3 Top AI Solutions for Recruitment (and When to Use Them)

Nowadays, there is an ever-growing variety of artificial intelligence solutions available for recruiters to use. Think for instance of natural language understanding (NLU), natural language processing (NLP), AI for video interviews, and cognitive chatbots, among plenty of other helpful tools. But for recruiters who may just now be diving into the world of AI recruitment solutions, it can be a bit overwhelming to understand exactly how all of these AI solutions work and when to use each of them in their own processes.

On top of those worries, there are plenty of cases of AI solutions failing and causing recruiters to pause: Twitter bots who learn from their interactions with humans have quickly been corrupted to become racist; meanwhile, Facebook’s AI ended up accidentally creating its own language instead of being able to talk to people.

In the world of recruitment, one of the most cited examples of AI gone wrong is what happened to Amazon, who created an AI algorithm that ultimately became gender-biased, showing a strong preference for male candidates over female ones.

With cases like these happening more often than not, it’s easy to see why some recruiters might be a little wary of introducing AI solutions. But although there sometimes are mishaps with AI software, using AI in recruitment can significantly improve processes, workflow and the quality of candidates coming in.

So, let’s take a deeper look into how some of the most popular AI solutions for recruitment work and when exactly you should implement them.

1. Facial Expression Analysis

Thanks to the internet, remote work has become extremely popular in recent years. In the US alone, around 5% of all workers in each state work remotely. With more and more companies starting to offer flexibility and remote work options, that number only stands to increase dramatically in the next few years.

What this also means is that recruiters are conducting more video interviews than ever before. And now, new AI technology has made it possible for recruiters to analyze a candidate’s facial expressions during the video interview and use that to assess their personality traits. In some cases, it has even been proven to increase candidate diversity!

However, recruiters need to use this technology in the right place at the right time. Some critics say that people who know that their facial expressions are analyzed may show self-consciousness or self-doubt, which could potentially negatively affect their scores.

But if you’re a high-volume recruiter without a ton of time to interview candidates in-person, or if your company hires a lot of remote workers, these facial recognition tools can help you screen candidates faster.

2. Sourcing & Matching Candidates with AI

One area where AI is massively helping recruiters is the sourcing of candidates. Whether it’s simple outreach, candidate matching, or even candidate rediscovery, there are a wide array of AI tools available to find the best candidates more easily than ever before.

With these tools, recruiters now have the ability to automate their sourcing and create a wider candidate pool. This same automation technology also helps engage prospects by being available 24/7 and sending candidates messages throughout the process.

Does your company forget about old candidates when posting a new job? Just because they weren’t a fit for the last one doesn’t mean their talents can’t be used elsewhere in a different position. AI technology can also now screen your existing candidate pool for strong past candidates that could be a good fit for a new role. 

When it comes to candidate matching, AI solutions (like pre-employment assessment tools for instance) are also being used to optimize the candidate screening process, using AI to tailor candidates to specific positions and ensure you’re finding the right person for the right job.

3. Cognitive & Rule-Based AI Chatbots

Chatbots are quickly changing the game for recruiters across industries – especially for companies with high-volume recruitment needs. There are two types of chatbots that can help immensely in screening and scheduling candidate interviews: Cognitive chatbots and rule-based chatbots.

Cognitive chatbots usually use a mixture of AI, machine learning and natural language understanding (NLU) capabilities to better understand the natural human dialogue. Rule-based chatbots are also effective, allowing their operators to implement certain rules and behaviors according to their industry or needs while being flexible enough to adapt and change those rules when necessary.

Cognitive chatbots enhanced with cognitive technologies are designed to accomplish more complicated tasks that traditionally only humans have been able to complete, such as planning, learning, and reasoning. Meanwhile, rule-based chatbots are designed to easily complete simple tasks, help automate workflows, and even schedule interviews on their own.

This is why both rule-based and cognitive chatbots are ideal for pre-screening candidates and choosing the best fits for the job — saving recruiters tons of time to focus on more important duties.

A final word

Ready or not, AI tools are rapidly changing the entire recruitment process. And while these AI recruitment solutions can all be effective, it’s important for recruiters to remember that each of these tools has very different purposes and should only be used specifically for those, rather than just implementing a ton of AI solutions or platforms simply for the sake of having AI.

When used correctly, however, AI solutions can dramatically impact a business’ bottom line from an ROI standpoint. For example, by implementing rule-based chatbots to screen and schedule candidates, some businesses have been able to cut their time-to-fill between five and 10%, saving up to millions of dollars for high-volume recruiters.

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Between a high ROI, increased efficiency and better candidate pools to choose from, there are plenty of reasons to implement AI recruitment software into your operations. The only question remaining is, when will you get started?