Machine Learning In Recruitment

The recruiting industry is constantly evolving. The way companies seek new talent is drastically different from how it used to be decades ago. Today, the recruiting process is almost entirely digital and utilizes the latest technology to maximize efficiency. 

While some of these innovations have made the recruitment process more accessible, others have created challenges for recruiters and job seekers. 

Machine learning is one of the tools helping companies find the best candidates to fill their openings. Learn more about how machine learning impacts the recruitment industry and how it can reduce your hiring costs by thousands of dollars. 

What Is Machine Learning?

Machine learning is a segment of artificial intelligence (AI) and computer science that uses algorithms and data to mimic how humans learn. In short, computer programs become more intelligent and more accurate over time. Machine learning has been a vital component of AI and the world of data science. By analyzing information at an extremely rapid pace, companies can make more informed decisions based on their data.

A familiar example of machine learning is speech-to-text. Over time, machines have learned to note what sounds match certain words and expressions to make search more seamless for people. That’s why your iPhone responds when you say “Hey Siri” and why you can use the voice search option on Google. 

Essentially, these machines can process data much faster than humanly possible. As a result, they can create a precise data analysis in seconds for specific criteria. Recruiters and companies can use the speed and accuracy of these machines to make better decisions when hiring. 

How Is Machine Learning Used in Recruitment?

Here are some common examples of how machine learning is transforming the recruiting sector:

Easier Job Postings

One of the most tedious tasks of a recruiter is writing and publishing job posts on numerous websites and social media. Machine learning technology can streamline the job posting process, making it easier and faster to publish job listings across a wide range of channels. 

Machines also can analyze the data of those who visit your website or listing to help create better targeting. For example, if most of the people visiting your listing are females aged 25-30, you can use machine learning to create targeted ads on social media and recruiting platforms to attract the best fit. 

Candidate Sourcing

Finding talent can be a daunting task for recruiters. Luckily, machine learning can help source top-tier candidates with minimal effort. For example, recruiters can use credentials from their clients to access employment databases from sites like CareerBuilder and Indeed.com.

With this data, an algorithm can sift through different people to see who has the credentials to fit a particular role. After collecting a decent-sized list of potential candidates, recruiters can reach out to them via email or LinkedIn to try and spark interest in some of their open positions. 

Screening Resumes

Reviewing candidate resumes is another time-consuming task designated for recruiters. Screening through resumes can take hours, particularly if the position attracts many applicants. Machine learning can help by automating the process and filtering out candidates that don’t qualify for the job. 

These algorithms help pinpoint specific candidate criteria, such as traits, past work experience, and other skills that are relevant to the job listing. As a result, the screening process is unbiased and purely based on data. Not only does this save recruiters time, but it also makes for a better experience for applicants. 

Assessing Applicants and Pre-Hiring

After shortlisting candidates, recruiters will set up interviews and assessments to determine whether they’re the right fit for the role. While there are several tools recruiters and hiring managers have at their disposal for this part of the process, machine learning can offer additional help. 

For starters, a program can analyze a candidate’s soft skills to see how well they’d match up for the job. Meanwhile, algorithms can determine which other character traits would make up the best candidate for the listed position. 

Furthermore, this data can also indicate whether or not a candidate would be a good company culture fit. 

Engaging With Candidates

Cultivating connections with your candidates is vital, especially if you’re trying to attract top talent. If you’re in the middle of the hiring process and suddenly go quiet, the candidate might look for opportunities elsewhere. That said, you don’t always have time to email and chat with your candidates if you have a busy schedule. 

That’s where machine learning comes in handy. These AI bots can offer more ways for your candidates to engage with you and your company. Some chatbots do an excellent job of imitating real-life human behavior, so applicants get an authentic experience when engaging with them.

These programs can help keep candidates interested in your business and free up time in your schedule. 

Reducing Recruitment Costs

Since machine learning can automate most of the recruitment process, it can also help bring down the cost of attracting new candidates. 

Recruiters and hiring managers don’t need to waste time on mundane tasks such as creating listings, sifting through applicants, and sourcing talent from third parties. As a result, they can allocate their time and resources toward more practical and profitable tasks. 

Furthermore, open positions fill much faster and more effectively than with standard recruiting tactics. According to Glassdoor, the average cost to hire an employee for a company with 1-500 employees is around $4,000. Meanwhile, the average time to fill an opening is about 40 days.

If you use machine learning properly during the hiring process, you can potentially save your company thousands of dollars and many days worth of time.

What to Expect With Machine Learning and Recruiting in the Future

Given that hiring is a delicate process, many companies and recruitment firms don’t like the idea of machines doing all the work. Human-to-human interaction is still necessary for job posters and applicants, so it doesn’t look like AI will completely take over. However, we can expect to see several new trends in the recruitment space, thanks to machine learning. 

Here’s what to expect in the next 3-5 years:

• Faster data processing
• Easier job posting/applying
• Better automated candidate engagement

Conclusion

Machine learning and AI are making a significant impact on how we list and apply for jobs. They make it easier for recruiters to find suitable candidates and streamline the entire hiring process.

Are you a recruiter or hiring manager looking for help finding the right people for your organization? Get in touch with ScoutLogic today. We offer countless resources for recruiters and hiring managers, and we’d love to see how we can help.

David Garcia

David Garcia, co-founder and CEO of Scout Logic, is an industry leader in the bulk background check world. With his strategic acumen and expertise in the HR sphere, specifically in hiring, recruiting, legal compliance, background checks, and resume screening, he’s an invaluable asset and consultant.

David's counsel extends across the boards of ScoutLogic, YipitData, and Supplier.io, drawing from his impactful stints on the boards of Infutor and Avetta. With an extensive 25-year journey, he champions unparalleled B2B commercial leadership within data & analytics, significantly shaping the HR landscape.