Artificial Intelligence Podcast: ChatGPT, Claude, Midjourney and all other AI Tools

Can AI Learn to be Lean with Chad Bareither

• Jonathan Green : Artificial Intelligence Expert and Author of ChatGPT Profits • Episode 389

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Welcome to the Artificial Intelligence Podcast with Jonathan Green! In this episode, we dive into the powerful intersection of AI and lean operations with our special guest, Chad Bareither, founder of Bareither Group and expert in operational excellence, continuous improvement, and lean thinking.

Chad brings a grounded, real-world perspective from years of working with manufacturing and utility companies. Together, he and Jonathan unpack a critical question for modern businesses:

Is AI actually making you more efficient—or are you just doing the wrong things faster?

They explore how easy access to AI tools can tempt leaders into “more, more, more”: more posts, more tools, more projects, more data. But without clear goals and a solid process, AI becomes an accelerant for chaos instead of a driver of meaningful results.

Chad explains how applying lean principles—clarity of purpose, focus on value, and disciplined measurement—can help business owners deploy AI intentionally, not emotionally. Instead of throwing AI at every problem, he shows how to treat AI like a team member: define its role, set expectations, and measure outcomes.

From manufacturing lines and data lakes to social media strategies and boutique consulting practices, this episode is a masterclass in doing less, better—and making sure AI serves your business instead of overwhelming it.

Notable Quotes:

  • "There's nothing more wasteful than doing efficiently what should not be done at all." – [Paraphrasing Peter Drucker, cited by Chad Bareither]
  • "AI is just an accelerant. If you have a bad process, you’re just going to do it faster." – [Jonathan Green]
  • "I like to think about any type of AI solution you're putting in as a team member. What is the role of that team member, and how will I measure whether or not it's being successful?" – [Chad Bareither]
  • "You have a presence, but you don't have a following." – [Chad Bareither]
  • "The more viral something is, the less likely it is to appeal to your ideal customer." – [Jonathan Green]
  • "What’s really going to eliminate your business is not AI in itself. It’s bad scoping and weak process." – [Chad Bareither]
  • "We’re keeping people busy generating AI that’s generating a bunch of stuff—and this ‘more’ is now just amplified." – [Chad Bareither]

Connect with Chad Bareither:

Chad and Jonathan reveal how less but better thinking, combined with smart AI deployment, can help small and medium-sized businesses avoid costly mistakes, stay focused on what matters, and build operations that scale sustainably.

If you’re interested in how AI can support lean, focused, and truly effective business operations, this episode is a must-listen!

Connect with Jonathan Green

Jonathan Green:

Can AI learn to be lean? We're gonna find out today's amazing special guest Chad Bareither. Welcome to the Artificial Intelligence Podcast, where we make AI simple, practical, and accessible for small business owners and leaders. Forget the complicated Tech talk or expensive consultants. This is where you'll learn how to implement AI strategies that are easy to understand and can make a big impact for your business. The Artificial Intelligence Podcast is brought to you by fraction aio. The trusted partner for AI Digital Transformation at fraction A IO, we help small and medium sized businesses boost revenue by eliminating time wasting non-revenue generating tasks that frustrate your team. With our custom AI bots, tools and automations, we make it easy to shift your team's focus to the tasks that matter most. Driving growth and results, we guide you through a smooth. Seamless transition to ai ensuring you avoid costly mistakes and invest in the tools that truly deliver value. Don't get left behind. Let fraction aio o help you stay ahead in today's AI driven world. Learn more. Get started. Fraction aio.com. Now Chad, I'm really interested in this idea of lean operations because the promise of AI and the reality are very different. The promise of AI is you can do five days of work in four days or three days, but nobody's getting less hours. And what we're seeing a lot of is now you have to do more and stress is going up, not down. So the promise of AI was AI will do most of the work, right? And then it's really not turning into that. So I'm really curious as an expert in the idea of lean, which is like just do the necessity. Ai. The problem with AI is it can do everything. I see so many people have this temptation to take on more tasks. They go I've got two free hours today. Why don't I launch a new division or expand and I'm guilty of this too. And it's like a goldfish. You put it in a bigger bowl, it keeps getting bigger. So no matter how much, if efficiency we get, we still wanna work those extra hours.

Chad Bareither:

Yeah. So it. It's, I love the analogy of the goldfish in a bowl. Most of the clients that we work with are in the manufacturing space. So if we start from there and bring the analogy back into AI and freeing up your capacity, oftentimes we're throwing people at a problem. And now if we say we're throwing AI at a problem, it's like we're trying to go faster, and maybe not really understand the problem that we're solving. So a lot of the times with clients, like we're asking to slow down, focus on fewer things, understand what really works. And I would say the same thing in this AI space, right? So if I'm speaking to independent consultants, boutique consultants, which we are is saying if you free up time, like launch more, I'm gonna do a podcast, I'm gonna do video, I'm gonna do whatever. It's are we pausing to actually reflect on what's working? Like more is not necessarily always the answer that's gonna get the attention of the client that's gonna speak to the specific problem because that's where the value that we have as consultants right. Is understanding the problem and being able to speak to the people that are experiencing the problem.

Jonathan Green:

Yeah, I know you're in manufacturer. I was thinking it's if you, sometimes you see the person, like I watch a lot of forged in fire and there's the person who has a ton of money and they buy every different thing for their forge and they know a little bit about everything and you can't, you don't master. So they can't really make anything. And it's the same thing where you have this temptation to go I want every type of machine and I make knives and swords and maces, and they're all different. And that's really the area I'm into, which is like because AI's become so cheap and affordable, it's now I can add in eight other tools and we forget. I think the thing people are really forgetting is to ask that critical question of do we, what problem does this solve? What's the benefit? And then what's the learning curve? So with every new tool. There's a dip, even if it's gonna make you more efficient in the long run, there's a dip as people have to relearn a behavior, whether it's walking to a different station. We've all done that, where we accidentally drive to our old job and we go, what am I doing? It's like a learned behavior or we, and then you have to retrain yourself not to do that thing, and it's this dip in efficiency that people are surprised by suddenly, and it's learning anything new you're bad at first. Even though AI increases your efficiency or a new tool, increases your efficiency we have to learn the protocols and how it works and there's always something that's a little different whether the buttons are in a different place or it uses a different tool and as part of its process. And I think that's really where we're starting to see people pile up because you go I can do a bunch of new things and I, why aren't I more efficient? You start to get, I think of sometimes that I love Lucy Skitch where the things going so fast and the chocolate's getting everywhere and the conveyor belt just goes faster and faster, and that's what it can start to feel like because you skip the strategy phase, which is very common now with businesses, especially digital type businesses, because you don't have to do a business plan. So if you wanna start like a manufacturing business or get a bank loan, you have to show up with a business plan. Here's what we're gonna do, here's our strategy. If you're starting your own business, you can bypass that, which means you can start faster. But it's it's actually useful because you need those metrics. And I say, why am I doing this? And I often find when I ask people, they go, I wanna do this. And I go, why? And they go, I don't know, seems like it. It's like the most common answer I get is it seems cool. Or I like the person. Depending on if I'm talking to a startup, I go, why are, what problem does your software solve? They go, oh, we don't know yet. I'm like, okay, that's worrying. Or they buy a software because they like the salesperson. It seems cool. And I'm like when you buy emotionally or when you add a strategy emotionally, like the number of people who start a podcast and I go, why? What's the end goal for, it's so important because it changes your entire strategy and changes the type of guests you have. It changes the type of questions you ask because they just go I just want one. Okay. It's like a labu boo. That's worrying. That's a worrying decision. How can we, with this temptation, right? It's like you have so many options and suddenly you become frozen. Too many options is actually a bad thing. So how can we pull back and become a little bit more lean in our decision making?

Chad Bareither:

Yeah that's great. The too many options. I just had a conversation with a colleague about this. It's like you go to the grocery store and like, how many options do I need for toothpaste? It's like mints and 70 varieties of mint. Yeah. You can be paralyzed and AI, as it's continued to evolve, can do a lot of things. And then suddenly you're as the business owner and you're growing and you're like, I need to do all of these things. It's a great question. Why do you need to do each of those things? Every engagement that we start with so if we're outside of AI and then bridging that analogy back into it is we start with the why, like why does this business exist? What are you trying to accomplish? And then what are the goals that you're falling short on? So if there's a specific goal in your business, I know your audience, like small, medium business that you're trying to accomplish and you need capacity or throughput that automation and artificial intelligence can provide. Great. What are you trying to accomplish? Can you measure that so that once you deploy one of these tools, is it actually helping you? Is it actually saving you time, or are you spending more time on the backend to filter through illegitimate leads to to counteract like comments on posts or posts that wasn't exactly what you implied by that. So it's really important I think to start off with, what am I trying to accomplish with deploying this particular tool? If we think about, I like to think about any type of AI solution you're putting in is like a team member. Granted it's free or very little cost, but I'm gonna bring a team member on that's gonna do something for my business. What is the role of that team member? What are they supposed to deliver and how will I measure whether or not it's being successful? So I love like these new tools and products. A manufacturer wouldn't just up and say no market research, no direction. We're just gonna start making something and hope someone buys it. And it can be a lot of the same thing that you're talking about. It's like we're I think I'm supposed to put content on LinkedIn, so I'm gonna have a bot tool. Okay what are you trying to accomplish by posting on LinkedIn? Our awareness reputation, thought leadership leads, like it's very different the direction that you're trying to head. And without that feedback loop on the backend of saying is it accomplishing what I want it to accomplish? It's the same thing as saying, deploying a new physical product without ever thinking about, I don't even need to know whether or not there's a market. For this potential sales. The other two things that you mentioned that are very important to think about, so one is just the metabolism that your organization has for change. So we're gonna change the way we do things and automate it, et cetera. Can we handle that much stuff going on? Because now that, yeah, I have all these AI automation workflows launched, who is keeping track of what's happening there? There's still some work on the backend to make sure it's working and it's working correctly, and it's giving you quality outputs from that. So I think one of the most important thing is on the front end is thinking about that. That why that strategic element. And so that is a very lean mindset of saying, what am I trying to accomplish? What is the output of this potential process? And then it's this feedback loop. We refer to that as the Deming cycle, so it's an acronym, PDCA plan, do check act. So if I'm gonna launch some sort of AI solution plan, what am I, what is what do I not have the capacity for today or don't have the ability to hire, or what am I trying to accomplish? Then being very thoughtful about the implementation of the tool. It's not like the old infomercials with the ovens, set it and forget it. It's be thoughtful about constructing that virtual team member and then don't forget to check are you actually getting the results that you want. I know I've listened to some of your other episodes and there's even large corporations that are getting in trouble by just launching stuff that's not filtered, checked for accuracy, checked for plagiarism, et cetera. But like not only checking the content before it goes up, but then also checking the results. So that's great. You're posting 17 times a day on Instagram or whatever. Is it moving the needle in the strategic direction that you wanted? Or maybe you need to spend some time and be a little bit more thoughtful about where you're spending the resource and that's when the last step comes act. So take some action, adjust or whatever, change the plan and iterate. But in a lot of areas of business, not just AI deployments we see our clients like really struggle with that check and adjust portion of, because I can't check unless I had a goal that I wanted to accomplish in the first place.

Jonathan Green:

Yeah, I fear that there's this idea that more is the answer to everything and more comments, more posts, more videos, more social media stuff. And I see this sometimes when I talk to someone, they go, what do you want? More leads? And I go, okay, let me say I. Let's say I get you a thousand leads and no one buys anything. Are you happy? And we have this, sometimes we gamify ourselves, like we don't say what our real goal is. And this biggest problem on social media is that we'll chase the wrong metric, which is like followers or engagement and it's one of the things I've discovered is I had a post go very viral last year and it was the lowest ROI of any post I've ever done. So had 400,000 views on LinkedIn, which in LinkedIn is insane and I got 12 followers from it and I was like, this is horrible. It's like basically it's a rounding error, and I realized that for something to go viral, it has to appeal to the masses, which means it doesn't appeal to your ideal customer. The more, the broader it is, the less likely your actual customer will like it, which means it's actually negative impact on your business. And that's one of the problems with chasing the wrong metric. And I always say like when people say, what's the most important metric to you? I'm like, dollars for sure. Money. I can't pay you in engage unless I can pay you in likes. Yeah. So you want, that's the same metric you want and it's, that's important. One of the dangers or things I see with AI is that people start talk so much about efficiency. The problem is it's immeasurable. It's usually self-reported I feel more efficient or I feel less efficient, or I got more done. It's not very easy to objectively measure unless you do something like data entry that's very measurable. Most people's tasks throughout the day are not that measurable, so it's like you couldn't tell like a 3% increase in efficiency. You would not be able to measure that very well because they just went to the bathroom one time less today, and that threw up all the numbers. It's that crazy. And. That's one of the problems is I see sometimes AI consultants like if you make everyone this much more efficient, you save this much money. I'm like, yeah, if you don't pay them for the two hours of efficiency, like you still have to pay their salary. The number doesn't change unless you fire someone or don't pay them for the two hours less a week they're working. And that's the problem there is that we, I think what happens is we get a new tool and we think it's gonna make our lives better and it doesn't at first. It's hard. Learning a new process is hard and there's that dip and you start to, because everyone like is hyping ai, especially, you start to think it's me. I'm actually slower 'cause I'm trying to learn this and I'm not learning as fast as everyone else. And you start to enter this negative thought loop, which is that. This is, this works for everyone else, but it doesn't work for me. So there's something wrong with me and you. It makes it worse and you can get in this like really negative cycle, even as large as your business, right? Where everyone is starting to feel like this working for everyone else. Why are we the, why are we the one company that can't get AI working quickly or get that efficiency or everyone else, and. This is this temptation we have to compare our backstage to everyone else's front of stage. Like I have no idea what's happening to either side of your camera. But so I only see what's on stage, front of stage. The presentation pair same for me. I set up the lights, we assume that someone would tell us if they're having a bad day, like no one's gonna, no one on LinkedIn ever post the truth. Me and my wife had a fight this morning, it was my fault. You never see that on LinkedIn. Nobody would actually post it even though it's true. And probably most of us have had have said something like that You dumb in the last month to our wive. So it's not that crazy. But we don't do it. And that's because it's, there's a performative element in the same way that reality television's not real. No one does those things. People, when there's a camera there, they act different. Or the, this person's make it louder, right? There's like a producer behind the camera. So there's, we, for some reason we think that Instagram is real or and even if you like. There's these act guy actors who like are abs actors, right? They have to show their abs. Some of them have to plan the shirtless day, six months in advance, so they die at Target. That's a nightmare. And then the day of the thing, they only eat ice for three days. There's a, and we, but we don't see that, right? We just say, oh, his abs like that all the time. And he's six months of help for a three minute scene. And that's the backstage, right? That's the off camera part that we don't notice. We just see that one moment. Which is great 'cause he worked towards it like great for him. Congratulations. The scene work. But it's like a huge amount of effort that we discount. So then we try and do it for ourselves. We go, why isn't it working for me in one day? And it's I've never, I don't know about you. I've never eaten ice for three. Like I've never done that. That's so tough that you're so hungry, you're eating ice. It's so wild. And in the same way we see other people using these tools and I'm sure it's the same in manufacturing. Someone else gets. And I've had amazing guests who were like, have AI welding machines. And there's some really cool things there where a machine will start to tell you how it's breaking down. So some cool things AI can do is say, oh, here's what's but it's still, it doesn't. Mean, it's gonna be easy. I can't tell. I got into a raging fight with an AI today. Like I said, some really dark stuff and it was completely wrong and it would go, no, here's the new code. It would give me the exact same four lines of code. I go, you are insane. And it got really mad. I go, because if you keep giving the same ant, you keep going, oh, here's a different answer, then give me the same code. That's the definition of insanity. And like it got mad, it got really hot. And it's like the idea that. Things never go wrong. That's a misnomer. And that's why I try to tell those stories. It's no, I get into a rage with AI all the time when it makes a mistake and then won't admit it. That's important to know. So what happens to you? But I think that a lot of it can happen where you add on a new project, you start to overwhelm yourself. It doesn't increase efficiency because you forget that time to learn it. Then you start thinking, oh, it works for what else? It's not working for me. So there's a problem with me until like now it's piling on. Now you have a physical and an emotional problem. So I wanna pull back again to the core concept you talked about and it's the core concept of your book, which is like to less is more. And I think it's so important, like one of the ways I know a business is gonna fail is if I say, who's your customer? And they go, everyone. I'm like, oh. That's the worst customer base you can have.'cause everyone is different. And it's like the more dialed in it is, the more likely you are to succeed.'cause you know who you're talking to. How can people before ai, I always say before you grab an ai, write down a plan. Like know what you want from any tool or anything. How can someone pull back and go, okay, what is an efficient use of my time? Or what is the right thing to do? Because doing something just because you can often doesn't help your business.

Chad Bareither:

Yeah. You covered a lot there. I made some notes, a couple of points to hit back to. So such good stuff. So you start off talking about how people feel like, oh, I'm falling behind. I need to do this AI thing, right? So there is a barrier, but at the same time, it's cheap and easy to use ai, right? So we can just feel like, just deploy. But without thinking about that specifically, if we're talking about brand recognition, thought leadership, et cetera, of who's my audience I'm even talking to, so the concept of niching down and saying are you speaking to one specific person's problem or are you just saying people have problems? And people are like, yeah, they do post, right? Like you were talking about 400,000 likes and 12 followers. So speaking to the specific problem that you're able to solve. But that takes some introspection, right? So the hard work. It's not just deploying the AI tool, it's sitting back and saying what problem, what service, what product are we providing and who is our target market and what's our process for delivering it? So I work in the consulting space. I think there's this fear, or it's been talked about in some spaces like that AI's gonna replace consulting or coaches, nutritionist, whatever you wanna say. In some cases, yeah, some of that knowledge can be synthesized, but what's really gonna eliminate your business is not AI in itself. It's bad scoping and weak process. And so if you don't focus on your scoping and your focus and your process upfront and then say AI is a tool to accelerate that maybe I can tell a story to illustrate that when I was working with a public utility, so like natural gas and electric distribution. There was a push for data and digitalization and one of the things they were talking about is they would get from the field, so they're gonna come out, they're gonna install a gas line or a distribution line for electric. And when you get in the field, like there may be a tree in the way, there may be a mail, there may be something there that wasn't on the map, right? So you have to adjust it. So you make an infield change called a red line and they would get back field notes and red line changes and they're saying, oh, it's taking forever'cause it's paper based and it has to go back and we have to enter 'em. We're gonna get everyone in the field toughbooks and they can put it in. Great. We gave everyone in the field toughbooks with very little training. And you know what we got? We got really crappy data a lot faster. So it's still wrong. We automated it, but like now we have a whole new problem to solve, right? So we didn't take time to invest in understanding the problem and the process that we were going after before we put this this efficiency acceleration on top of that. So because there's a quote from Peter Drucker, right? There's nothing more wasteful than doing efficiently, which should not be done at all. So great. You're blasting out social media content and people see that you're posting, but it's noise, right? It's not tugging at the heartstring of your specific client or customer's problem. It's just noise. You have a presence, but you don't have a following. And I think that's one of the big problems that we have is that this focus on more and more, more, whether it's in your business or we're talking specifically ai, but like more of whats, to your point, I want more leads, but if they're not qualified and they're not buying anything great. I want more likes, more views, more impressions. But if that doesn't actually translate into whatever product or service you're selling. So I would pull everything back and say, you need to start up front with just saying okay, so what is the strategy of my business? Who do I serve? What do they value? And then architect your processes for delivering that. And then maybe automation and AI can help you become more efficient. There was one other thing you talked in there about no one posts on LinkedIn and Facebook, like the fight they had there with their wife or the other thing, another thing. Especially in my space, like coaches, advisors, consultants need to be careful of not creating this like Insta you version of yourself, right? This Instagram version where like you are this lone, stoic sage and you have all the answers and then they meet you and they're unimpressed. Wouldn't that be terrible? So you've synthesized all this knowledge together, you've pulled it together, but then like you can't actually cash the check that you're writing like that's. That's something you have to look out for as well. So at least in the deployment of, we use AI in any content generation within our company. It's trained on all of our own IP. It's trained on my book, it's trained upon our blog posts. It's trained upon our case studies. So I'm not gonna go out there and promise people results that we actually haven't delivered. I'm not gonna refer to solutions, methods, principles, and tools that we don't actually use. Because that's gonna just create, again it's efficiency, gen, efficiently generating a lot of stuff, but it may not actually turn into any sort of value.

Jonathan Green:

Yeah, I think you're so right. The danger is that it's so easy and that's the temptation. If it's, if it was really hard to generate trash content, people wouldn't do it, but you could push a button and make it. AI image that looks terrible, but it's okay. And then write a post that's generic but not crazy. And then it's easier and easier. And I think that's something that we forget about is that like most bad stuff is easy. Good stuff is hard in most cases, right? And that's what happens is that you start to look at something like social media is hard. It just is. It's hard to think of something to write. It's hard to write a post that goes viral and you could put a lot of work. And I put a it's happened to me with books, the book that I spent the most time writing, people like the least, and a book that I wrote in one day. People really love so. There's no correlation between your effort and people's response. And we can all see this.'cause you can talk about, there's certain movies that like bombed and they go, but they spent four years making it. Yeah, I still don't like it. We don't respect their effort. That it was harder and there are certain movies like Sorcerers, this movie from the seventies, which is a remake of a French movie. And it was like they shot it on location in South America and like they all got cholera, to make it real. Like they, it was like it's notorious as being the hardest movie ever filmed.'cause he did everything practical, including the diseases. Like I think half the film crew had to go back to America because they were dying like so hard. And it took four years. No one cares, like other than other filmmakers and people like me, because it's very interesting to me. And that's the thing we forget. And so then when we're making content, we go, if no one cares if I put an effort or not, I start to get lazier and it's tempting. And the thing that's dangerous is that if you are saying things, you dunno what you're saying. And if you're AI's answering your emails and AI's writing your post and AI's answering the comments, you're gonna miss. Like the warning signs, if something's good or bad. People will tell you on social media if they like or don't like things early and you miss that and then you're not seeing it in your emails. You can push back how long until you get warned you're about to do a bad idea or that you should do something. That's something that people want. So there's the reason it's valuable and it's like I've started to notice that more and more. It's this dead internet theory, which is AIs are posting and AIs are commenting and it's like my engagement's up. Yeah, but not with humans. You're doing great for the bots and it's a distracting metric and that's, it all pulls back to this what is my goal? Who is my customer? What problem do I solve? And will this tool or will this machine, or will this system or will this employee get me there faster? It's such a critical question and most businesses really especially like smaller business or businesses get excited by tools, this can be really devastating. It's I bought this, now I have to justify it. So this is where you start doubling down on a bad idea and it's I bought this tool, I signed a one year license, so I have, we have to use it even if it makes things worse.'cause I have to justify the purchase and you can start entering this dangerous cycle. There's this pressure to decide very quickly with ai'cause you'll get left behind. And I've certainly said things like this before, but it's like any technology cycle. It's you don't have a car phone, you don't have a pager, you don't have a fax machine. All these older technologies that half our listeners probably don't know what they are anymore. And it's like there was the same pressure, like, how can you be a business if you don't have this? There are huge businesses that do nine, 10 figures. They don't have a website. Not every business has a website, and there was this need maybe 25 years ago, 2000 to 2000. Every business, like you have to have a website and they say why? How will the website help your business in particular? And you start to get this like keeping up with the Jones is like everyone else has a website, so I need one. So now it's like everyone else has ai, so I need it. That's, I think this thing that pulls us in, it's there's this old story of a farmer who the consultant comes and is I could do all of this stuff and then it'll take you 10 years to pay it off, but if anything goes wrong, you lose your farm. And it's everything's already working. I don't think I need that. But it's a temptation to have the cool new thing, the cool new machine that could work out and could be high risk. And it's like the thing I always watch out for with my clients, I always say, I don't want to have to do a dramatic change to human behavior. Because if I have to dramatically change how you guys behave, in order for this system to work, I have to teach you to do a new tool. I have to teach you to do behavior, then that increases the odds of failure because it's try changing a habit, right? Try changing someone else habit is really hard and I've seen some of these tools like even these AI note takers, there are some that you have to push a button at the start of the meeting and like never use those. Because you'll forget. You'll forget to push the button the one time you need those notes, right? It's such a small thing. If you can't remember, and we all can't. I know.'cause I've forgotten to hit the button so I'm not judging anyone else. That's all it takes to have a problem. So if you can't remember that, all these other behavioral changes where it's switch the tool you use, switch the questions you ask, switch your process. These are dramatic changes that. Can take an employee like six months to really ingrain a new way of doing things. And like I grew up in Tennessee, so a lot of my friends were in manufacturing. My friend used to put in the back seats to Saturns. And if you change the order in which you assembled the car, it would be such a big deal if you said, oh we do, now the backseat's third instead of fifth. Huge issue, right? You have to move things around. Very dramatic. And we think it's a small change, but it's actually a really big change because he had, he could do his job with his eyes closed because he'd memorize the behaviors.'cause he would bolt in the backseat the same way every time he put in like thousands and thousands of vaccines. So that's a lot of unprogramming to do when you wanna change a behavior like, that's the critical part. So it's be very sure that there's a real benefit here and that you're willing to pay the price.'cause with ai, it's not a price in money very much. It's usually a price in, effort and time and efficiency things. Things like where you have to go through that dip before you get the result and it still happens For me, every time I'm learning a new tool, there's a process, like I didn't use any AI tool besides chat GPT for two years. I was like, I'm still getting good at this. When I was trying to learn another tool. It's like trying to learn, try to unicycle and trying to learn to juggle at the same time. They're both really hard. I can't do either. I can't do either of those things, but I would probably rather learn one and then the other as opposed to learning them at the same time.

Chad Bareither:

Yeah, what you're full of great analogies today. I love the juggling and unicycle, learn 'em separately. The interesting thing about like the, you said AI note taking and things like that, and parallel to that is what I, what we run into with clients is like data generation, right? So we have data and then we have a data lake, and then we have these all these servers of data and it's so we generate AI notes and data and everything. Like on the back end. You're like who's doing anything with all this? Information that we're generating, right? Oh, we'll just have AI analyzed. It's okay, but we're back on that topic of like more for the sake of more. It's more because we can, we're gonna AI transcribe every meeting. It's like, all right, is anyone ever gonna look at that? What are, why are we doing that? Rather than because the tool exists I, I think is really important. The changing behavior one is like stuck in the back of my head because honestly our company, that's what we work on a lot. It's like changing behavior, right? Changing our behavior as it relates to manufacturing. So the Saturn analogy is a good one. If you need to change a process, like recognizing for that individual that's putting in the backseat, if we're gonna change the bolt pattern, if we're gonna change the sequence, like that's gonna be a big change. So they need to understand why we're changing it and have a little bit of input onto, does this work for me, the operator versus at a top level in your business, and depending on how big the business is, just saying, we're gonna do this, and now I'm wrestling through that change curve myself. Then you get back to the more for the sake of more. I oftentimes look at companies and ask them things like what are we looking at in terms of strategy? I was recently working with a company only about 160 members total. And like, how many strategic initiatives do you have going on? And they're like, 12. And I'm like, alright. So as a leader, can you manage something substantial, changing your business every month? No. Okay. Then maybe we should be focusing on changing fewer things right now. If you don't have on the backend to review, reflect kinda that check and adjust we talked about earlier, like why are we changing all this stuff if we don't have the leadership capacity to manage the change as well? Again, I think we default to the fact that like AI is cheap, AI is easy, and we can get back into the cycle of more for the sake of more generating junk that's just gonna generate junk leads, junk impressions, junk clients, things of that nature. And so really thinking about the behavioral change of the organization I think is important as well. Like it's easy to deploy. Again, we're talking about relative. It's relative, relatively easy to deploy an AI solution. The hard part as a leader is making sure, like the team's on board and we're getting the results that we expected out of it. Now if we hold ourselves accountable to thinking a little bit more about that, maybe the AI solution for every facet of business doesn't make sense because we don't really understand why we'd be using it and we don't have the capacity, the change metabolism to follow up with that and reinforce it. Like it's a great point you make there. The other thing I had written down that I don't want to talk about is we talk about putting out junk content. You said like it's easy to put out junk content and if junk content leads to junk clients, I dunno, whatever that means, right? Not the clients that you're hoping to focus on, then I really question what are we, what are you trying to create in your business? So again, this is the hard, the kind of thinking part, the introspection that you can't outsource to AI is like, why do you have a business in the first place and what are you trying to create? Great examples of saying there are businesses that are thriving and doing six, seven figures of revenue because they're passionate in what about what they're doing. And they've niched down and they're exclusively on referral business, but that's what they want. So if you're like growth more, because I think I'm supposed to grow because everyone else seems to be growing on LinkedIn. Like we can get caught in that trap of like, why not pause and pull back and say, what are you actually trying, like your business, what are you actually trying to create? Because if you just try to scale and scale and be, everything to everyone, you eventually turn into a commodity and if that's what you want, that's a different story. But I know that's not what I want for my business.

Jonathan Green:

I think that we get so caught up in the excitement of any movement or anything that we skip over a lot of the steps and we're seeing a lot of emotional decisions. I love that you brought up like that it's very easy for you to change your process at the top if you're not the one who's doing it. But yeah, like I was just thinking about how we, when you're doing a physical task like over and over again, you get very fast at it. If you have to change the pattern, you're gonna slow down quite a bit, right? So maybe now instead of 50 backseats a day, you're doing 35, and eventually in six months you'll be back up to 50. But there is that slow downtime. It's just sometimes people come out with a new pattern for a keyboard. Like they move all the letters around, think about how long it would take you to relearn. And there's the promise of efficiency.'cause there are versions where they put the most common letters near each other and then they did all these studies. It doesn't make a difference. It doesn't make you any faster. It. And it's this huge learning curve that people put a lot of effort to find out, like when they invented Esperanto, right? All this like the universal language anyone could learn. No one learns it, but it's this idea that it would solve a problem. And yeah, we, what I see is that sometimes you decide to initiate a change and you forget. If you don't have a measurable, like a measurement of success. This is a very common mistake I see with people when they have their first hire. The very first person you hire to grow your company, you haven't written down your processes, you don't have any SOPs, you don't have any measurements of success, so they don't know what to do and they don't know if they're doing bad. And that's if you don't know. And then of course you go they haven't hit the goal that I wanted. It's but did you tell them that was the goal? And so they're fired and they're surprised as they should be. Very common with a first hire is that you don't have a metric of success and a metric of failure. And I see that happening where you implemented a new tool and you go how do we know? How does the person using it know they've hit your goal of the increase of efficiency, the increase of results? It's very important to have a concrete number because as a worker whenever I'm working on a project for a client, I need to know what success looks like for them. Otherwise, it's so hard to hit. Like sometimes someone will be like, I'll know it when I see it. I'm like, then it's gonna be a very long project. That's gonna be years. Because that means I have to keep guessing and I'm not good at guessing what you're thinking. No one is right. It's this very challenging place to be in. So I think that it's such a good lesson today to really sit back and like before you use the ai, before you use a tool, before you buy a new machine, before you hire someone to sit down and go, is this gonna bring us closer to our company's goal? And. I think that we, as I said at the beginning, because we don't write business plans as much anymore, we don't have our goal written down, right? We don't have it really measurable, and I always see the people who like write down, I wanna make this much money per month, like on a giant wall next in their room. I've seen a few people do that. They always hit it. It really works like. In a, it's very big and whatever, but it works because they know how much money they need to make every month. They know what metric they need and they go, I wanna make this much money, so I need this many clients. I need to do this many calls. And they start to trickle down to, okay, then I have to send out this many emails. So it's this we start to, like we said, more and more grab these tools, but it's why and the why is such an important question that we're just missing. And I think that I've, and I've seen it at very big companies where they do this massive investment and then it's why? Like I, and I've even seen small companies spend a money amount of money in AI that like my eyes water, and I go, why did you spend that much? And they're like to do this, I'm like, oh my gosh. You spent like hundreds of thousands of dollars more than you needed to. It's that much money and it's like mind boggling. And that's the thing is that we are not making a logical decision. We have to pull back and be logical for a second before we deploy something.

Chad Bareither:

Yeah, it's, I think it's possible that AI is not necessarily changing that for companies, what it is it's amplifying it because it's so fast and easy versus we could have done the same thing in the past, but you would've had to hire a bunch of people, make a department, et cetera, et cetera. And so if I can skip all of that and just deploy a tool for, one 10th of the cost, one 100th of the cost, maybe I'm not doing a lot of that front end work. We think we started at the beginning saying, how do we put some more lean thinking around AI deployments? If you go all the way back to, so Lean is based upon most of the principles based upon the Toyota production system, and so Toyota is an auto manufacturer. But besides the production system, which is like how we do strategy deployment and continuous improvement, the Toyota way was continuous improvement and a little Venn diagram most also respect for people. So now. I'm wrestling with this in my mind, hearing your last thought about oh, man, because AI can take the human out of the loop. Have we taken the human out of the loop here in the AI in terms of the change curve of what do I want my team to accomplish? What do I wanna accomplish? And we're just deploying this bot and assume it's gonna do whatever we hope to. Versus that other side of the continuous improvement means we need to have a strategy to deploy. We need to have a process documented to understand how to improve it, and we need some sort of daily management system. You mentioned like metrics on the wall, like what are we trying to hit or else we're like blindly throwing these AI darts everywhere and not being very respectful to our people. We're keeping them busy generating the AI that's generating a bunch of stuff and this more is now just amplified, I think, more than a new problem. Does that make sense?

Jonathan Green:

Yeah, absolutely. I think that it's exactly what you're saying, which is that it just makes it faster, louder, bigger. So like cracks that were small now get really big or amplified. And AI is just an accelerant. If you have a bad process, you're just gonna do it faster. They have a good, processing it faster and that's, it's all come, comes back to that, which is you don't wanna accelerate something until you're sure it's a good idea. I think of the first person who like. Tied a rocket to the top of their car and drove in the desert, and then they just found them on the side of a mountain like a hundred miles away because it rockets are very fast and it's like faster seems like a good idea. But you, there's a reason like there's a top land speed record because a, and same for boats above a certain speed, the machine just dissolves. And there's a reason and that's, there's an idea that faster is always better. So I really love this. I think that like just pulling it back and it's what I want to dial into is like this core concept of lean, which is like, what are the things we need to do to get the result we want? And it's, if you don't know the result you want, then the formula doesn't work. Out the gate. And I see this so many times in so many different sectors with so many types of entrepreneurs and small businesses. I, when I was in doing a lot of authorship teaching, sometimes he would say, what I wanna write is I wanna write a children's book, then a book of erotic poetry, then a cookbook, and then like a mystery. And I'm like anyone who goes to your author page is gonna freak out if you what. You're starting four businesses. Each time you enter a new market as an author, if you're writing children's books and then you start trying another genre, it doesn't cross over. I even see as authors who go from science fiction to fantasy, it's not the same people. You lose like 80% of your audience. If the same customer won't buy all four of your products, then you have four different businesses, and it's that simple where you're driven by curiosity or passion, and it can be too disparate. Where you start to go in too many directions because you can. So I think it's been really great and be helpful for a lot of people. People who are very interested in the type of companies you help and the type of projects you work on, and maybe they just wanna read your book, which is very excellent. Where can they find the kind of things you're doing online chad, the best place to find your business. Maybe the best place to reach out to you.

Chad Bareither:

Yeah the best place to reach out to me directly 'cause we still do, despite this being an AI podcast, we still do in-person connections. I would be at our website, which is Bareither group.com. Social media platforms. We're most active on LinkedIn, but you can find us on LinkedIn or Instagram and that'll get us back to the same point. But if you wanna get in touch with me directly. Bareither group.com. There is on there. You mentioned the book, there's a free download of chapter one. If you wanna learn a little bit more about that and a contact page, you wanna set up a direct call with me, so that would be the best place to go.

Jonathan Green:

Perfect. We'll put it in the show notes as always, and blow all the videos. Thank you so much for being here today for another amazing episode of the Artificial Intelligence Podcast.

Chad Bareither:

Thank you.

Jonathan Green:

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