And now, the convergence of my two areas of interest: recruiting and AI. The companies in this space, many of which are startups, are finding novel ways to apply AI to the recruiting process. I’ll break these out into a few categories, reflecting the stages of recruiting: sourcing, assessment and candidate experience. Today I’m highlighting sourcing.
Sourcing is a natural fit for AI because it’s an expensive activity for recruiting organizations and there is so much data available on potential candidates.
In traditional talent sourcing, a recruiter (or sourcer) looks far and wide across a population to find relevant talent for an available job. Once a qualified person has been identified, the recruiter then attempts to engage this person to see if they will consider the job. There are a few obstacles here: first, the pool of potential talent may be very large and difficult to comb through; second, it may be difficult to identify best-fit candidates, and third, it may be difficult to engage or find people willing to engage.
AI is a great fit for AI because it’s a data-rich activity. Across the web, there’s social media profiles, participation on forums, articles and white papers. Content that could flag someone as a relevant fit for a job is nearly limitless. And within companies, there is plentiful data as well. Data on existing employees can suggest what skills work well for roles, and efficient mining of previous job candidates can lead to a future hire for a different job.
Here are a few companies applying AI to sourcing activities:
- LinkedIn: A leader in recruiting technology. LinkedIn Recruiter is a popular tool for recruiting organizations and AI is at the heart of the recommendations to recruiters when they are searching for new talent pools
- Entelo: A startup that applies predictive analytics to identify those most receptive to a job opportunity
- Restless Bandit: Analyzes resumes within a company applicant tracking system to match top candidates to open roles
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