AI is gradually making its way into every stage of the recruitment process, from sourcing to pre-selection and interviewing, as well as reference and background checks and determining fair compensation. To give you an idea of what’s currently going on, we’ve compiled a list of the 11 most groundbreaking uses of AI in recruitment that we believe we’ll see (a lot) more of in the coming years.
Interview robots
Yes, an actual, physical interview robot can now be used in your recruitment process. To assess a candidate’s soft skills and personality traits, the bot combines natural language processing (NLP) and interview analytics. As a result, because it does not consider gender, age, physical characteristics, or other characteristics, it aids in the elimination of (unconscious) bias.
While using a physical interview robot has many advantages, there are certain things to consider. To begin with, as with all AI applications, the software is only as good as the data it is fed.
Another consideration is the candidate’s prior experience. Using a robot can ensure consistency and provide each candidate with the same interview experience, but will they appreciate being spoken to by a machine?
Even if you only use the robot for a small portion of the recruitment process, make sure your candidates understand why and that you compensate for the absence of a “human element” in other ways.
Read More: Talent Marketplaces: A Complete Guide
Analytics for conversation
Metaview technology, for example, listens in on job interviews and extracts perspectives so that companies can interview more efficiently and make better hiring decisions.
The software audio-records your interviews, whether via (video) call or in-person, and then transcribes them automatically. The interview insights you gain from this can help you determine how effective your interviewers are and where you can improve.
In terms of insights, consider information about the most frequently asked questions by candidates. They can also show you if you are interviewing all applicants consistently and if you are failing to assess certain core skills during the recruitment process.
Of course, the most crucial thing to remember here is to ensure that your candidates are aware that their job interview is being recorded and analyzed – and to obtain their full consent ahead of time.
AI-powered background checks
Although background checks may appear to be a formality, the reality is that regulations change almost constantly, and laws differ from one country (and role) to the next.
However, as time-consuming and labor-intensive as the background check process may be, it is unlikely to disappear because it reduces risk for businesses. As a result, it’s not surprising to see yet another innovative use of AI in background checking.
Reduced bias, more privacy for applicants (because the software only checks necessary details), a simpler, quicker, and more efficient process, and the expandability of the solution are all advantages of using AI-infused background-checking technology.
Checkr is a background check company that uses artificial intelligence and machine learning, and the company claims to be the only one.
Top HR Tech Insights: Understanding Global Talent Marketplace
Checking references through automation
Even though the background and reference checks are not the same things, they are frequently performed at the same time – near the end of the hiring process. Collecting various reliable references, like background checks, can be a time-consuming task.
The reliability of both the person providing the reference and the review itself are big barriers to a manual reference check process (if we can call it that). But there are more practical issues as well: people may not pick up the first time you call them, referees do not receive automated reminders, the process is difficult to replicate for multiple jobs, and so on.
Many of these issues can be alleviated by using an AI-powered reference check tool. The software automates the process and aids in the collection of all relevant data on a single platform.
To avoid hiccups, referees complete scientifically designed questionnaires and receive automated reminders (and lengthy waiting times). Potentially fraudulent activity (for example, a candidate’s friends acting as referees) is flagged.
Artificial intelligence for internal mobility
Hiring internally can help you save time and money. It reduces hiring costs and risks significantly, and your ‘new’ hire already knows the company, so they’ll be functional and productive sooner.
Making internal mobility a primary focus is thus one of many companies’ top recruiting strategies this year. To accomplish this, 44% of HR professionals want to use AI to find the best internal candidates.
Gloat, Phenom People, and Eightfold are three companies that provide AI-infused internal mobility platforms.
Identifying team strengths and closing talent gaps
One of the more global trends we see in HR is a shift away from an emphasis on individuals and toward an emphasis on teams. In recent years, there has been a lot of focus on the individual candidate; their goals, skills, potential, and whether or not they would fit into the company culture.
As a result, we’ve seen an increase in the utilization of pre-employment assessment tools for individual candidates, for example. Companies such as Teamscope, on the other hand, are taking the use of AI in recruitment to the next level.
They use data analytics and scientific testing to understand individuals’ deep-level characteristics, and machine learning to understand how these variables influence collaboration and effectiveness in a team setting.
The basic concept of making better hiring decisions continues to remain the same; however, those hiring decisions are now made with the greater good in mind, which means the performance of the team as a whole and, by extension, the entire organization.
AI-powered talent marketplaces
The rise of the gig economy, or more broadly, people who prefer (part-time) freelancing over traditional employment, has resulted in the rise of freelance marketplaces such as Fiverr, Upwork, PeoplePerHour, and others.
Notably, we are now seeing other companies step up their game in the freelance marketplace. Rather than simply connecting freelancers and employers, these AI-powered talent marketplaces assess experts’ skills and experience and match them to the needs of businesses.
The benefits of these ‘talent marketplaces 2.0’ are obvious, with the main one being that automated matching saves time, increases efficiency on both sides, and reduces the chances of a discrepancy.
Occur and Boon Tech are two examples of AI-driven talent marketplaces.
Compensation estimation
Choosing the best compensation and benefits package for a new employee is similar to solving a puzzle. This is typically the responsibility of a compensation and benefits manager in larger organizations, but in smaller businesses, comp and benefits is an additional task for the HR generalist.
Naturally, the appropriate package is determined by your industry, local laws, and employee level. Because industry standards and local regulations change, keeping track of this data can be difficult.
This is where another novel application of artificial intelligence in recruitment comes into play. PayScale, a cloud-based compensation software provider, introduced its Differentials Engine last year.
When pricing high-demand jobs in competitive markets, the tool allows businesses to consider the specific skills and geographic data.
Top HR Tech Insights: Unlocking Business Success With Data-Driven Leadership
Robotic Processing Automation (RPA)
The process of using software to automate business tasks is known as robotic processing automation (RPA). It’s yet another application of AI in recruitment that can handle a wide range of tasks and activities.
You may be wondering what kinds of tasks and activities are involved. Everything from sourcing candidates and improving recruitment marketing campaigns to interview scheduling and chatbot deployment.
Post-offer activities can also be automated using RPA technology. Consider gathering additional information from applicants, submitting (required) forms, and even conducting pre-employment checks.
PeopleScout is one of the companies active in this space.
Rerouting candidates
Simply because someone isn’t the right candidate right now and in this location doesn’t mean they can’t be your ideal candidate later on or in another one of your locations. So, why risk losing top talent when you can instead develop a relationship with them and keep them interested in your company?
In a still-competitive market, more and more organizations recognize the importance of developing and maintaining a talent pool – a database of candidate profiles interested in working for your business.
Similarly, we see organizations increasingly using AI to reroute people to roles that are more suitable for them. Although only 7% of businesses currently do so, this is expected to increase over the next two years.
Rerouting candidates can be especially beneficial for retail or hospitality companies that have multiple locations in the same geographic region, as it allows them to make better use of their candidate pool. For example, if a candidate’s availability does not match a specific location, why not reroute them to a nearby location with different scheduling requirements?
Since rerouting candidates is not the same as engaging with them through a talent pool, it is a different method of achieving the same result – keeping good applicants with your organization rather than losing them to the competition.
Onboarding of new employees
Employee onboarding received a lot of attention last year, and for good reason. If you consider recruitment to be the stage at which two people begin dating, then the onboarding period is similar to a workplace honeymoon.
In other words, it’s a critical period that will stick with people and lay the groundwork for a strong, long-lasting relationship.
Of course, artificial intelligence is now being incorporated into the onboarding process.
As we saw when discussing robotic processing automation, AI-driven technology can aid in lowering the administrative burden of the onboarding process.
Employee onboarding software also enables organizations to provide onboarding services 24 hours a day, seven days a week. AI chatbots can answer (basic) questions and walk candidates through the various stages of their onboarding process. As a result, new hires can integrate more quickly.
However, as we stated at the beginning of this article when discussing physical interview robots, it is critical not to lose track of the human aspect of employee onboarding.
Talmundo and My Ally are two examples of onboarding software vendors.
Final thoughts
People are inventing new ways to make recruitment faster, easier, and fairer as the use of AI in recruitment becomes more common. More innovation will be seen in the later stages of the recruitment funnel, such as interviewing, hiring, and onboarding, in the near future.
This list is intended to inspire you and provide you with an idea of what is technically feasible if you want to reinvent your recruitment process. Of course, before you begin procuring any kind of tool, make sure you understand what you want to accomplish and how the technology works.
HR Technology News: MIT xPRO Launches Programs with Simplilearn in Executive Leadership Principles and Machine Learning
[To share your insights with us, please write to sghosh@martechseries.com]