Understanding the Impact of Automation in Recruitment


Leveraging new and innovative technologies to automate time-consuming tasks in recruitment has the potential to free up resources, lower the costs associated with recruitment and produce better quality hires, faster.

With that in mind, it’s not a surprise that 80 percent of recruitment executives believe Artificial Intelligence (AI)--the brains behind automation--can improve both the productivity and performance of their talent acquisition efforts, according to Undercover Recruiter.

While automating recruiting tasks is nothing new (Harvard Business Review points to the late 1990’s as the advent of AI in recruitment), it’s certainly beginning to spill into the mainstream like never before.

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Unfortunately, as a recent study by the Pew Research Center shows, most Americans view automation with worry rather than enthusiasm. In fact, when it comes to the question of robots and computers taking over human jobs, 72 percent of respondents said they were worried or very worried, with only 33 percent expressing any sort of enthusiasm.

This clearly illustrates the knowledge gap that exists between what AI and automation are capable of today and what potential impact many believe it will have on the talent acquisition space.

In this blog, we’ll provide insights that help bridge that knowledge gap, making it easy for you to understand the true impact automation has on recruitment.

The Basics of AI, Machine Learning and Automation

If the first thing that pops into your mind when you hear “AI” is Steven Spielberg's underrated 2001 movie, then you’re not alone--but you're not exactly on the right path either.

We’re still quite a ways off from being able to produce AI that’s totally conscious and self-aware. But what we can produce today is nothing short of amazing.

Artificial Intelligence classifies any product or service that can take external outputs into consideration during their programmed operations. Essentially, AI utilizes a set of computer programs that are capable of completing tasks that require human capabilities--for instance, speech recognition, visual perception and document filtering or filing.

Artificial Intelligence is powered by a process called “machine learning.” Machine learning is a process made possible by algorithms that take advantage of If/Then formulas. These algorithms are programmed into an AI product and they tell the AI “brain” what sort of information is important to recognize and what to do when that information is presented.

For instance, this is how music services like Pandora serve you tailored playlists. The AI “brain” is programmed to recognize things like how often a song is played, which kinds of songs are skipped and which kinds of songs receive the “thumbs up” through user input. The AI “brain” then takes these external inputs and combine them with their pre-programmed algorithm to serve you music that matches your user behavior.

Which brings us back to automation. Automation describes a process AI has taken over through a combination of programming and machine learning. In this respect, AI and machine learning power automation. For example, in the absence of a product like Pandora, playlist building can be a long and tedious process. However, with AI and machine learning, Pandora is able to automate this common task normally completed by music listeners.

How Automation Works in Recruitment

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Automation takes on a number of different forms in recruitment, but at the end of the day it’s really all about efficiency.

As businesses grow, their talent demand increases, and they aren’t always able to grow their HR and talent acquisition teams at the same rate. This means that there are often more positions to fill, but the same number of recruiters to fill them.

Couple that with the complicated process of online recruitment today, and there’s quite a lot of work to tackle.

Recruiters need to be able to write thoughtful and engaging descriptions for their job ads and then post those ads across job boards, aggregators, to their company’s career page and across social media. Most job boards and aggregators require employers, staffing firms and marketplaces pay to place these job ads on their sites. This means recruiters must also monitor performance of spend against results across multiple sites and reallocate funds where appropriate to get the most bang for their buck. Failure to do so could be mean a lack of qualified candidates to consider for the position--a true waste of budget.

All of these responsibilities only really cover the top end of the recruitment funnel, or in other words, getting people to apply for jobs. Once a recruiter has received enough applicants to make a hire, they must filter through resumes to find qualified talent and then move them through the interview process, and so forth. And as we know, the ATS industry exists in order to make this second half of the funnel (moving applicants through to hire) easier to navigate.

Automation in recruitment aims to make all of these processes and responsibilities easier to manage.

For instance, two critical ways that automation should be used for recruitment are as follows:

  • Centralized Job Distribution helps recruiters automate the process of sending their job ads out to multiple sites at once and tracking their performance at both the job and source level. This gives recruiters the ability to post and monitor all of their jobs from a single platform, saving significant time.
  • Programmatic Job Advertising allows recruiters to create logic-based automation rules to manage budgets for PPC and PPA media, as well as job slots. Recruiters can set rules to start and stop spending on specific jobs or job groups, they can set parameters for reallocating funds from over-performing jobs to challenged jobs and they can ensure job slots are always filled with priority roles, among other things. This type of automation doesn’t just save time, it also saves money--allowing recruiters to spend every budget dollar in the most effective way possible--lower recruiting costs and increasing ROI.

As mentioned earlier, there are other ways automation has made its way into recruitment. Some companies provide automation software that can read and filter resumes based on specifications made by the recruiter. Others focus on automating communication between recruiters and candidates through the use of chat bots. There are even services available to automate the preliminary interview process.

It’s worth noting that, with the proper resources and a large enough budget, a company could technically automate recruitment from start to finish--but most recruitment thought-leaders and talent acquisition professionals see the concept of a fully-automated recruitment system, with no human engagement, as a recipe for disaster.

Where Automation has the Most Potential in Recruitment

Automation can do a lot of things for recruiters, but as with any powerful technology, it must be implemented properly.

Too much automation can take the human element right out of your HR department, presenting an employer brand that is cold and unattractive. But not enough automation, and your team won’t have the resources available to hit their recruiting goals. In either scenario, hiring will suffer and, by extension, so will your business.

The true potential impact of automation in recruitment lies in the proper balance between technology and a human touch. We’ve found that using a platform like Recruitics to automate and optimize the top of the recruitment funnel to produce more candidates at a lower cost helps eliminate much of the heavy lifting associated with recruitment, without dehumanizing the hiring process.

And, by having an automation platform like Recruitics that integrates with leading ATS providers such as iCIMs and Bullhorn, recruiters can gain even greater insight into their hiring funnel that allowing them to further optimize their efforts.

To learn more about how Recruitics can help make it easy to automate and optimize your job advertising strategies, sign up for a demo today.

Posted by Sal Trifilio

LinkedIn