For its latest episode of Elevating The Conversation, the Journal sat down with  Wade Larson, the executive director of the Production & Manufacturing Institute and the owner of Optimal Talent Dynamics, to discuss the Inland Northwest labor market.

The Elevating The Conversation podcast is available on Apple Podcasts, Amazon Music, Spotify, and elsewhere. Search for it on any of those platforms or the Journal's website to hear the entire conversation, but for now, here are five takeaways — edited for space and clarity — from the episode.

1. The pandemic accelerated labor market challenges, but it didn’t cause them.

 We often take a look at the pandemic and we blame the pandemic for our current situation.

When I first jumped into HR, back in the early '90s, mid-90s, I remember coming across a report from the Department of Labor, and it was from 1990 and it was a 30-year workforce projection. They projected out that in 2020 there was this cliff, this drop-off cliff, that at that point, the availability of supply of labor plummets.

They were spot on. The only difference was in about 2010 when we had that recession. They were off a little bit, and that's because we had some incentives to keep people in school a little bit longer. Other than that, they were spot on, and that's because (of lower birth rates in the U.S.).

But we've known for 30 years that this was coming. So, the pandemic shifted some things. It accelerated some things. But this shouldn't be a surprise.

2. There’s more of a skilled labor shortage than a total labor shortage.

 On the one hand, we have employers who are saying, “Why can't I find anybody? Who's qualified? I get some applications in, but nobody's qualified. This length of time to find somebody is crazy.”

On the other hand, I have job seekers who are saying, “I can't find a job. I apply to these places and nobody will hire me.”

And so how can that be?

We have this unemployment rate of 3.6% roughly. And you know, it's a low unemployment rate, so somebody who wants a job should be able to go find a job, but they're not getting callbacks.

It's not that we don't have people who want jobs, it's the qualified talent.

(Job seekers) have to upskill their skills. They have to go in with a higher level, with AI and automation. The entry-level job is not entry level anymore. They're gonna have to continue to upskill their skill just to be entry level now.

So, there's some factors that are playing in here that are different today than they ever have been.

For those who have little to no skills going in, it’s gonna be a rough day.

3. Artificial intelligence and automation will continue to replace unskilled labor roles. 

 It will continue to be that the employers are gonna need fewer of those unskilled labor positions. And that will grow.

Moving ahead, when we consider workforce 2030, four or five years from now, when we get to that point, we're gonna need fewer and fewer unskilled folks because on the employer's side, as they recognize the need for more skilled folks, more skilled labor, they're gonna automate some things.

Not because they need to replace current people. They need to fill the gaps for that lack of qualified talent. They're gonna recognize, “Hey, you know, I don't have anybody out there.” So they're gonna start to automate more. They're gonna bring in more AI solutions. AI won't replace the current folks. AI's gonna fill the gaps for the talent that they don't have.

As they're filling this in, the people who are coming in from the outside have to have those skills.

4. Employers have to take new approaches to finding, and creating, talent.

 Employers need to recognize that the old model of throwing in the net, casting the net, and hoping for the best no longer works, hasn't worked for some time, and it never will work again.

We've got about three models that are gonna work from now into the future.

Model No. 1 is taking your current employees and upskilling them. Finding opportunities to grow them and providing incentives along the way, finding those who have the attitude and the aptitude, and finding opportunities to learn them, grow them, and also provide the incentives because it's the pay model. They have to pay them as they grow and improve their capabilities.

No. 2, they have to invest in the community programs. They have to help upskill their applicants.

From one side, they're gonna say, “Well, that's a big investment with no (return on investment) or a hard-to-track ROI.”

We're saying, “Yeah, it is, but if you want the investment to pay off, we're gonna have to upskill the community.”

And then No. 3, one of the best ROIs that they have is to invest in the high school programs; directly to work-based learning programs to connect with them, train them, and bring them straight in.

 There's no perfect model, but the best models are where business says, “This is what we need,” education says, “We'll build a program around that,” and government funds it, or the agencies fund it and business is investing in it too.

Anytime that we have that kind of a model that's collaborative, that's what makes it work.

5. Younger generations need to develop AI familiarity and skills prior to entering the workforce.

 I think (AI is) gonna be a core competence. That core competency is gonna be required of them. When we talked about the new upskill level for entry-level workers, AI familiarity is gonna be a baseline.

AI competency is gonna be your license to play. It's not even gonna be a step ahead. That's gonna be an entry level requirement; to understand AI, how it works, how it integrates.

So, if you're at a white-collar professional level, you better be well versed on how AI works and how to integrate that into your job.

If you're in the medical field, you're in health care, they're gonna have AI intertwined within your (electronic records) system, within all of the other systems already, and you better understand how those analytics work and how to read and utilize those.

Business, absolutely. Business informatics, we've been using AI for a long time, but even within production manufacturing, we have to understand how to use those, how to integrate those. 

So for us to say, “I'm not a computer kind of a guy,” then plan on not getting a job for some time.