How Machine Learning Is Changing Recruiting

Artificial Intelligence (AI) has been reshaping the world in the last few decades. It’s changed the way we live and do business, influencing everything from transportation to medicine. Human resources didn’t escape this trend, which made recruiting a much more difficult and competitive niche than what it used to be.

A study proved that it takes an average of 27 working days to make a new hire, but the best candidates are off the market within 10 days. In such circumstances, it is becoming increasingly important to embrace machine learning as a recruiting mechanism. In this post, I will show you 5 ways how AI is influencing HR.

Traditional recruiters have a problem sourcing the best candidates from a vast talent pool. This is not an issue with machine learning as it uses advanced algorithms to detect only the most appropriate prospects.

It doesn’t only analyze resumes, work experience, and education, either. Using AI, you can monitor thousands of candidates through their social media profiles or blogs. This gives you a deeper insight into personal preferences of each individual and helps you to find a perfect match for your team.

For instance, Entelo is HR software capable of targeting professionals who have a 30% likelihood of changing jobs within the next 90 days. It analyzes over 70 predictive variables to come up with the best solution for your unit, giving you a comparative advantage over HR competitors.

Years of experience in HR and headhunting made me realize that the best recruiters are those who work in the same niche or industry for a long time. Experienced HR officers can recognize talented candidates because they know exactly what kind of profile fits a specific position within the company. However, most organizations don’t have such competent recruiters.

On the other side, machine learning has the power to analyze an entire history of HR activities in your company. As the matter of fact, it can also analyze dozens of similar organizations and compile an overview of the best features for each role separately.

This kind of tailored approach generates better and more accurate results, improving the overall retention rate and employee satisfaction. It’s an important upgrade because it costs between $7 and $40 thousand to replace an employee – depending on his position in the hierarchy.

Manual work is what slows down traditional HR managers. They need to complete a lot of paperwork, communicate with job applicants, and schedule the first interviews. It’s a time-consuming procedure that can easily be reduced with the help from machine learning.

The whole process can be automated to speed up recruiting, which is a win-win situation both for the applicants and employers. Chatbots play a major role in this field because they can take over communication with all candidates and keep them informed about the job specifics.

Paradox is only one example of the new recruiting technology. It’s a multichannel AI assistant that engages with potential candidates by handling tasks such as interview scheduling and responding to general inquiries regarding the company or position.

With all that manual work taken over by machine learning, HR managers have enough time to actually focus on real work. They can prepare thoroughly for interviews with candidates who pass the first elimination phases and create conditions for a comprehensive discussion with potential employees.

Machine learning also cuts the majority of operational costs because you don’t need the additional workforce to complete tasks that can be done automatically. According to the research, costs of non-automated recruiting are lower productivity (41%), higher administrative expenses (35%) and poor candidate experience (17%).

Bearing this in mind, it is clear that you should embrace AI to improve the overall productivity of your HR staff. Without talent sourcing, resume screening, and candidate shortlisting, the recruiter’s job becomes much more efficient and precise.

Discrimination in recruiting, unintentional or not, has always been a big issue. James Mayfield, a headhunter at CareersBooster, recently noted:

“Traditional recruiting is burdened with discrimination-based controversy. It’s easy to turn down a candidate just because you don’t like his race, age, gender, or any other non-professional feature. However, I strongly believe machine learning will eliminate discrimination from hiring procedures.”

AI conducts unbiased candidate analysis based only on job-related criteria. In such circumstances, it becomes irrelevant whether the applicant is African American, Caucasian, or Asian. Machine learning treats all candidates equally, so you can hire employees based on professional capabilities, not prejudice.

The shortage of talent forced HR teams to use machine learning in order to find the right candidates more accurately and in a timely manner. Companies that use AI in recruiting can stay competitive long-term, while those that stick to traditional hiring techniques will probably lose pace.

Eva Wislow is a career coach and HR Executive from Pittsburgh. She is on a mission to help people find their true calling. Eva maintains a strong interest in bringing the digital revolution in human resources. She finds her inspiration in writing and peace of mind through yoga. Connect with Eva on Twitter.

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