Ultimate Guide of AI Recruiting Terms and Why You Need to Know Them

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According to the latest research , 24% of businesses use artificial intelligence (AI) in their hiring process. However, it’s becoming more common as companies try to find better hiring methods.

But even though it’s becoming more common in the employment market, recruiters and hiring managers are still confused about what AI is and how it’s used in recruiting.

Keep reading, and we’ll break down all of the common AI recruiting terms you need to know to find the most qualified candidates.

Artificial Intelligence

AI is one of the most foundational terms, but it’s essential to understand because many people aren’t quite sure what it means. And, no, it doesn’t mean that a robot will take over your job. Instead, AI is a powerful machine that learns how to mimic human abilities. This could be like scanning a resume, solving a problem, automating a repetitive task, learning from data, or offering solutions to problems.

However, to work correctly, AI needs a lot of data to read. For example, think about when you’re scrolling through Netflix trying to find something to watch. All your previously watched shows and movies act as data that go into Netflix’s AI algorithm. AI can identify patterns in your viewing habits and look for similar ways in other shows or movies that you might be interested in. This is how it can provide accurate suggestions.

However, AI is also popular in other aspects of our lives, like with Tesla’s self-driving cars, Apple’s Siri, or Google’s Alexa. But in recruiting, AI is used in more of a problem-solving or learning function.

Most of the time, AI technology is designed to automate repetitive tasks to help save time. For example, if you have too many resumes to screen, AI can use the data you tell it to look for and quickly scan all the resumes and figure out which candidate is a better fit based on the information you gave.

However, other companies use AI technology for recruiting chatbots, interview assessments, or sourcing as a service. 

Machine Learning

Machine learning is an application of AI which looks for code patterns. You can program machine learning to look for specific patterns. If you put more data into the program, it’ll be able to adapt better and provide more accurate outcomes.

In recruiting, you can sometimes use machine learning to screen resumes and rank them. However, to do that, a recruiter would need to plug in the requirements, keywords, and skills to look for and what qualifications a hiring manager are looking for.


An algorithm is a type of formula or a procedure that goes through specific steps to solve a problem or come up with a solution. For example, Spotify uses an algorithm based on your listening data to determine what songs you might like on your Release Radar each week. When a user says they love or hate a song, this input goes into the algorithm so that it can offer better suggestions.

In recruiting, one of the most basic ways you can use an algorithm is through a Boolean search or keywords. However, you’ll need to identify qualified candidates from a large applicant pool. You’ll want to input your search terms, and then you’ll get an output of candidates that match those requirements.

For example, you could use this when sourcing passive candidates. If you’re sourcing a software engineer, then you’ll put in what keywords you want to be on the engineer’s resume. That way, the algorithm will go through all the candidates and pull out the ones that meet the requirements that you set.

Natural Language Processing

When you’re using a computer, it uses natural language processing (NLP) to communicate what you want it to do. It can understand and generate speech and text without using programming languages.

You can also apply this in your recruitment process. You’ll see it most commonly in AI recruiting assistants, like chatbots. These chatbots can read what text a candidate is sending, for example, and provide any answers or feedback based on that. These chatbots can be great at answering simple questions that candidates have so that recruiters can focus on other, more critical tasks.

People Analytics

While this isn’t an AI term, you can use it with other types of recruiting technology. People analytics uses data analysis techniques. These techniques can help improve, understand, and optimize the people-facing side of your business. When you use it in recruiting, it can help you know how to improve your candidate experience better.

People analytics will help you connect the people data with different types of business algorithms. These will be aligned with your goals, like increasing revenue, lowering hiring costs, or improving the candidate experience.

Sentiment Analytics

When a computer program can decide on a subjective opinion, emotion, or an emotional effect, it can translate it into written communication. This is sentiment analytics.

For example, if you’ve used Grammarly, you might have noticed that their algorithm will analyze your text and let you know what type of emotion you’re conveying. For example, you might be writing confidently or persuasively. This is investigating your intended effect.

In recruiting, you can also use this. People use this to identify the potentially biased language in the job descriptions before you post them on job boards. The algorithm will scan your job description and let you know what the tone of your words conveys. For example, you might be writing an aggressive job posting that deters women from applying.

When you analyze these words and improve your messaging, you can work towards hiring a more diverse workforce.

Predictive Analytics

In general, recruiters might hear predictive analytics as a catch-all term. It’s used to talk about an equation or algorithm for a data set. You can use these data sets to create a predictive model to showcase what might happen in the future.

For example, if you’re using this in recruiting, you can use this to screen a candidate’s resume or profile and predict how successful an employee they would be. You can use this to analyze interview scores, resume data, or hiring assessments.

You can also use this to predict which existing employees are more likely to quit. Based on this, you could start building a talent pipeline and preparing to find job seekers so that your HR is more prepared to fill that open position if they do leave.

Start Using Recruiting AI Technology Today

Eighty-four percent  of business leaders expect AI to help them gain a competitive edge in future hiring. If you don’t want to be left behind, you should learn more about the terms that we talked about above.

However, if you still struggle with the terms or concept of AI in recruiting, you don’t have to learn them. Recruiter.com can help you by managing the software for you! We’re talent acquisition professionals who have powerful AI sourcing software that can help clients find candidates for even their most challenging positions.

If you’re interested in learning more about our sourcing as a service and how it can improve your recruiting process, contact us today !



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By Alyssa Harmon