As a buzzword, “artificial intelligence” is lobbed freely around the technology business, used to describe both streamlined workflows with less human interaction, and the application of large datasets to specific tasks. But how is actually applied when to comes to talent acquisition?

Although AI has been a recruiting tool for years, actually proving its merits is difficult. If artificial intelligence is truly beneficial and works as many believe it should, would “the Great Resignation” have occurred? Citing research from Work Institute, Oracle noted that 40% of employees quit within their first year of being hired. It begs the question: Why didn’t AI tools forecast that nearly half of employees would be gone inside of 12 months?

AI in Recruiting and Interviews

Artificial intelligence is the application of knowledge from a massive dataset. While machine learning can gather and parse data to create datasets, AI is the forward-facing platform or the tool used to apply that knowledge.

In recruiting, the dataset consists of resumes, which may be scanned for preferred skills, experience or other factors. The process saves humans from the tedious task of screening resumes, and it helps surface preferred candidates quickly.

This is where issues begin. AI doesn’t understand nuance or context. For instance, a candidate who has three years working at a top competitor might be far more valuable than someone with 10 years of experience in a related but general field. If a recruiter sets up a parameter requiring at least five years of experience, well-qualified job seekers with three years under  their belt may never land an interview.

Also, AI is subject to human error. Yes, it’s popular because it reduces time to hire, but it’s important to consider how solutions are set up and the cost of any mistakes. On average, SHRM notes, it costs on average $5,000 to hire and onboard – a cost which scales wildly in some fields, like technology.

Where AI Succeeds for HR

But it’s not all bad news or caveats. While proper application is critical in the recruiting and review stage, beyond that point, AI can shine.

Better Candidate Experience

AI also drives automation. When hiring managers agree a candidate should be considered for a role, automated tools can present requests for initial interviews and tests or questionnaires candidates may need to complete as job requisites. Intelligent automation can send the requested information, surface it to the proper stakeholders upon completion and generally move candidates along in the hiring process.

Objective Decision-Making

Where context matters in recruiting, it may be detrimental to the process of deciding which candidates to hire. Many platforms require interviewers to submit scorecards for candidates after they’ve met. AI can examine that information and relate findings back to the team, allowing for true objectivity where – and when – it matters most.

How AI Can Help Recruiters

Deep Learning

When tools are used properly, artificial intelligence can filter context to datasets. When a candidate is turned away and the reasoning is logged, AI can return to its machine learning roots and add notes to a candidate’s profile. This is useful when reviewing or interviewing candidates. While machines do not know how to apply context, artificial intelligence can use it as a reference for future interactions.

Stay Connected

Chatbots often induce eye rolls, but they can be useful for large companies that have many open roles and many candidates. AI can answer complex questions about benefits or the interview process, and help recruiters gather data in a more engaged environment. Although chatbots take time to set up properly, their long-term benefits are profound.

How AI Surfaces Better Candidates and Improves Retention

AI can do plenty of positive things for recruiters and HR managers. For one, it can automate tasks like background checks, which may be critical for a role or a company-wide standard. The gathering of information can be automated, and AI can identify potential red flags and surface potential issues for employers even before a background check is conducted.

Of course, having too many good candidates is a great problem to have. AI can automate high-volume tasks like screening resumes and candidates’ answers to screening questions. Based on the responses given, AI can quickly surface skills assessments or other communications to high-value candidates.

Finally, candidates who may not be qualified for a particular job at a company may find another role is a better fit. AI can help surface those jobs and add notes to candidate profiles that might speed them through the interview process for this new job. Rather than eliminate candidates, artificial intelligence can serve as a job-matching tool.

Improving Retention

A case study from technology provider Sparhound illustrates how AI can improve retention through employee engagement. The unnamed company had 40% turnover in some regions and using AI to examine datapoints for former employees like salary level, training and exit interview comments could help identify flight-risk factors.

The company created a dashboard for at-risk staff members so HR could engage them directly or use automated tools to gauge their satisfaction. With AI tools applied this way, identifying under-trained staff might be possible, so the employer train at-risk workers appropriately.

The Reality of It All: Does AI Work?

Where objectivity is mandatory, AI should be brought to bear. It’s almost impossible for humans to be totally objective in the hiring process. We may bend the rules if there aren’t enough candidates, and feel pressure to give underqualified candidates the benefit of the doubt when it seems like they could learn critical skills on the job.

AI can apply intelligence as long as invest the time necessary to set proper parameters. When that’s done, AI  tools or platforms can eliminate unqualified candidates and make appropriate decisions for how remaining prospects move through the hiring process. High-potential candidates might be surfaced to recruiters or HR quickly while others wait to be examined, for example.

At the end of the interview process, AI can help create individualized offers, which candidates are more likely to accept. It can evaluate local market salaries and a candidate’s job history and skillset to help HR managers make the best offer possible. It may even predict a candidate’s likelihood to accept, and provide insight on what next steps should be taken in case they don’t.

The ADP Research Institute found employees who have at least one point of contact in HR value their company twice as much as those who feel disconnected. The needed trust-building can start with AI during the recruitment process. Using the technology to message candidates with relevant, contextualized information may help them feel connected to the company, which can also improve the chances of their accepting an offer.

AI works in recruiting and HR when its applied properly. If it’s used simply as a time-saver, employers miss the opportunity to improve the candidate and employee experience, and to gain the benefits of a truly engaged workforce.


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