Artificial Intelligence (AI) is the hottest thing in hiring and recruitment right now. And while Machine Learning is not AI, it is a subset of AI that trains machines to learn by automatically applying complex mathematical calculations to Big Data to find patterns without human intervention. From there, predictive models can be built and refined automatically over time as the machine learns with each iteration’s findings and as new data is introduced over time.

Basically, Machine Learning can help free up your actual human resources for other things! Get all the data! But if you’re not yet familiar with how it works or what it can really do for you and your organization, the whole thing might make you pause. Is this going to automate my job right out of existence? Can we trust the AI more than we trust our own work? It can feel overwhelming, but if you’re considering how and why you should implement an AI approach to recruitment and hiring, we’ve outlined what you need to know about supplementing your work with Machine Learning.

Finding the right candidates

So much of the recruitment process has historically been hoping for the best, using the best methods at your disposal. That meant spreading job listings around different job boards, using a range of outreach tools that would ideally bring in the perfect candidate in a sea of applicants. By automating this process as much as possible through a tool that not only handles the posting process but also collects data and makes data-driven recommendations, you’re helping to improve your candidate pipeline now and in the years to come.

These programs can take the baseline information you have (applications, resumes, and information on past candidates, hires, and current employees) and compare it against new applicants. This not only gives you a rounder sense of the incoming applicants’ fitness, but also tells you whether you’re getting the highest quality candidates from particular sources. It’s not just automating the process; the dynamic algorithms behind the process that give you even more information to make informed decisions and strategies for your hiring process.

Turning passive candidates into active ones

Candidates who come from an active job search (responding to job listings, submitting resumes on a career site) aren’t the only candidates you want to target. The perfect candidate may be someone who never sees your job posting, but would actually be open to the opportunity. These candidates are hard to reach—how do you identify and engage them?—but this is where machine learning helps as well. Sites like LinkedIn and other recruitment-focused platforms offer “predictability” tools that can help search for candidates who might fit a job opening really well, but who didn’t come in through the traditional doors. Algorithms that are constantly updated to meet your organization’s needs provide real-time scouting. And again, this has the potential to free up the person who would normally be scouring LinkedIn or other networks to do other things.

Building a better interview process

As one of the most time- and resource-intensive parts of recruitment and hiring, interviewing is arguably the area of HR that could use the most improvement. As you know, it’s a constant juggle of schedules, logistics, preparation, and wrangling post-interview information, and all on a schedule that keeps your time-to-hire in check. This makes machine learning a prime candidate for streamlining and improving that process for you and your team. By identifying better candidates based on algorithms and predictions, programs ensure that you’re using your interview spots most effectively.

Machine Learning can also factor into the interview itself, by using video and facial recognition technology to help assess a candidate’s skills and personality.

Should we fear the rise of the machines?

Terminator/Skynet jokes aside, there’s a genuine fear that automating the HR process means that we’ll lose the “human” part of it. Instead of approaching it from a replacement angle, think of AI and Machine Learning as a tool you can use to make your job better and more efficient. You’ll be working smarter, and channeling your energy into the tasks and steps that will always require human insight and interaction. And by embracing the wave of data-driven recruiting and strategy, you’re helping to ensure that your skills are evolving along with the HR industry’s. So don’t worry about robot overlords just yet—think about how they can help you become a leaner, meaner HR professional.