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Steve  1:01  
Welcome to the System of Record show. My name is Steve Boese. I am thrilled for today's show. Right now, the conversation around AI at work is almost exclusively around knowledge workers, desk workers, people who stare like me at monitors all day, which we know about dashboards and agents and coding assistance, right? We're talking about that constantly. You see that a lot in the media. We're talking less about where real work gets done, right in America and around the world, quite frankly, in factories, in distribution centers, out in the field, by frontline workers, by any estimates, 55, 60, 65% of the US workforce are front frontline workers. AI is playing a role there, and we want to talk about that today on the show, and we have a great guest who can talk about that with us. He is Chris Kuntz. He is the VP of Strategic Operations at Augmentir, which is a fascinating company that's sitting at that intersection of empowerment of the frontline worker and bringing advanced technology into the enterprise to support these workers. So Chris, welcome to the show. How are you today?

Chris Kuntz  2:10  
Great. Steve, thank you so much. Really excited to be here. And as you you mentioned, I think this is such an important topic, it isn't talked about enough. These deskless workers that represent the majority of the workforce. They're underserved by technology, but I think there's a real unique opportunity on using and applying AI to augment these workers, you know, in a different way, not replace these workers, but augment and empower them to do their best work. So really excited about this conversation. And again, thank you for having me on.

Steve  2:40  
Yeah, thank you, Chris. Let's start with for folks who may not be familiar, first, I love a little bit more about you. We talked a little bit in the pre show you. You live in my former home base, Rochester, New York area, which I have fond memories of. But let's learn a bit a bit more about you, Chris, and then tell us about Augmentir and how Augmentir sits in this enterprise ecosystem.

Chris Kuntz  2:59  
Yeah, sure, yeah. So I live, born and raised, in the Rochester area. I live here with my family, currently. Myself, I have 30 years or so in the emerging tech space, mostly focused on the industrial software side of things, varying roles, mostly on the go to market side. But I've been fortunate to be part of a team of serial entrepreneurs, where we have built companies that have been at the forefront of some of the most exciting advancements in technology in the industrial sector, dating back 20 plus, 30 years ago, our last endeavor was thing works, which was an industrial IoT application pioneered how equipment, industrial equipment, becomes smart and connected. And it's interesting that I bring up that analogy is because when we left and in, you know, the team decided to come back together, we looked at the industrial space, specifically manufacturing, and recognized, you know, talking with customers, recognized that the humans were the missing piece of this whole industrial transformation, you know, industry 4.0 5.0 whatever you want to call it, that that equation, the humans have been largely underserved by technology in this whole space. And so how can we just in the same way that we made equipment and machines smart and connected. How can we do the same for the humans? And it's become more of an important topic now post pandemic, and if you look at the manufacturing workforce, five, seven years ago versus today, completely different, a new set of challenges. And I think technology plays a big role in helping to offset some of the issues caused by those challenges.

Steve  3:45  
Yeah, thank you, Chris, for that background, and appreciate you sharing that. And I agree with you totally right, like the shift in the requirements and the expectations in the frontline workforce, in the manufacturing workforce, is quite remarkable, and then at the same time, we continue to hear that employers just can't find enough folks as well. So that sort of indicates to me that employers today have got to try to get a little bit more efficient, get a little more productive, get people up to speed faster, right when they do get hired in. And these are all applications where AI can step in and play a role. So let's talk a little bit about Augmentir and how you support your customers and actually making those making those production enhancements or those transformations possible. 

Chris Kuntz  5:35  
Yeah, so Augmentir is an AI first company, founded and launched the product in 2018 and what we focus on is what we consider to be the most important problem in manufacturing today. It's the impact of not just a smaller workforce, but a less skilled and less experienced workforce. If you look at the average tenure rate five to seven years ago was, you know, 20 years now it's, you know, less than three years the time and position is down from, you know, seven, you know, seven years to nine months, the job quitting rate in the first three months of employment is up 50% and you know, so HR leaders need to rethink how they're onboarding workers. You can't spend six months onboarding a frontline operator if they're going to leave in three months, right? It's just not going to work anymore.

Steve  6:27  
Yeah, that level of churn, the cost to their the cost, and cost, hard cost, as well as lost productivities.

Chris Kuntz  6:36  
And so you think about it, yes, there's a skills gap, yes, there's a labor shortage, but it's an experience gap as well, and that causes issues. It causes safety issues, causes quality issues, product recalls, it causes downtime. You know, a lot of that can be attributed to human error, because these, you know, the workers, they're human, they make mistakes. And if they're less skilled, less experienced there, they may make more mistakes. And so we focus on addressing that and the technology space that we're in, you know, most, most of the industry calls it the connected worker space, but what we're thinking about is here, connecting these historically disconnected workers and connecting them in the way, not just with a phone or a tablet or a wearable device, but connecting them to the digital thread of The business so they are integrated through a single interface into the ERP systems, the learning management systems, the HR systems, and they can be an active participant in the digital ecosystem of a manufacturing environment.

Steve  7:33  
Chris, thank you for that. How does this show up then? So if I'm I'm one of these workers, say, in a manufacturing environment, and they're the customers working with Augments here to improve workflows, to improve training, etc. What would be one or two of those kind of use cases where me, like as that worker, would see this and reflect in my workflow or my day to day?

Chris Kuntz  7:54  
So one of the interesting things about manufacturing, and you can say industrial in general, because energy utilities, mining, oil and gas, they're all you know, similar in a way, where, if you look at broad set use cases of equipment, operation, maintenance and repair safety, quality and employee training and workforce development, those are common across many sectors, in manufacturing, in any industrial setting, and not just that they're common, but there is standard work that you have to follow to ensure that safety is is upheld, to ensure that processes are followed, to ensure that a product is created correctly. And historically, many of those work procedures were done on paper, or, you know, in in someone's head, right? And so we look at this as a as a digital maturity, where first you're digitizing work procedures, but once you digitize work procedures and digitally connect workers, you can then learn a lot about how they're working and what they're working on, what their skills are, what their certifications are, and how they're actually performing on the job. With that data, then you can, you can act more intelligently on how to improve their performance, how to potentially rescale or upscale, how to drive continuous improvement efforts. So broad set from a use case standpoint, safety, quality, maintenance, equipment operation, those are common across all of our customers. And really, you know, digitally connecting those workers, using that data to continuously drive improvements within the operation.

Steve  9:29  
Yeah, the second, the thing I was thinking about, Chris, as you were just describing that use case was, it seems to me that the level of information and potential insight that feeds back up the up to the plant managers, or the, you know, the line managers, whoever the case may be, that's got to be quite remarkable as well, compared to, say, backward looking reports, you know, at the end of a shift or the end of a week, right? I can you talk to me a little bit about the types of information and maybe decision support tools that become available to folks who are making those decisions.

Chris Kuntz  10:05  
So it's really interesting, when you think about skills and certifications for frontline operations, you know, it's sort of like a driver's license. We took our driver's test. We passed a driver's test that says nothing about how we're driving a car today. You know, 10 years later, five years later, whatever it is. And so what we're able to do now with a digitally connected workforce is capture information on how those workers are performing. And that could be, and we capture dozens and hundreds of data points, but it could be, how long did it take them to perform a routine? It could be, what was the output of that procedure or that job. Did it result in scrap? Did it result in in rework? Did it result in a safety incident? Did it result in equipment downtime? Did they have to repeat a step five times? You know, if they're going through a procedure, and it's a digital procedure, and there's a little helper that says, Here is all you open the back panel of this filler before you perform a cleaning routine that they have to watch a video on that five times. Those are all indicators of something right. They're indicators of your your your competency and performance level, or potential indicators where their targeted training might be important, or where the the content is lacking, and maybe the content needs to be improved. And so being able to surface all those signals, we have a library of dozens of machine learning algorithms that take that information and surface insights into where are the continuous improvement opportunities? Is it in the individual? Is it in the work process? Is it in the cohort of workers that have been, you know, trained or onboarded in a certain way. And so those those surface incredible insights for manufacturers that they didn't have before. And you know, yes, if you had a very stable workforce, you might just know who knows what and what they're good at and what they're not good at, but with the dynamics of today, when they're changing so often, and job quitting is up, you don't have that information. You know in the back of your mind, it's not as available, and so being able to surface those insights is incredibly important, and that's where I think, you know, when we started, one of the first applications of AI was to surface this data around continuous improvement. But it's now gone way beyond that. When you think about factory assistance, you know, and AI agents that can then act on this data. It becomes incredibly important, incredibly interesting.

Steve  12:26  
Yeah, I want to come back to AI agents in a second. One of the other things that I thought about is I thinking, you know, we always look at work through our own lenses, sometimes, right? And I think about some of the jobs I had back when I was younger, in industrial settings, and a couple of places I worked where was an AI at the time, but it was, you know, we had pretty substantial monitoring things and performance tracking going on. And I'd love for you to comment a little bit about how you guys think about the worker experience with some of this in these of the like tools that are empowering and enabling and supporting training, right? Versus, hey, this is I'm really feeling like I'm being watched overtly, right? Or I'm being micromanaged, or I'm being monitored, whatever the term you like. How do you guys think about that from a balanced perspective? Right? Because these are people, right? They're not machines themselves, right? I love your your thoughts on that, and maybe some of the feedback you see from the field, from from folks who are implementing these systems. 

Chris Kuntz  13:27  
So what's really interesting is so we certainly aren't the first company to think about digitizing work instructions and and putting technology in the hands of workers. I mean, that's been going on for years. The difference is looking at it from a operational standpoint, versus looking at it from an HR standpoint. And worker empowerment. Many of these workers, all they want is to be empowered to do their jobs correctly and safely, so they can go home that night, so they can, you know, not struggle, not feel like they're contributing to the problem, but feel like they're contributing to solutions. And so when you think about when you put your HR lens on this, you can then look at, what information can I give workers so that they can do their job safely and correctly? Can I reward them or badge them if they are contributing to a solution they detect an oil spill? Do they submit that in their digital device as a safety incident report. That's an indicator, that's a sign that that worker is engaged. It's a great signal for HR, right? How do I reward them for doing that? How do I reward them for efficiency on procedures? And so I think really, and this is also bringing together HR and operations where they've historically been disconnected. 

Steve  14:42  
Yeah, completely disconnected. I've done this show for 15 years, Chris, I've, I've had two conversations maybe, about connecting HR digitally, right to operations. It's just not a topic HR talks about at all, as far as I go.

Chris Kuntz  14:57  
And just a quick story, one of our. Our customers, long customers, Colgate, Palmolive, you know? And many, many customers come to us with this. So they're like, Okay, let's focus on use cases, maintenance, quality. Maybe those are use cases I want to focus on first. And so there are digitizing procedures, but then they come across those issues. How do I know when to schedule work for someone, or if they're able to do that work, oh, it's in some skills matrix somewhere that's in a spreadsheet in some HR system. Well, the operations lead doesn't have access to that. Or maybe they have to log, you know, go find and log into a system. What if you could, you know, take that skills matrix and put it in the same system that's driving the operational work. Isn't that fantastic? So that's what we have, you know, the ability to pull that in, but they're so disconnected today, you know? And then once you can do that, now HR can look over and say, Oh, now I know where the gaps are. Now I know where the where the reskilling or upskilling or potential, you know, targeted training needs to happen. Now I can measure the effectiveness of my training a big black box. If you talk to HR, folks are like, I don't know how to justify my budget because I can't measure the effectiveness of training. Now they can, right? So bringing together those, those two sides, I think, is a big piece of this for sure.

Steve  16:13  
Yeah, and the worker empowerment angle here, Chris, I think is, don't want to underestimate that. I think you were spot on when you said, the vast majority of folks, they want to come in, do a really good job, have see some success, see the results of their efforts, understand how they're contributing to the overall, the goals of the team, the goals of the shift, the goals of the company, etc. And then, you know, be fairly rewarded for that, of course, as well, via recognition. Of course, via compensation, you know, all the things right. And making this through line between, you know, those, those desires, right and those outcomes, is, to me, is where you guys are sitting, which is such an important place, you know, in the employee experience. And again, I think really, really important as well.

Chris Kuntz  16:59  
Another quick thing. Sorry, I wanted to just dive into this because you mentioned, you know, is it someone looking over your shoulder and you know, the worker? 

Steve  17:09  
I was thinking that a little bit, yeah. 

Chris Kuntz  17:10  
What's really interesting is our most successful customers, when they're rolling out a connected worker solution like Augmentier, they're involving their frontline workers and their operators early on in the process, so they can be part of that feedback loop, part of that change management process, because it is disruptive, right? But our most successful deployments are ones where they're involving the users early on in the process, and they feel like they're part of the solution, which completely removes that, Hey, there's this digital technology looking over my shoulder, right? It completely removes that, that insecurity.

Steve  17:43  
Yeah, I love that, and that's one of the fundamentals, right? We've talked about forever, right? In especially in enterprise tools, right? How do you get buying, how do you get success? How do you make sure that what you're deploying isn't just another, oh, my god, here's another admin tool, right? That someone's going to require the key here, and I think I read this in some of the Augmentir literature. It's about helping the technology, enabling people and serving people, not making people just serve the technology, right? 

Chris Kuntz  18:13  
Yeah, absolutely. 

Steve  18:14  
CRM has been like that forever. I know I talked to folks who like who hated their CRM because they felt like all I ever did was type data in my CRM and never helped me do anything, right? All I did was put what I did into that, and I never got anything back, right?

Chris Kuntz  18:29  
But I love the stories that we get from our customers, the operators. You know that the quotes that we get from the operators are the best quotes? You know? Yeah, yeah. It's great to get it from the supply chain leads that are talking about technology, how it's transforming their business and whatnot, but to get positive feedback from the operators on how it's making their job easier, I was making their life easier is that's, that's what's rewarding about this. I mean, they're truly embracing it as technology that's supporting and enabling them, versus versus anything else, and that that really hits at home for us.

Steve  19:01  
Yeah, I think that makes perfect sense. And when you're impacting, I think the most effective and the most, I don't know, just inspirational kind of stories we hear in the tech space, because it can be kind of cold and it can be kind of dry at times, right? But when you, when you, when you distill it down to its impact on individuals who are real people with often very hard jobs, right? Not, you know, physically demanding jobs, cognitively taxing jobs, jobs that require, you know, skill and attention and physical all that, and you can make those lives better and make those jobs better. I don't think there's anything more important, right, in what we do as technologists, in how you know AI is getting applied and other technologies are getting applied, it's really noble thing. And Chris, you mentioned agents, right? And I feel like in 2026 talking about the extension of AI into. Agentic is, I mean, I guess it's a requirement. The HR side is talking about it constantly. I probably spent the last half of 2025 every conversation I had with the technology company was talking about their their slew of agents and and I guess you guys are talking about it too. Is is it something that's really going to change how we support workers and enterprises are going to implement these tools like actually configuring, enabling and activating agentic AI in the enterprise? And I'd love for your comments on that. And then, how is it showing up, if it is showing up so far?

Chris Kuntz  20:35  
Yeah, absolutely. So what's interesting for us? You know, we're AI first company. We've been using AI since the beginning. What we started out is on the data side, so using a series of machine learning algorithms that assess the data that's collected from frontline operations and from workers to improve and continue to improve their performance. And what we talked about previously in was it 2023 we launched our factory agent. It's called Augie. That's more of a generative AI assistant. So if you think you know Gemini chat, GPT, but for the industrial setting, and why is that different? Because that factory assistant has to know who you are, what skills you have, what job you're working on, what machine you're sitting in front of. It has to have context into the work, because the answers it gives you has to be, you know, correct and very relevant to your job, right? But then with agents, I think it's taking that to the next level, where these are really digital workers. They are digital workers acting alongside humans in a factory setting. They are intelligent. They can act on data. They can do, you know, that invisible work, right? That work of trying to understand where the continuous improvement opportunities exist, trying to do, I mean, there's a lot that's happening, you know, right now in terms of, like, you know, materials ordering, or, you know, Scheduling Optimization. There's a lot of that. But we think it can even go down to the true frontline operations in the next level. If you think about a training agent, a digital lean coach, a skills agent, you know, or a "5 Whys" agent, you know, we think about like root cause analysis. Why is the machine going down all the time and doing my "5 Whys" analysis, and as my team of continuous improvement engineers doing all this stuff. Why not have a digital agent sitting there at the worker that has has access all the data, has access to all the equipment information in the history of that equipment has accessed all the worker information. You can ask it questions, or you could say, act on this data when these conditions happen, because that's what's going to save me time. They're not going to do my human work, right? And so agents as digital workers. It's happening. It's really exciting. What Our Customers Are Saying, Hey, we're building, we're going to build a quality agent. It's going to do XYZ. It's just fantastic. You know, hear the stories. But the other really important thing is, early on, there was this, okay, so how do we trust agents, right? Like, sure they start a line. Can they stop a line? Can they do a shutdown? You know, it gets kind of scary when you think about humans are sometimes there. And so we developed what we call the six laws of agents in the industrial setting, which helps sort of safeguard agents for industrial use, and so things like, you know, you have to anything that's generated with AI has to carry that label, you know. So if it's a troubleshooting guide that's generated with AI, which could be completely relevant, you have to have a disclaimer that was generated with AI. 

Steve  23:38  
Makes sense. 

Chris Kuntz  23:39  
An SME might have to, like, put their stamp of approval on it, or something even down to things like, no generative AI, when you think about human safety, right? You can't have non deterministic AI code trying to do something that might impact human safety. That has to be deterministic, and then the concept of humans in the loop. So if, if you do have a situation where your AI agent could start and stop a line or do something impactful, a human has to be in the loop to be able to perform a final level of approval on that on that step. And I think that helps safeguard, helps put the right guardrails in place, so that that these, these companies, these industrial enterprises, can feel confident that it's truly supporting their operation.

Steve  24:28  
Yeah, Chris, yeah. I think what, what I'm getting from this, and hopefully the audience is getting as well, is like we're just now tapping in to the capabilities and the potential of some of these tools to really transform the experience of work and how work is done at a really hands on frontline level, you know, out again, outside of the offices, outside of the screens, and where works getting done all across the country and in enterprises and facilities all around the world. And it's, it's wild, and it's fascinating, because I think, I think making work better and a better for everybody is kind of why we're all here, right? No matter what, where we're sitting, and especially these jobs, which can be so difficult and so challenging, and honestly, right, as you said, folks are coming into them, maybe not totally prepared. The technology on the operation side is advanced. That's probably another show right to how operations, technology itself, and the requirements and the knowledge that these folks need to have is quite a bit different, right, than it used to be 10, 20, years ago, for sure, as well. And so keeping up is the challenge, right? Yeah, one of the things Chris, I guess the last thing maybe I want to talk about a little bit is, I think we touched on a little bit with agentic. But you guys are probably working with some of the very progressive, forward thinking companies that are really thinking about, hey, how do we make work better? How do we improve outcomes? How do we improve safety and processes? What's exciting you about the next year or two in the in the frontline worker space, connected worker space, you know, what do you what do you think? Boy, this is going to be really interesting to watch. And we're working on this really cool thing. Whatever case may be, what's got you jazzed up, because I can tell you, really excited about this. And you, yeah, you love it.

Chris Kuntz  26:15  
I mean, so, I mean, we, we work with some of the biggest companies in the world and different manufacturing sectors, you know, Colgate, Palmolive, Hershey, and in these companies, they're, they're truly innovative leaders in their space in terms of, you know, think about digital transformation all the way down to the front line. And what's been really interesting is seeing, you know, roles created within their organizations, like people capability leads, you know, these roles that blend HR and operations, and they're focused on worker empowerment. They're focused on tapping into, you know, how do we make the performance excellence happen? You know, on the front line, that's what's exciting. They're they're looking at, you know, what signals can we get from technology that can help improve worker retention. Help, you know, reduce onboarding. How do I move training into the flow of work so that, you know, we're not, you know, slogging through six months of onboarding time. And it's really exciting to see companies embrace the HR angle and to see that come together. I think it's really exciting to see these companies look at truly ways to augment the workers. I mean, no one in manufacturing anyway, no one wants to fire anyone. I mean, they can't find anyone to hire anyway. There's such a job shortage. But they're truly looking at what things can I do to empower the workers, to make them feel better about themselves, you know. And then that may be tied to salary or promotions or maybe tied to, you know, certain, you know, bonuses based on based on performance. But that's what's really exciting is, is taking the people side of it forward again, these companies, I think, you know, Hershey recently put out a great article on this. And really the the blending of and we hear about it all the time. People process and technology. We all hear about that, but it sometimes it's not as easy to do, right? And the, you know, companies like the colgates and Hershey's that do that well and really include those frontline workers in as part of their digital transformation strategy. And that's, that's true innovation there.

Steve  28:18  
So, Chris man, that is a great way to sort of sum up the conversation. I I'm excited I brought down. I want to go get in touch with the Hershey folks and talk to them about it, because it sounds like Hershey, right? Who doesn't love that? But, you know, just, just to talk about that experience would be, I think, a fascinating maybe follow up to this conversation. But I'm super excited, Chris, that we were able to talk to you today and really start to pull, pull the blanket down from what's really happening with these advanced technologies on the front lines. Because I think it's fascinating, it's exciting, it's empowering. And Augmentir is like at the forefront of it, doing wonderful work. So I want to thank you again for folks who want to learn more certainly about augment here. We just send them to the Augmentir website.

Chris Kuntz  29:04  
Chris, yeah, augmentir.com Yep. Happy to, you know, connect on LinkedIn, if you can search for me on LinkedIn. Happy to connect and answer anyone's questions offline, for sure. 

Steve  29:16  
If you're an HR person listening to this show, which I'm sure there's plenty, I think you can really think about what Chris talked about, about making those key connections between kind of the HR kind of things, on training, on skills development, on workforce planning right and recruiting, right, and onboarding and and the real outcomes that are happening in operations, In, you know on the lines and and how traditional HR tools aren't going to be enough right to help you make those connections, because they're just not right. You need more, and you need you need to think a little bit differently about it, and certainly, working with folks like Chris and the team at Augmentir here would be a great, a great opportunity for you. So, Chris, thanks again. Man, it's been great to meet you. Shout out to Rochester, New York, my old hometown. I miss it, but hopefully I'll get back there soon. And thanks again for joining us on System of Record today.

Chris Kuntz  30:12  
Yeah, thank you very much. It was a pleasure. Thank you.

Steve  30:14  
Awesome, great stuff. So thank you to Chris again. Thanks everybody for listening. Check out all the shows on the HR Happy Hour Network. Go to hrhappyhour.net, and follow along, System of Record, coming back soon, hopefully with stories from the frontlines of the candy factories. Anyway, my name is Steve Boese, thanks for listening. We'll see you next time, and bye for now. 

Transcribed by https://otter.ai