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6 Uses of AI in the Recruitment Process

Editor’s Note: This is a guest post by Michael Deane. His opinions are his own. 

We’re witnessing the rise of the machines at the moment, as AI, ML, and other hi-tech abbreviations are taking the world by the storm.

Many people genuinely wonder whether robots will steal their jobs somewhere in the near future, while imaginative sci-fi lovers believe that androids will develop a mind of their own and start running amok very soon.

Until either of the two scenarios happens, it’s safe to conclude that AI is a disruptive technology which can assist us with countless everyday tasks and save us a lot of time, while ensuring that all this isn’t done at the expense of quality.

Recruiting new employees can be a challenging task. With AI picking up the slack and performing the tedious paperwork and repetitive administrative tasks, you’ll have more time to focus on picking the right person for the job.

1. Writing effective job descriptions

The best candidates stay on the market for 10 days only, which means that there’s a very short window of opportunity for you to grab them.

Creating and posting highly-targeted job ads is essential for getting in touch with the right people. While many companies require their candidates to put their best foot forward and show what they’re made of, those very same companies forget that they’re being scrutinized too. Why would top talent even consider applying for a job with a lame, sub-par description?

So, if you want qualified applicants to submit their resumes, you need to present your company in an attractive light.

And you’d better let AI do the talking.

There are tools which use advanced algorithms to analyze the structure of effective job ads and identify relevant linguistic patterns. This allows them to use targeted words and phrases which hit the right notes with the best and most qualified talent for a particular opening.

The more job ads are fed to this smart machine, the more refined it gets in crafting compelling job descriptions. Subsequently, a job description which paints an accurate picture of the candidate who fits your needs will eliminate unqualified applicants and prevent you from wasting your time on less than perfect employees.

2. Screening resumes

After you post your perfectly structured and polished job ad online, you can expect that you’ll be flooded with resumes that you’ll have to go through.

That’s a good thing, right? I mean, you’ve managed to attract a lot of potential employees, eager to start working for you.

Don’t get your hopes up just yet. Stats say that approximately 80% of the CVs received are a far cry from being a perfect match for the job. People tend to unselectively blast their resumes in hopes that they’ll get lucky.

The trouble is that this mundane task is particularly time-consuming, and yet highly-qualified recruiters have to perform it instead of focusing on more important things – no wonder that 52% of talent acquisition leaders name candidate screening as the most challenging part of their job.

Again, AI saves the day (many days, to be more precise) as a machine can be programmed to search for relevant keywords and language elements which have previously been used in successful applications.

But, in order for AI to be able to accurately eliminate inadequate applications, it needs a huge amount of data which is why it’s of vital importance to keep tabs on and record all your hires. For example, the algorithm will in time learn how to tell the difference between applicants who turned out to be great employees and those who left the company shortly after being hired. This ability to predict the outcome of each individual hire makes it perfect for the screening process.

Subsequently, recruiters won’t have to handle this part of the process, which will give them more time to prepare for the interviews and actually asses their candidates.

3. Analysing applicants’ personalities

It’s a fact that many people tend to fabricate and make things up. And saying that they’re particularly inclined to do this when they’re applying for a job would be an understatement.

The reality is that a shocking 85% of applicants lie on their resumes. And while there are behavioural techniques that can help you spot a dishonest applicant, it’s too complicated to conduct such a procedure. This is a particularly big issue for companies which heavily rely on the distributed workforce.

Luckily, AI has the answer to this problem too. Namely, big corporations such as Dove or and Unilever already take advantage of a sophisticated AI-powered technology for assessing their applicants’ personality traits based on analysing their facial expressions during video interviews.

4. Using chatbots as assistants

Chatbots are mainly used in the field of customer support to answer frequently asked questions, as well as in HR to allow employees to book their paid vacations and days off. Similarly, they can help in the recruitment process by finding the available time slots for interviews and sending invitations automatically.

But, their full potential can be achieved by involving them in the direct communication with the applicants. Sometimes candidates don’t answer all the questions from the application form, and chatbots can collect the missing information from them and update their application. Then, there’s also the factor of improving candidates’ experience by providing them with answers to their questions about the interview and the company.

However, the synergy of NLP and AI creates an even more advanced chatbot which has the ability to talk to candidates and analyse their feedback in order to establish whether they possess a set of skills necessary for the particular job they’re interested in. Also, if there are openings in the company for which the applicant is more suitable, this chatbot notifies the recruiting officers and recommends them.

5. Preventing biased hires

People are biased, and there’s little anyone can do about it. We can try to make impartial choices, but sometimes certain subconscious factors interfere and make it impossible.

Machines operate according to some predefined and standardized rules, and many AI advocates insist that this is what makes them fairer and practically unbiased.

On the other hand, AI sceptics claim that since these tools are built by people who are intrinsically biased, they will most certainly adopt such “reasoning”. Another argument which speaks in favour of their claim is that since AI expands its knowledge by learning from the patterns, it will also “pick up” the bias together with other information.

In practice, this means that if a male team of developers built a screening AI tool, the odds are that they transferred their biases to it, simply by marking certain words mainly used by male candidates as more effective.

Companies which develop AI software can, however, ensure that these biases are prevented from replicating by having a safeguarding procedure in place.

6. Candidate nurturing and creation of a talent database

As companies collect and analyse a vast amount of data on their candidates, the best thing they can do is create and maintain a talent database where all the information about every applicant will be stored.

Such a database can come in handy when it’s time for another round of recruitment – the candidates who weren’t initially hired could be taken into consideration the next time there’s a similar opening.

Moreover, AI tools are used to gather additional information about the candidates on social media and other websites and update changes. This way they will always have their own internal talent pool from which they can recruit qualified candidates and get in touch with them the minute there’s an available opening which fits their skills and interests.

AI can speed up the recruiting process and help companies find the employees who will contribute to their growth.

Michael Deane

Michael is a marketing executive by day, passionate about all things AI and deep learning. By night, he is a huge Lakers fan, a secret detective fiction reader and a great cook.

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