AI, Hiring, and the Future of Entry-Level Talent in ManufacturingAI, Hiring, and the Future of Entry-Level Talent in Manufacturing

AI, Hiring, and the Future of Entry-Level Talent in Manufacturing Transcript:

Jeff White: Welcome to The KulaRing, a podcast for manufacturing marketers brought to you by Kula Partners. My name is Jeff White, and joining me today is Carman Pirie. Carman, how are you doing, sir? 

Carman Pirie: All is well. And you?

Jeff White: Doing great. Thanks. 

Carman Pirie: I’m excited to be tackling this topic in today’s show. I think, look, we’ve discussed AI before. It’s not like the topic of AI is new, but this is an interesting impact of it and a kind of evolution of that impact and an evolution of a problem that manufacturing has been seeing for a long time, for a time before AI was being talked about. It’s just that it’s changing the texture of this challenge for manufacturers. I think it’s an interesting thing to dive into. 

Jeff White: Yeah, it’s. A lovely little tangential topic to the more marketing-related side of AI that we’ve certainly talked about here. We’re gonna delve into some more HR related things as they relate to AI.

Carman Pirie: Yeah. And who better to have on the show than a recruiter to help talk about that?

Jeff White: Absolutely. Yeah. So, joining us today is Friddy Hoegener, President of SCOPE Recruiting. Welcome to The Kula Ring, Freddie. 

Friddy Hoegener: Hey, thank you so much for having me. 

Carman Pirie: Friddy, it’s wonderful to have you on the show. Thanks for joining us today. First off, I guess I’d like to know a little bit more about your firm. Please introduce us to SCOPE Recruiting, if you would. What are you up to? 

Friddy Hoegener: Yeah. We are a boutique supply chain and operations recruiting firm. And really, what that means is we specialize in supply chain, operations nationwide across all industries. And our niche really is within that supply chain. And the reason we started SCOPE recruiting almost 10 years ago was that we saw a need for recruiters to speak the language, both of the hiring managers and the candidates. And we see that till today, right? We have candidates who say, Hey, it’s so great to talk to somebody who actually understands what I’m doing. Who understands the language, who can speak with me almost like a peer, instead of just being asked a list of questions, and I give right high-level answers, and they move on. But I have, a lot of times, candidates feel like they, they haven’t been really understood. And a lot of times recruiters reach out to candidates for roles that weren’t really a fit. And on the flip side, when we talk to hiring managers, we make sure we really understand, okay, what are you looking to accomplish by hiring for this role? What does success look like in the first six months, 12 months? What does an ideal candidate look like? Both from technical expertise and a culture fit. And so having that supply chain and manufacturing background really allows us to dig deeper and find better candidates for our clients. 

Jeff White: Friddy, if you would, before we learn a little bit more about your own personal background as well. What are some of the roles that you’re recruiting for with the supply chain and manufacturing clients that you work with?

Friddy Hoegener: Yeah. On the supply chain side, we really started with entry-level roles. So, a supply chain analyst, a buyer, all the way up to the VP level. We do the occasional executives, but really our sweet spot is probably in that manager director space with some of the earlier career outliers. And the occasional executive.

And then on the manufacturing side, it’s manager level and up, right? So it’s an operations manager, it’s a plant manager, it’s a continuous improvement manager, it’s a demand planning manager, anything you would see in a manufacturing environment. 

Jeff White: Very cool. 

Carman Pirie: Very cool indeed. What did you do before SCOPE recruiting? Or how did you end up starting the firm, Friddy? 

Friddy Hoegener: Yeah. I worked with ABB. I started a global rotational program with ABB out of Germany. And that was at the time when they bought Thomas and Bets in Memphis. And I ended up in Memphis. During my rotational program, ABB decided it would be a good idea to have somebody from ABB who has seen the ABB tools and systems over in Memphis, so I could help kinda roll out some of those supply chain initiatives and show the team what I find. What is ABB doing? How are they working? And I ended up becoming a global commodity manager with Thomas and Bets at the time. From there, I became a supply chain manager at a furniture manufacturer in North Carolina. I did my undergrad in Asheville, North Carolina. Beautiful area. Not a lot of supply chain jobs. So I was commuting to Hickory, North Carolina, daily, and became a global supply chain manager there. The company back then was owned by Kohler. So I went up to Kohler, saw their engine manufacturing and all of that. But then in 2017, we decided to start scope recruiting, and really, when we moved to Asheville, my wife had gotten into supply chain recruiting before I did.

There are some other boutique supply chain recruiting firms out there, and my wife was hired by one of them, but she quickly realized that even they were a boutique supply chain recruiting firm. Nobody there had ever worked in supply chain or had hands-on experience with supply chain. So she was doing extremely well in her role, and we decided that there was a gap. There’s that niche for a boutique supply chain recruiting firm that actually has been in the role, has done the work, and understands the work. And that’s when we decided to start SCOPE recruiting. And until today, all of the recruiters we’ve hired. We teach ’em the recruiting side of the business, right? We hire them with that supply chain background, the supply chain experience. And instead of trying to teach a recruiter about supply chain, we are teaching supply chain professionals, the recruiting side of the business. 

Jeff White: Why do you think it works better in that direction? 

Friddy Hoegener: I do think the supply chain is more complex than the recruiting side of the business. And if you understand the role and you know what the role is supposed to do, and you know what success looks like in the role, I think interviewing for those roles just becomes more natural. And it’s having that understanding, I think, that allows you to decide, okay, they just look good on paper. They can actually do the work, or they actually are a better fit for a different role. And having the recruiting background that is a generic recruiting background, I think, prepares you for assessing culture fit, it prepares you for some interview techniques. But it doesn’t really give you the understanding of the role, and that takes a lot of time for a lot of recruiters who are in this space who don’t have that supply chain background. I’ve talked to some of them, right? They say it took me five to 10 years before I really felt like I understood those roles. 

Carman Pirie: Yeah, that makes sense to me. All I wanna understand is what you’re seeing from the point of view of AI’s impact in your work, specifically, as well as what you’re seeing client-side. And I know that there’s some overlap between those things, but maybe let’s start with how it’s impacting the work of recruiting, even in the specialty recruiting that you’re involved with? 

Friddy Hoegener: I would consider myself a somewhat early adopter. And so we have embraced AI from the get-go, built our own ChatGPT agents, and I think it probably has saved us 10, 15 hours of work. Always in the sense of enhancing human work and not replacing it. I think the best tool that AI is doing for us today is the recording. Back in the day, we had to sit there, we were talking to candidates, and we had to take notes while we talked to them, and that was a distraction. Taking notes while you’re talking means you can’t be as fully immersed in the conversation in the interview process.

Now, AI is doing a much better job than we ever could have of recording and taking notes, so I think that’s a great help for AI. Typically, after every interview, we would sit there for 30 to 45 minutes and type up our notes. How does this candidate compare to the role? What is their experience? What’s their skillset like? And so that work has mostly been eliminated. We do a lot, we do more work upfront now, where we create a very detailed plan. Write up a template for each job and tell the AI exactly what skills to look out for, what skills to summarize, and what the client needs. So more work is done upfront. Now, because we don’t want generic AI notes, we want very specific notes that are relevant and that are maybe even better than the notes we used to do. And in order to do that, I think we have to have a very clear picture of what you’re interviewing for. So our job now is to ask the right questions, even more right?

Digging in deeper, finding out truly what the hands-on capabilities of candidates are, how they fit the culture, what’s their leadership style? And then AI can provide the right direction. Extremely well-written notes that probably eliminated right. 10 to 15 hours of our time. I do think there are a lot of pitfalls in AI as well, and there are companies trying to replace human interaction with AI, and we do see that backfire quite a bit. So we have candidates who reach out to us and say, Hey, I interviewed for this company. I had a, I had an interview scheduled. The only person who showed up was an AI agent on the other side. They didn’t have somebody from HR there; they didn’t have a hiring manager there. They had AI conduct the interview.

And one, I think it’s not accepted today in 2026. People still expect a human to be there when they have an interview. And I also think it creates. A lot of pitfalls, because the next logical step in my mind is that candidates are gonna send AI agents to answer those interview questions for them. So you’re gonna have AI talking to AI, and we’re already seeing that on the resume side. I was talking about that yesterday, right? Back five years ago. You get a hundred applicants. You go through the resumes, and you can pretty definitively and confidently see 10 candidates in there that stand out, that are a good fit for the role.

Now with AI, everybody can make their resume look great, right? So you get a hundred applicants. All of a sudden, 60 or 70 of them look great because AI has written all of them. And so you have, I think, two options now. You can either put an AI filter in it and tell candidates, Hey, if you upload a resume. You have to manually write that you cannot use AI, or you have to interview 50 or 60 people to actually find out who can do the work. 

Carman Pirie: Yeah. The cover letters have never been better. 

Friddy Hoegener: Yeah. Fantastic. 

Jeff White: Finally getting them regularly because people hated writing them, but it always made the candidates stand out.

Carman Pirie: It’s funny, a period of time you couldn’t, you basically wrote a cover letter that was halfway decent and all of a sudden you were getting an interview because you were one of 5% of people that would actually do it now, boom. Cover letters actually make sense, and they’re less useful than ever.

Friddy Hoegener: But it creates some interesting challenges because right now, that first screening hurdle, really, if you’re not using AI to get through it, you are, you’re probably being left behind. But on the flip side, right? All of a sudden, every candidate looks great now on paper.

Jeff White: Do you have any recommendations for people for hiring managers and recruiters on how to weed through something that is largely homogeneous in terms of quality?

Friddy Hoegener: I do think we’re going to see ATS, applicant tracking systems, within the AI filter. That’s the only solution that I can think of. I know they already exist in other businesses on the marketing side. When you submit articles, they have AI filters. They can tell you exactly your AI score for any given article.

I do think. If the resume wants to survive and has to survive, we’re going to need an AI filter that makes candidates write their own resumes. On the flip side, I know from some family relationships that, for example, Google is going to in-office interviews for the most part because candidates have been using AI to cheat in remote interviews. So Google’s only solution today is to bring candidates back into the office and do the interviews in person? 

Carman Pirie: Yeah. That’s telling, because if anybody could define a technological solution to it, you would think it would be them. 

Friddy Hoegener: Yep. 

Carman Pirie: I wanna talk about what you’re seeing on the client side and this notion of the evolving nature of the skills gap that you’re seeing. I believe that the hinge of your hypothesis is that AI is coming for the entry-level roles first, and therefore. We have nobody to move up into the other rules when they’re required. 

Friddy Hoegener: That’s a trend we have seen. Is that right? What AI is good at is repetitive tasks. It’s the data analysis. It’s the things that typically right companies give to entry-level folks to learn about the company.

Go sit there 40 hours a week, do the data entry,  place the POs, pay the invoices, and do certain things that are made for AI to automate. And so we do see a sharp decline in entry-level roles. My hope is that they won’t go away fully, that companies will recognize not having entry-level candidates will create a long-term problem and that they will start creating new entry-level roles. I think the entry-level roles from five years ago, right? They are more or less gone. I do think there is gonna be value in creating entry-level roles that work with AI that aren’t just your typical job tasks, but AI can elevate those entry-level roles, too, now. They were looking at those and said, Okay, we’re not just trying to keep efficiency steady and replace people with AI and basically stay where we are today. Instead, companies are gonna look at it and say, okay, our employees now have 40% more time. What can they do with that time that we just haven’t been able to do before?

And I think it comes down to candidates’ willingness to adopt AI, work with AI, and then go to the business and say, Hey, you know what, we’ve never been able to do this before because we didn’t have the information, we didn’t have the capabilities. This is what we can do now with AI. To become more profitable and more efficient. So instead of just eliminating roles that can be eliminated. It’s more looking at it, okay, now that we have that capacity, what can we do with that capacity to grow? 

Jeff White: How do you think organizations need to be looking at, if we’re redefining what entry level looks like, because it can be assisted using AI?

How do organizations need to be thinking about career progression for people now? Are, is the entire, because obviously if we’re elevating that entry level role, the things that they’re going to move into probably look different too, don’t you think? 

Friddy Hoegener: Yeah. I think they become more strategic. They become more cross-functional. I think what AI is really good at is getting you to a decision-making point more quickly. What may have taken 10 hours of data analysis and digging through Google to find new vendors. Let’s say if we’re running an RFPA request for proposal, and we’re trying to quote out a certain product that we’re buying. In the old days, you had to create the RFP, so you had to collect the information on the product. Then you had to go out, you had to find the vendors, who can we actually bid this out to? And AI can speed all of that up, right? So it’s really, I think you get to that decision-making point with AI much quicker, where you can say, okay, we have all this information. We have all of this. What do we do with it now? And I think the entry-level roads are gonna get to that point quicker as well. With the utilization of AI, they can go to their managers, to the business and say, Hey, this is what we can do to make the company better instead of just sitting there, placing POs, for example. So I think there will be more agency in entry-level roles. But the business still needs a learning process, too. So I think, what does the business do? How does the business operate? And you have to understand that before you can make recommendations on what to do better.

So I think, again, AI can probably assist in getting early career candidates to that point quicker. They’re gonna get assisted by AI. They don’t have to start from scratch, right? They don’t have to do the analysis from scratch. AI can help with a lot of that, and then it comes down to, okay, what are we doing with that information, and how do we utilize it? I think we’re probably quite a few years, if not ever, away from letting AI make decisions, right? I think the good large language models, the good AI tools that. That has the capabilities to actually replace white-collar. They’re gonna be prohibitively expensive and energy efficient, and I don’t think they can be rolled out at scale, is what I’m frankly hoping for.

I think maybe you have research, you have medical, you have certain fields where you have these very advanced AI tools that actually have those capabilities. But they’re too expensive and too data hungry to really deploy in scale. So what we will get is probably what we have today. Maybe there’s gonna be another 25% bump in efficiency and capabilities in those large language models, but they’re still not good enough to just let ’em run by themselves, right?

So they’re still gonna need that human oversight. They’re still gonna need people, actually interpreting the data and saying, okay, what are we doing with the data? And then in the end, making decisions and taking responsibility for those decisions. 

Carman Pirie: Yeah, I think that’s an interesting hinge in this whole debate is the question of whether humans are required for judgment on an ongoing basis, or are they required for accountability on an ongoing basis?

Because those are connected, surely, but they’re different. And there’s been some interesting articles of late parsing out the difference between that and PE and actually suggesting that maybe humans are, maybe we’re being a little bit too bullish of our ongoing role on the judgment side, but I don’t know.

It does seem to me, Friddy, that we’re… You’re asking businesses to maybe exercise a bit of a different muscle; at least some of them are used to exercising. In that, we’re seeing that as we think about these entry-level roles, it’s not just about the jobs to be done, but it’s about crafting those roles in a way so that we have a pool of experienced applicants for other jobs to be done later. And that takes some… it just strikes me that takes some longer-term thinking. That at least some of the folks who are chasing quarterly results maybe aren’t going to be as capable of. It feels pretty tempting to just cut 20% of the workforce because you were able to leverage those efficiencies and eliminate those entry-level positions.

I guess you’re seeing that in your work? Is there a bit of a distance between people who are very clearly looking at the role of entry-level jobs as a long-term feeder for the organization, versus others that may be more likely to give it away? 

Friddy Hoegener: Yes, I do think so. And it feels like tech is at the forefront of eliminating those. Early-level roles in terms of coding and what they are seeing. And I do think other industries, right? And there’ve always been industries that, that take longer to adopt certain technologies. I think larger organizations, in general, are slower at adopting new tools and new technology. And having worked at ABB, I’ve seen it myself, right? It takes a long time for a company in the Fortune 500 to adopt technology like that; they need to evaluate the business case, and do an analysis of how it’s gonna impact everybody. It’s a grind, right? It’s bureaucracy.

Everything is slow, everything. So, smaller companies certainly have an advantage in being more agile and being able to adopt technology more quickly. And I think some of those smaller companies, I think, are right. I can see two ways this can go. Company A says we’re, we are happy with where we are, we’re gonna replace the people we have with AI.

And it immediately affects our bottom line. The other company could see this coming and said, Okay, instead of replacing these people, we create new roles for them, and we ask those people to create business value for us. What can you do now with AI? To help grow our company. And I think some of those companies are gonna be able to see tremendous growth because they get new ideas, they get a fresh perspective from those earlier, early candidates. And I think while company A might be able to stay steady and just have a bigger profit margin, company B might be able to grow much quicker because they’re still utilizing AI, but they’re also seeing the need to further invent, innovate and grow. And for that, I think AI is not, in my mind, capable of doing that.

I think AI is good at replacing your tactical tasks. But getting AI to invent and grow and kind of create a business case, work with stakeholders across the company and look at things that haven’t been done before. That seems to me still a stretch for AI to accomplish. 

Carman Pirie: You paint an exciting picture of a really interesting levelling opportunity here. Like I could think of folks working from maybe more, family-owned manufacturers, smaller to mid-size manufacturing organizations that feel, from an HR perspective, from a talent attraction perspective, that probably feel outgunned by some of the big, well-funded, publicly traded competitors.

And you just painted a picture of, yeah, they, they may be better funded, but they may be slower to move, and therefore the attraction to that entry level talent may swing a little bit more in the favour of the small, the mid-size manufacturers. I think that sounds exciting. 

Friddy Hoegener: I do think that’s a great point and a very real possibility that those smaller organizations now can offer those early career graduates something that the larger organizations just can’t. And I do think that’s gonna be interesting for those candidates. And really exciting too, because you might not fully eliminate the grunt work for early-level careers, but you probably don’t have ’em do this a hundred percent of the time. You can probably offer them 20 30% of their time where they can be more innovative.

And I think that’s something that probably started with my generation as a millennial, right? We’ve always wanted to do more than just waste our time, wait until it’s our turn and just do the grunt work. I think starting with us, we always felt like we wanted to be more involved sooner and have more agency, and that just really, very rarely has been the case. And I think with AI, you take some of the danger out of giving some of that to the inexperienced candidates or inexperienced employees because they don’t have AI to fall back on and say, yeah, what you are trying to do, there is a nice idea, but here’s why it wouldn’t work. It gives like guide rails to college grads and to people who are early on in their career, that we didn’t have, but maybe also gives them the opportunity to be more impactful. 

Jeff White: I do wonder, though. The level of strategic thought for the types of early, early-career candidates we’re talking about is probably higher than we might’ve thought before, and may make recruitment even more difficult because there are so few people who are able to.

If you want to hire somebody and say, Okay, you’re going to come in, and I want you to spend a quarter of your time to a third of your time thinking strategically about how to improve the overall business. There aren’t as many people at that early stage of their career who are potentially going to be able to do that.

Friddy Hoegener: Yeah. And that’s why I think AI can provide those guardrails, right? And be a sounding board and say, if I have this idea, AI can immediately kind of spitball. And I think AI, I’ve found personally, is a great sounding board, right? A lot of times, I have an idea, and I just throw it in there and be like, tell me what the pros and cons are. So I think a lot of that learning that typically happens over years with a manager, right? When you have an idea, you go to your manager, you sit down, and they explain it to you. That time can be condensed with AI, and AI can provide some of those guardrails where you don’t go off into those very ambitious avenues.

Carman Pirie: Friddy, I feel like if I don’t ask you this question, I’m missing the boat, because somebody who deals with them. Recruiting new talent every day. I’ve gotta ask, what do you want, what do you wish people looking to break into the world of manufacturing, and what do they need to know? What tips do you want to give them to be successful in gaining these entry-level roles, and even these management roles and beyond that, you’re recruiting for? What’s the secret sauce that you wish they had? 

Friddy Hoegener: I think what companies are looking for is some of those old school soft skills, right? The willingness to learn, the willingness to put in the hours. Somebody who says I’m coming in here and I’m willing to do the things that it takes. I’m eager, I’m hungry. I want to work, I want to make this company better. Paired with an interest in AI, right? Somebody who’s coming in there, they’re not interested in data, they’re not interested in AI, they’re not good with the systems and the tools. It’s gonna be a challenge. So I think it’s that mix of the right… Somebody who comes in as an early career and says it’s all about work-life balance. I think that’s kinda been a sticking point for a lot of companies, and a lot of our clients say if somebody mentions work-life balance, when they come in here with two years of experience, we’re immediately just stopping the process here.

So companies are looking for people who are willing to grind, right? But also, they don’t want to stagnate; they’re looking for people who are looking to grow. They’re looking to innovate in some sense, have some of that entrepreneurial mindset. But I think in turn, companies are more willing to take these candidates more seriously and give them more agency and give them more responsibility. I think what wasn’t the case 10, 15 years ago, right? Those companies weren’t willing to give those early career employees the responsibility or the platform even to share their ideas, right? It was your time is gonna come. You sit there, you do your work, and if you’ve done it five years, six years, 10 years, then you get to a point where we take you seriously. I think there’s a little bit of a shift where companies are willing to give that agency sooner if they feel like the candidates are they have the right mindset. 

Carman Pirie: That’s a fascinating perspective, Friddy. I feel that based upon that response, I feel that I could ask you another hour of questions, honestly. But thank you for sharing your insights with us today. It’s been wonderful to have you on the show. I think it’s just been a really interesting conversation. Thanks again. 

Friddy Hoegener: Thank you so much for having me. 

Jeff White: Yeah, it’s been quite wonderful. Some great advice for both job seekers and hiring managers there at the end too, and throughout, so thanks.