Data & Automation

5 excellent cases for using AI in recruitment

October 24, 2019

5 excellent cases for using AI in recruitment

You’ve probably read the endless headlines: artificial intelligence is going to change the way we work, AI is out to get your job, we are on the verge of a new era with AI technology. In many ways, the headlines speak the truth. Artificial intelligence can and will change many industries around the globe, including recruitment. What you might be less familiar with, though, is how that will actually happen, and why. In this article, we’re going to look at some use cases for AI in recruiting, and how it will benefit your hiring strategy in the future. 

The benefits of AI in recruitment

We touched on the many benefits of AI recruiting in a previous article, but let’s have a quick recap of how artificial intelligence will help you and your recruitment teams before we dig into some core use cases.

  1. It will reduce or eliminate time-consuming and redundant tasks.
  2. It will allow teams to do more and better work with fewer human resources.
  3. It will help to improve the quality of hire through job matching, standardized process, regular analysis of recruitment data, and incremental process improvements. 
  4. It will reduce cost-per-hire by eliminating inefficient sourcing and processes. 
  5. It will greatly reduce operational burden on recruiters, freeing them up for more strategic and human-driven tasks. 
  6. Company knowledge and improvements will be automatically retained and applied to subsequent tasks and processes. 
  7. It will provide recruitment teams with powerful tools to tackle the most challenging, time-consuming, and expensive tasks. 

Of course, whether or not your company reaps these benefits of AI recruiting will depend on how you use it, and which artificial intelligence tools you leverage to augment your work.

5 ways to use AI in recruitment 

Artificial intelligence works best when it’s applied to repetitive jobs and processes, and when processing and analytics abilities are deployed to encourage continuous improvement. Improving processes, automating jobs, and leveraging data for continuous growth are all core themes you should be thinking about when adopting AI recruitment tools at your company. 

Let’s take a look at some AI recruitment use cases. 

1. Establishing a fair recruitment process

Creating a recruitment process that’s fair and emphasizes diversity should be a priority for every recruitment team. Not only does a transparent and fair hiring process lead to a great candidate experience, it generally leads to a better hire in the end. That’s because being fair often means being objective, and looking at candidates based on their likelihood to succeed. 

AI recruitment is particularly well suited to encouraging fair recruitment because it leverages objective data to make decisions. Recruitment platforms equipped with artificial intelligence are able to collect and analyze thousands of data points from every candidate who applies for a position, and use historical evidence to make a decision on who to shortlist. 

AI in recruiting can also be used to gather and analyze candidate information through means like video recruitment, structured interviews, resume screening, talent assessments, and language analysis. 

As AI is integrated into more and more parts of your recruitment strategy, this ability to take subjectivity out of the process becomes stronger and more consistent. The result is a near removal of bias from the majority of the recruitment process, and stronger diversity within your team. 

2. Reducing errors in the recruitment process

Another critical use case for AI in recruiting is using it to reduce simple errors and omissions in the recruitment funnel. Unfortunately, due to the sheer volume of applicants that many companies receive, it’s easy for things to fall through the cracks. This might be something as simple as forgetting to reply to an email or question, or it could be as significant as entirely missing a qualified application due to human error. Either way, the result can be a poor candidate experience, or missed opportunities to hire a top candidate. 

Recruitment tech that leverages AI such as Applicant Tracking Systems (ATS) or chatbots can identify these problem areas, and ensure that they stop happening. This is accomplished by a combination of analytics and process improvements. AI can continuously monitor and analyze a recruitment process for errors and omissions, and suggest improvement areas and new processes to alleviate issues. Likewise, messaging applications like chatbots can be used to ensure that any time a candidate asks a question or sends an email, there’s somebody on the other end to answer. 

Through a series of continuous monitoring, improvement, and automation, AI recruitment can be used to dramatically reduce the number of errors in the overall hiring process. Less errors means a better experience, means a happier pool of applicants, which means better results for your company. 

3. Increasing the use of analytics and metrics

All of this talk of monitoring and analyzing the recruitment process brings us to perhaps the core use case of AI in recruitment: leveraging the abundance of analytics, metrics, and data that is available thanks to recent advances in digital technology. As you likely know, the last decade or so in many businesses has been dominated by the collection of big data. Thanks to an explosion of digital technology and different ways of tracking and collecting information about clients and candidates, many companies have an absolute surplus of data with which to work. 

Artificial intelligence is the tool for turning that data hoarding into actionable processes and metrics that drive real business results. AI recruitment, therefore, is the next frontier for leveraging analytics and metrics to accomplish better results from your hiring. 

By its nature, AI technology is only as good as the data that you give it. Companies that have been diligent in collecting data about their employees are well suited to leverage AI for the next step in process improvement. If your company hasn’t collected much data historically, that same technology is a good way to pick up the slack. 

Onboarding AI-driven platforms across different touch points in your recruitment process will enable a continuous collection of data points on your candidates and employees that provide insight into what makes a good hire. These same platforms will allow you to monitor the core metrics that matter to your business, and alter your strategy to ensure that you’re hitting your goals. 

4. Making the process faster and more efficient

By automating time-consuming tasks, and focussing on the metrics that drive the best results, recruitment teams are able to drastically improve the speed and efficiency of their hiring process. We’ve already talked about the value of leveraging big data analytics to improve your recruitment process, but the automation of tasks is just as important to overall success. 

Effective recruitment strategies will always be driven by human input. That means that recruiters need to be freed up to think strategically, build and execute frameworks for success, and network with real people who will make a difference in their organization. A recruitment team that spends most of their time on tasks that a machine could do will not be getting the most out of their human resources, which will affect the performance and efficiency of the overall recruitment process.

Likewise, certain recruitment tasks are just better suited to automation. Communication tasks, for example, that require the same email or information to be sent out over and over again are much better suited to a machine that can mass send messages at a set time. Likewise, sourcing and screening technology has gotten to the point where machines can quickly scan hundreds of resumes and social profiles, and match them to potential job openings. Yes, a recruiter can do that too, but there are too many variables at play that make the process much less efficient. 

AI in recruiting is best thought of as a tool that enhances your team’s efficiency and output. Humans are best suited to strategic tasks, while machines can take care of the repetitive and data-heavy ones. In the end, your recruitment process will thank you for it. 

5. Enabling better assessments

Lastly, AI in recruitment can be used to improve how you assess candidates. This can be accomplished in many ways, depending on the technology you’re using. 

ATS platforms, for example, leverage artificial intelligence, to quickly screen resumes for predetermined keywords related to the job requirements. Many ATS platforms will use natural language processing and other forms of AI to quickly analyze resumes for word choice and content to determine who should be shortlisted. Given that most resumes that are submitted for most jobs are unqualified candidates, this type of technology can mean significant time savings for recruiters. 

Likewise, automating candidate sourcing can both expedite and expand your outreach on social media, job boards, forums, and so on. AI can be used to analyze hundreds of social profiles, for example, to find and message passive but high quality candidates. 

AI can even be used alongside traditional interviews to analyze things like body language and word choice, providing an extra layer of objective assessment that recruiters can use to make a hiring decision. 

These are just five general use cases for AI in recruitment, and this is just the tip of the iceberg in terms of potential. If your company is looking to get better and more efficient results from your hiring, then AI-driven recruitment tools are likely the way to go.  

Brendan is an experienced writer and content marketing professional with experience working for various HR tech and SaaS companies in Canada. He has an extensive background in web content marketing and journalism.