Colleva

Job Seeker Insights

Not Doing AI Interviews Comes With a Cost

We were reading a recent LinkedIn post from long-time talent acquisition and sourcing leader Carmen Hudson, and, well, she nailed it.

Hudson writes:
Aren't tools that assess every candidate with the same set of criteria better than not using tools at all?
In my experience, of the candidates that apply, only a teeny-tiny percentage are assessed at all, if an automated tool isn't used. So what's better? A documented approach to assessing all candidates, or a haphazard assessment of a few folks?

Amen, Carmen.

She adds:
We have to remain vigilant when using AI to assess skills and behaviors. That's likely ongoing, never-ending work. But let's not sit around pretending that we currently do a great job of candidate assessment at scale.

We’ll put it this way, more bluntly: we’re not doing a great job of candidate assessment at scale.

It’s not that we should consider a better way of reducing the resume pile. It’s that we have to.

Waiting for the Problem to Go Away … Doesn’t Work

Turning to artificial intelligence for an initial job interview may seem like a “nice to have” more than a “must have.” But, the costs of not doing so can be substantial in many companies. These include:

Mishires. When you screen, assess, and select haphazardly, likely ignoring some people, likely biased against some people, likely spend very little time on each person, mishires happen. Every bad hire costs about 30 percent of an employee’s first-year earnings.
Burnout bias: Excessive interviews can cause burnout and bias. For example, interviewers short on time, spending a few seconds scrolling through hundreds of candidates, may turn to “recency bias” (favoring the more recent people they have interviewed) or “primacy bias” (favoring the initial around and skipping the rest. Or, the halo effect: if they graduated from MIT, Stanford, or survived Facebook or Google, they can do no wrong. All this can greatly and negatively impact quality of hire. Burnout, more simply, can also lead to turnover in the talent acquisition department among recruiters, recruiting coordinators, and others stretched too thin.
Interview creep. Initial interviews are prone to bias. Even experienced members of the hiring team asking some initial questions to a job candidate can engage in “small talk” about the weather, the city where the candidate lives, people they know in common, or other topics, and find themselves favorably or unfavorably disposed to the candidate for reasons unrelated to the job.
Missing red flags. Busy interviewers doing a massive initial round of interviews can miss “soft skill red flags.” Again, this can impact quality of hire, and lead to short employee tenures due to people quitting quickly or being terminated during their initial months on the job.
Competition. Companies that miss out on talented applicants for a job not only lose out on a potentially great employee, but their competitors that can handle a greater interview load gain one. Similarly, high-quality candidates who experience a lengthy or poor application process can be lost to competitors quickly. If your competitors are using AI interviews, they are likely interviewing about 10 times more candidates per recruiter.
Loss of untapped talent. Nontraditional candidates can be overlooked by resume filters, but found by AI interviews. Many tools don’t actually solve the screening problem; they just filter out nonconformity.
Long implementation cycles for alternatives. Many alternatives to avatar interviews involve major transformations in an organization, and very lengthy implementation time.
The wrong people making decisions. Hiring teams are often put in the position of evaluating and selecting a small number of people to interview among thousands – and quickly. This is a nearly impossible task for anyone, but especially those recruiters who don’t have sufficient training, such as hiring managers who are largely untrained.

‍Let us know if you want to learn more about using AI to help winnow down your initial group of job applicants. Waiting is not a good option.

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Waiting for the Problem to Go Away … Doesn’t Work

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