Is AI Reliable Enough to Hire Your Employees?

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Artificial intelligence (AI) has emerged as a powerful tool for making new hires. Early experiments have shown it to be fair, fast, and effective. And yet, employers all over the world remain skeptical. Can it replace the human touch for a task that seems so personal? 

It may be a long time before computers completely replace humans in managing the hiring process. However, AI in hiring remains an exciting development that is worth consideration. Below, we look at what AI does well and what it might not be able to handle. 

Defining Reliable

First, what does it even mean to be reliable at hiring new employees? Does it mean finding someone with the right background and skill set? Avoiding personal bias? Navigating large candidate pools quickly and effectively?

AI is well suited to meet these criteria as far as it is programmed to do so. But what about the softer components of making a hire? The gut feeling that can’t be programmed into an algorithm? The knowledge of how your existing staff operates and your assumptions about how this potential hire will play into the group dynamic?

These factors are harder to leave up to AI. Below, we look at what artificial intelligence does well and what it doesn’t. 

Maximizing Efficiency

One of the best things about using AI for hires is that it can immediately eliminate all applications not suited to the job specifications based on the candidate’s history. Dozens or hundreds of people might send applications for a job listing. When a human employee has to sort through them, they might spend weeks just cutting applicants who never had any business sending their resume in the first place. 

Not only is this frustrating, but it also makes it harder to concentrate on applicants who are well suited for the job. 

Data implementation is all about maximizing efficiency. AI hiring programs can do this by taking a pool of dozens of candidates and narrowing it down to a few of the best fits. 

Finding Good Fits

Of course, the main goal of any hire is to find someone who will do the job well and stick around for a long time. Based on these criteria, AI is very good at what it does. Candidates with the right skills are identified immediately.

Good hires contribute more to a business and can reduce turnover by sticking around for longer and contributing to a productive work environment that makes other employees want to stick around. 

It’s worth mentioning that retention numbers often dip around the time that businesses start looking for and hiring a new employee. The reason for this is simple. While you do that, your existing staff is left with more work than they used to have as they pick up the slack for the job vacancy or the ineptitude of a new hire. 

AI can eliminate both factors by making the hiring process quick and ensuring that the person who gets the job is well suited. 

Without Bias?

Can computer programs be biased? In fact, bias in AI runs significantly more profound than it does in human beings. For example, you might have assumptions about how the ideal job candidate will speak. Perhaps you assume that perfect grammar and a degree of formality in their speech and writing are requisite qualities for anyone you would be willing to hire. 

But then, an application catches your eye. The grammar and syntax don’t read like the resume was printed off by someone on their way to getting an MBA, but there is something about the applicant. They have personality. You give them a call; you make the hire. 

In other words, you change your mind.

Algorithms do not. Much has been made about the potential for AI’s capacity to share the bias of its programmers. If the people who write the software have any form of prejudice, latent or otherwise, the fear is that it will play out in the code. 

Researchers have gone back and forth on if this is probable, possible, or preventable. Even without large-scale prejudice, however, AI does operate under presumptions that cannot change. When you use AI to make hires, there are no gut feelings. Either a candidate meets the criteria, or they don’t. 


With that said, it is worth mentioning that AI is better at establishing diversity in the workplace than human bosses. While there is not enough data to say if this trend would hold on a global level, early efforts to integrate AI into the hiring process have resulted in quick, diverse hires, usually with well-qualified candidates. 

This suggests that while AI might have bias, it’s not personal. A hiring manager may subconsciously gravitate toward candidates they feel a group connection. Unless Windows 10 applies to your job, there isn’t much risk of this happening with AI. 

Maximizing Data Use in Business

AI and data implementation in business are a growing trend quickly transitioning from “competitive advantage” to “business requisite.” Right now, it’s not necessarily the standard to have AI make hiring decisions. 

While studies have shown that AI has enormous potential, making new hires is still a task many people prefer to do manually. How should businesses make decisions about how they use data and technology?

Utility has and will always be the driving factor. Technology should:

  • Simplify existing processes
  • Create more time for jobs that have to be done by hand

New hires might fall into the “jobs that have to be done by hand” category for years to come. However, that doesn’t mean AI can’t help at all. By allowing AI to influence how new positions are listed and by determining which candidates find their way in front of HR, it not only saves time but will enable businesses to focus on the parts of the job that are important. 


Andrew Deen is currently writing a book about scaling up a business.


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Andrew Deen has been a consultant for startups in almost every industry from retail to medical devices and everything in between. He implements lean methodology and is currently writing a book about scaling up a business.