AI: The Org Impact You Won't See Coming

"Smart. Beautiful. Intuitive." Pick your AI technology, this description fits—it could be Lever (a modern talent acquisition suite), Spoke (the organizational admin AI bot), or x.ai (a virtual assistant). "Smart, beautiful, and intuitive" solves a lot of yesterday's user adoption problems, often through integrations (which reduce learning curves), interactivity (leading to simplified interfaces), and proactivity (meaning the system does your thinking for you). These are the things we see and get excited about.

But AI (including its precursors which are being used today) also creates new, more complicated adoption problems—ones that are often bigger and harder to see than the ones we're used to.

For example:

Job board Indeed is starting to use AI to match job seekers with jobs they might like by analyzing résumés and job descriptions.

That's résumés and job descriptions.

Indeed touts a 10%–15% improvement in matches using their AI, and they are driving sales with that number, which means their clients are celebrating 10%–15% faster fill times.

Again, with résumés and job descriptions.

I emphasize this because the numbers on job satisfaction, engagement, and turnover are terrible: Gallup reports that 91% of people actively left their last job for their current one, and 51% of people are already actively looking to leave their current one.

Roughly speaking, this means that about half the people who left their last job landed someplace that didn't live up to expectations. Or, put another way, the current job search process yields false positives half the time.

With numbers like this, the résumé/job description matching process can't be considered anything but a massive fail.

Back to Indeed: their AI accelerates matches by 15%, but doesn't improve the underlying process—something that would require improving the accuracy of both job descriptions and résumés. Indeed's AI creates efficiency within a horrible system. The false positives just come faster—and that's a big problem.

So why will companies buy it? Because of those efficiency numbers! Recruiters aren't asked to think about the entire lifecycle of an employee, just the hiring part, and Indeed fixes that. If the fix comes at the expense of retention metrics, so what? That's HR's problem, not recruiting's. Meanwhile, HR has no line of sight into recruiting's processes, meaning that it's likely that no one will realize that recruiting's "solution" is actually the cause of the problem.

And right there is how this massive problem can hide in plain sight.

What will logically happen in this case is that as companies suffer increased turnover, recruiters will say, "Yes, please fix it, we increased capacity 10% - 15% but we're bleeding out the great talent we find faster than ever—our hiring managers must have gotten worse!"

To combat these kinds of challenges, leaders will need to become more adept than ever at design thinking—and will need to change the way incentives flow their organizations to get others to help them think holistically, too.

It may be AI, but it's going to require a boatload of "RI"—real intelligence—to get right.

AI, Tech adoptionseiden