for 23 hours; more than 60% of this effort is spent making sure the résumé is the right one.
In a survey, 52% of talent acquisition leaders stated that selecting candidates from a wide pool of applicants is the most difficult aspect of hiring.
Finding the ideal applicant for an open position requires a lot of work on the part of recruiters who must spend a lot of time sourcing candidates from various job boards and social media. Organizations must locate and hire candidates in the shortest possible time in today’s competitive environment, and AI is the ideal tool for this.
Recruiters will use AI to go through the millions of resumes on various job boards and social media platforms like LinkedIn, and GitHub. Additionally, an AI tool rates and lists the best applicants according to the recruiter’s search criteria, which improves the recruiter’s efficiency in finding candidates.
The AI tool’s ability to extract job criteria from the job description and add them while searching the database is another important benefit. To select the best applicants, AI takes into account a number of variables, including candidate education, experience, projects, and skillsets that fit the job criteria.
Candidate Selection Using Niche Websites:
Recruiters are aware that it might be challenging to fill some roles in the fields of data science and Machine learning. Such positions are filled through internal hiring or reference checks. However, passive job seekers are active on some specialized websites like GitHub, but it is extremely difficult to recruit from these sites.
One of the most well-known locations in the IT sector where applicants from all backgrounds join the platform to learn, share their opinions, and build software is GitHub.
However, without utilizing any Boolean tools, such candidates may be found by applying the AI tool. The AI algorithms will thoroughly search these websites and use a variety of criteria to identify applicants according to their skill set and languages of proficiency.
Targeting and Posting Jobs:
Previously, Talent Acquisition had to manually add the positions to the dashboard after logging in, which took a lot of time. However, customized advertising via Artificial Intelligence is transforming the job posting process. AI Programming is done so that the position is listed and targeted to the particular applicants who are qualified for it.
A candidate’s abilities, such as history, demographic profile, and social networking sites like LinkedIn may all be used for Target advertisements. The job, a candidate is interested in and could take in the future will be seen in their search history.
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