Five AI Terms Every Recruitment Pro Should Commit to Memory

As the term artificial intelligence swirls around the recruiting and talent acquisition industries, many other buzzwords associated with it are starting to flow in as well. It can be easy to get these technical terms confused or use them in the wrong instance. However, with this quick guide, recruitment pros better understand all the verbiage and never risk misunderstanding or misusing AI terminology again.

1. Artificial Intelligence

In the most basic terms, AI can be defined as a computer system that can learn in a deeper way and predict an outcome. Examples of artificial intelligence surround us every day. AI is in our Amazon purchasing suggestions, Netflix new show recommendations and even the predictive text on your smartphone messages.

What it can do for recruiting:

Some examples of AI in recruiting include technologies that have the ability to screen resumes for recruiters and engage candidates through a chatbot feature.

2. Machine Learning

A computer program that is capable of machine learning can learn and act without being explicitly programmed to do so. As more data is input into the program, it is then able to adapt its outcomes to be more accurate.

What it can do for recruiting:

Machine learning in recruiting can be used to rank candidate resumes to give recruiters the most qualified applications based on the data and information they provide the program. The more the system can learn about the company and the position requirements, etc. the better results it presents recruiters.

3. Natural Language Processing

A computer system or program with natural language processing (NLP) can understand and generate text and speech without the intervention of programming languages.

What it can do for recruiting:

You can see this technology being used in recruiting assistants that have the ability to communicate with users in real-time providing answers, feedback and recommendations.

4. Chatbot

A chatbot is a computer program designed to simulate conversation with human users, typically over the internet. Examples of chatbots can be seen anywhere from customer service to helping individuals book travel.

What it can do for recruiting:

Instead of recruiters struggling to find the time to talk to each candidate, chatbots can be used, alongside NLP, to respond to and engage candidates while they go through the application process.

5. Sentiment Analysis

Sentiment analysis is a programs ability not only to scan and determine keywords but also categorize the emotion, meaning and opinion behind phrases and sentences.

What it can do for recruiting:

This type of program can be used to scan candidate resumes for not only keywords but concepts hidden in the text. Additionally, the program can help better assess for cultural fit, personality and job requirements.

It’s hard to avoid using these terms nowadays as AI becomes more prevalent throughout the industry. By committing these definitions to memory, you’ll be able to keep up and better understand the new technology emerging in the field.

This article originally featured on Money Inc.

About Noel Webb:

Noel Webb is co-founder and CEO of (Your Cognitive Recruiting Assistant), the latest project from his role as Director of Product Innovation at Innosphere. A veteran of business development and out-of-the-box thinking, Noel has been a leader in his roles over the years for several companies, including Bam Digital, SpeakFeel and Agnition. During his career as a technology leader, Noel has developed a passion for products and innovations and has been the driving force behind products such as: OOLYO, Tech & Design and TeamHQ. In addition, Noel has been a strategic advisor for high profile clients such as Torstar Digital, Syngenta, Toyota and Modis and helped them to build a product-driven approach to business.

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.