How Is Artificial Intelligence Changing the Recruiting Process?

Artificial intelligence has advanced by leaps and bounds in the last few years, with nearly every job function, including recruiting, seeing its transformative power. From providing basic resume screening assistance just a few short years ago to performing nearly every aspect of the hiring process today, AI has immense potential to improve efficiency and facilitate smarter hiring. 

AI in recruiting, however, is not without its downsides. In fact, there are many of them. We’ll examine how AI is changing the recruiting process and explore the pros and cons of this shift. 

The Power of AI in Recruiting

AI can disrupt any aspect of recruiting, but we see the most significant potential for improvement in four key areas.

Efficiency

AI-powered tools can tackle some of the most time-consuming tasks in the hiring process, like screening resumes and sending messages. By managing these necessary but tedious tasks, AI can free up recruiters’ time for activities that are better suited to humans, like conducting interviews and speaking with references. This can dramatically improve efficiency and enable recruiters to consider more candidates, expanding a company’s hiring pool. 

Candidate experience

If there’s one thing we know about job seekers, it’s that they want to hear back from the companies they’ve applied with. More communication is almost always better than less, yet maintaining consistent engagement with candidates has historically been a huge hurdle for recruiters. AI alleviates the challenge with tools to communicate regularly with candidates, answer questions 24/7, and even conduct interviews. All of this contributes to a more seamless hiring process. 

Accuracy

Perhaps the most compelling aspect of AI in recruiting–at least as the technology stands today–is its potential to help employers make better hires more often. Advanced algorithms can identify job success and retention predictors, helping us zero in on the best candidate from a group of finalists. Facial analysis tools can assess candidates’ expressions to gauge personality and even flag potential signs of deception. Continuous learning means the technology gets more accurate the more data it has to work with, facilitating ongoing improvement the longer you use it. 

Fairness 

Since data drives AI, it’s inherently less prone to the biases that can creep into the hiring process (though it’s not completely immune to bias–more on that a little later on). AI-assisted screening can ensure all candidates are given fair consideration. At the same time, tools like AI-powered assessments can judge candidates based on their actual qualifications rather than other factors like gender, age, or ethnicity. 

The Pros of AI in the Recruiting Process

Thanks to advances in AI, recruiters can leverage technology in many beneficial ways. Here are some of its top upsides. 

Identifying candidates

AI algorithms can search through vast pools of candidates on job boards, social media, and other platforms to identify those who match the job description. This greatly reduces the amount of time recruiters spend on sourcing and ensures that only qualified candidates are approached for consideration. 

Screening candidates

AI tools can quickly scan and filter resumes, identifying the most relevant candidates based on hiring managers’ criteria. This helps recruiters manage roles with a heavy volume of applicants and spend more time carefully considering those who are a strong fit. 

Predicting success

With the help of machine learning, recruiters can analyze historical data to identify patterns and make strong predictions. This includes things like which candidates are most likely to be successful in a role or company culture, which sourcing channels yield the best results, whether an individual is likely to be job searching or open to new opportunities, and how likely a candidate is to accept an offer.

Reducing bias

We’ve already touched on AI’s potential to make the hiring process more objective. By removing potential bias-inducing information like candidates’ names and education details, AI focuses on candidate credentials and other data-driven criteria. 

Assisting applicants

AI-driven chatbots can answer frequently asked questions, suggest roles that fit a candidate’s skills, and even complete on-the-spot screenings. This ensures timely responses and allows companies to offer a communication channel that’s available around the clock.

Analyzing data

AI has the unparalleled ability to parse through large volumes of data and layer predictive capabilities on top of it to identify trends and forecast likely outcomes. The resulting intelligence can help you make better hires, avoid hiring mistakes, predict when you need to ramp up hiring, and more. 

The Cons of AI in the Recruiting Process

While the future of AI is promising for the talent acquisition field, it also poses several noteworthy challenges to be aware of. 

Bias

That’s right–the tools meant to help employers reduce bias can develop their own prejudices. AI models are only as good as the data they’re trained on, which means they can “learn” to show preference to certain candidates based on who has been hired in the past. Companies must be mindful that AI systems are designed and trained in a way that avoids perpetuating existing biases.  

Application overload

Just as employers are using machines to do more of the tedious recruiting tasks, job seekers are using technology to automate the laborious process of applying for jobs. New services allow candidates to find matching positions, automatically customize their resume for them, and submit an application within a few clicks. As a result, a landslide of AI-generated applications swamps companies, and a bot-on-bot battle ensues as their own AI tools sift through them. 

Doctored application materials

If you had a dedicated copywriting tool that could take your cobbled-together list of jobs and skills and turn it into an impressive, impeccable resume, why wouldn’t you use it? Thanks to ChatGPT, all candidates now have access to such a tool, and running your application materials through it has become the norm before submitting them. This calls into question those materials’ usefulness in assessing a candidate’s actual suitability for a job. 

Data limitations

AI technologies get better the more data they have to learn from. For large and enterprise-level firms, this isn’t a problem, but smaller companies may not find the same level of usefulness or accuracy due to a smaller data set. 

Exclusion of qualified candidates

One major advantage of human recruiters is that they can see past the keywords and the job titles to the “whole package,” like if a candidate lacks formal education but has extremely relevant experience. AI, for the most part, doesn’t have this level of discretion, which means great candidates may be ruled out. 

Security

We’ve already mentioned several times the large volume of data AI relies on. Storing, accessing, and managing this data raises significant privacy and security concerns, especially if sensitive candidate information is mishandled or a breach occurs. 

Technical difficulties

As with all technology, glitches happen. Outages and bugs will inevitably pop up, which can confuse candidates and delay the hiring process.

Impersonal nature

Interacting with AI machines can feel like just that–talking to a machine. It’s speedy and efficient, but the impersonal nature can feel transactional and may be off-putting for some candidates. 

Job displacement

We’d be remiss not to mention the elephant in the room: AI taking over the very jobs we’re using it to do. This is particularly concerning for roles heavily focused on administrative tasks. It can create resistance and raise ethical concerns about the broader implications for the workforce. 

As AI continues to evolve, it’s best to move forward with our eyes wide open to both the possibilities and the challenges. As with any technology, we can’t fall into the “set it and forget it” trap. As we implement emerging tools, it’s crucial to evaluate their success and accuracy over time and reflect carefully on the results. We’re excited about what’s to come and to see how this technology will continue to transform our field, both in the near term and in the years ahead.