4 Ways to Use Artificial Intelligence in Recruiting and HR

Business.com / HR Solutions / Last Modified: May 16, 2017
Photo credit: Mopic/Shutterstock

There are so many resumes to review and candidates to interview that HR can't keep up. Learn how AI and machine learning can transform your Human Resources department.

Recruiting and human resources are probably some of the most complicated internal business processes that a company might have. What separates them from the rest of the bunch is that they require constant communication: interviews, screening calls, complaints management, etc. Just look at your HR’s Skype contact list and you’ll realize what we’re talking about. The only department that’s theoretically more slammed in terms of communications is customer care.

And that’s why human resources operations are the perfect proving ground for artificial intelligence and machine learning technologies. Modern AI advances can eliminate a great chunk of HR work and leave plenty of room for what’s really important: unobstructed communication with employees and prospects.

After all, it wouldn’t make much sense to call it ‘human’ resources, if it was all about the machines. Let’s take a look at some of the very promising uses of AI-based solutions in HR and recruiting.

Employee Retention

With people acquiring skills, getting promotions and overall becoming more valuable assets, it’s crucial to have them stay on board. Their experience and expertise are invaluable. AI-based solutions that let you detect employees who are about to leave the company are pretty common these days.

In fact, some employee retention solutions, based on artificial intelligence, have demonstrated a 98 percent accuracy rate, when it comes to predicting risk categories of employees.

These solutions also open up additional opportunities for the company, employing them. You can decide whether a promotion is appropriate for someone who’s about to leave or on contrary, decide to promote another person, knowing full well that the initial candidate will skip the offer. It all depends on the data that you collect and the logic of algorithms, which make the final call and risk assessment.

Candidate Lead Scoring

Services like Pomato use artificial intelligence to scan through heaps of resumes to match them with the most appropriate positions within the company. Services like this can also be used for lead scoring, when you identify the most desirable candidates to focus your efforts on.

All of this candidate info can be reverse engineered to create the perfect job posting, which will attract the most relevant and professional candidates. In fact, HR companies are already looking into ways of accomplishing this.

Performance Evaluation and Predictions

You’ve likely heard of the famous ‘Moneyball’ story, which used sabermetrics (a fancy name for baseball analytics) to identify the most desirable baseball talent.

We now know that one of the major baseball teams purchased a CRAY supercomputer sometime ago. And we’re pretty sure that the purchase was made not to play Mario, but rather to use the power of statistics and AI to empower that team’s performance evaluation and predictions.

This is the perfect example of a human resources use case, which takes employee performance over time and predicts how it’s going to change. This can be applied to any HR case, where a specific set of KPIs is used to evaluate employee performance.

Of course, right now the array of such cases is pretty limited, because not many industries have a similar statistical performance backbone, as baseball does. But with certain alterations it can be used for customer care representatives and sales managers, because their performance is KPI-based. Overtime, the pool of such use cases will only grow wider, as more companies and niches adopt statistical approach to performance evaluation.

Unconscious Bias

Recruiters and human resource professionals are still human. We’ve come a long way, as a species, but our subconsciousness still controls a significant chunk of our lives. We might not be aware of these biases or subconscious urges, but they do affect our decision-making. HR is not an exception. That’s why many highly experienced HR professionals agree that recruiting and employment decisions are often made with biases. AI and machine learning technologies already deal with this problem through products like Sunstone, which refine the onboarding process to remove any potential biases.

How much should you rely on AI?

There are plenty of AI-based solutions that already help with onboarding, candidate screening and employee performance evaluation. These products greatly shorten the onboarding process and increase the chances of someone staying happy within the corporate structure by matching jobs with the most appropriate candidates.

However, it’s important to remember that ‘H’ in ‘HR’ still stands for ‘human’. There are many factors that a company has to keep in mind when automating specific HR and recruiting processes. How? When? Why? These questions are important to remember when giving up a certain part of your HR process to a machine. Are you sure that you want AI to vet your candidates? Are you sure that KPIs are the only thing that matters when it comes to evaluating an employee?

Companies have to exercise caution when implementing automation routines for HR processes, which might require a ‘human touch’ or a decision that goes well beyond the binary world of artificial intelligence. A machine can’t have a hunch.

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