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AI is evolving faster than ever…

But what does that mean for you?

Will it replace your job?

Or will it make you 10x more valuable?

Some use AI to work smarter, automate tasks, and scale fast.

Others fall behind, watching their skills become useless.

In this episode, we’re breaking it all down.

How AI is changing work.

Who’s winning, who’s losing.

And most importantly - how you can stay ahead.

Let’s get into it.

📌 Timestamps:

0:00 - AI Is Coming After All of Your Jobs

1:20 - Will AI Create Higher-Value Jobs?

6:27 - The Real Question

7:15 - The New Problem

11:45 - Will AI Make Prices Go Down?

13:55 - The Transition, and How Welders Make So Much Money Now

16:24 - The Last 20 Years

25:46 - The Distrust in Information

31:13 - A Scary Thought

38:58 - The Impact of AI on Businesses

58:35 - How to Actually Use AI in Your Work

1:04:00 - The Luddite Analogy

1:10:49 - The Real Question

1:14:48 - How to Future-Proof Your Career

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Welcome to the Make Work Not Suck podcast.

I've been talking with people about AI for a long time, and and here's how I I framed it up to an an audience a couple years ago. I said, based on the trends that we have seen in technology development, technology tends to get twice as good every eighteen months. So imagine a day when you walk into, work, whatever that means for you. Right? Maybe it's you you walk into your bedroom and pop open your laptop and your job has been replaced because there is now a robot, an AI computer, something rather that will do your job as well as you can, but it doesn't need vacation days.

It doesn't take days off. It doesn't have sick days. It doesn't have a wife and kids that it needs to take care of, and it doesn't ask for, performance in, raises bonuses because it's getting a % cheaper every year and a half.

So, basically, you're asking, is AI coming after my job?

I think AI is coming after all of us. The question is how can AI make work not suck? Because I think it's very easy to believe that AI is going to make work suck for everyone.

Or is I AI gonna create better, higher value jobs? Oh, interesting. Let's discuss. Alright. So let's see.

The vision of AI in work, business versus employee perspectives. Which one do you wanna take?

I'll take the business perspective. You take the employee perspective. K. I've worked with a lot of Chick fil A operators. They cannot wait for the robot army to be here.

They tend to hire a lot of teens and early twenties. Those would be considered, you know, gen z's, maybe some gen alphas. And this this one guy that I've worked with for several years, he was like, being a Chick fil A operator is great. You know? People love the food.

I'm respected in the community and, you know, make good money. And he's and I was like, okay. So then what's the problem? He's like, being a Chick fil A operator sucks. All I do is deal with teenager drama all day long.

And he's like, man, if I could just have a robot, I would gladly pay significantly more because I know they're gonna show up. I'm not gonna have to deal with the nonsense. I'm not gonna have to deal with the the BS that comes with just dealing with people. And, look, this is a hard job. I just need somebody to bread chicken.

It isn't sexy, but somebody's gotta do it. And the moment I could hire a, robot to do it and replace that 18 year old in the back, I will do it.

So that's interesting. We started out with AI, and you went to robot, but the robot's probably gonna be powered by AI because they've gotta make some level decisions. I mean, there's I guess, you could probably have an arm that, you know, just, like, drop chicken in, drop chicken here, but you probably still need a human or another robot to do another component, another robot, another robot, and then your technology bill gets I

mean, maybe today you will, but pretty soon, I I don't think you're gonna need that many robots. Like, I'm pretty sure you can just buy one robot that makes chicken sandwiches, and it can bread the chicken and fry the chicken and prepare the sandwich. Well, I mean before robots.

There's there's a series of restaurants around me that actually have a rep a robot that delivers the food. Yeah. I know. I know. Somebody still foods it, but they put it on little robot, and the robot walks it over to the to the table.

There's a couple of burger joints that, burger concept. I don't know how it survived, but it was called flippy and it was like a burger flipping robot. So they put the robot in the back to cook the food, but you could actually watch it cook the food, because there weren't people back there. Whole side note, you don't have to worry about workers' comp. You don't have to work like it's, it's far more sanitary to have a robot in the kitchen than a bunch of teenage boys.

Let's be honest. So so there's more than just the economics here of an argument for outsourcing, at least some of those kinds of jobs to you the our AI robot overlords.

Yeah. Well, then you got the other side of that is, it's more sanitary until it springs an oil leak and then, you

know Okay.

Sprays oil everywhere. Mhmm. Or, you know, a a a thunderstorm rolls through and Yeah. Lightning zaps it, and then there your your hundred thousand dollar employee that is perfect is no better than a teenager that doesn't show up. Right.

Maybe maybe worse because he weighs three thousand pounds and you can't move him.

But but I think but I think those are the anomalies. Right? So from the business standpoint, you could probably bake that in the equation and just go, I can I can have a spare robot or I can do it? But but let's let's talk AI. I mean Okay.

With with AI today, people are able to outsource, you know, task and particular, you know, just like low level things like calendar organization or meeting scheduling or, you know, content creation. There's there's just so many little micro tasks that you can do that you would normally pay somebody. Yeah. Maybe maybe on the low end, you pay somebody, you know, $15.20 dollars an hour to do it, or it'd be a full time job that's, you know, $60.70, dollars 80,000 a year. But right now, if you can use AI, you know, somewhat efficiently, you can almost replace an entire person just by making the current people more efficient.

And the real question is how much more of the workforce is gonna get slimmed down because it's not there there's the old antique of everybody working harder. But if you give people tools that allow them to work faster, more efficient, or you're just literally offloading work

Right.

Then you need less people. Yeah. So so the real question is is, like, where do you sit on that continuum? Because if you're a person that gets cut from it, you're looking at this as AI is coming after my job. If you're the person that knows how to utilize the AI and you are now as powerful as, you know, three to five humans at once, you're probably loving this.

Yeah. But that I think that's that's a really big important distinction. I I might call them the haves and the have nots. Right? The people who know how to use AI will radically, improve their value in the market.

The people who don't know how to use AI will end up getting a job where the robots tell them what to do. And and I think that divide is here and it is accelerating at us.

Well, in what's there's at the end of the day, the more robots that get into the marketplace or the more AI well, it's let's sorry. This way. You've seen NVIDIA shares. Right? Mhmm.

Skyrocketing because they're the processor to have for AI right now. Right. Somebody still gotta make those chips. Somebody still gotta service the servers. There's, you know, still infrastructure that has to to be maintained to support that.

And so I think there's a level of, does it really does it shrink the job pool, or does it just reshuffle the job pool? Because

Good question.

Even if you get into the AI robot well, let's let's let's talk about AI in a more practical sense at a restaurant. Okay. Right now, there are call center call systems right now that you can actually talk to an AI agent that can do a level of tasking without the human.

Right. You

know, check my schedule, check my bank balance, check this, check that, give me this input. You could theoretically probably roll that out, and it wouldn't surprise me if somebody's either already done this, doing it, or about to do it. You could roll that out in the drive through for order taking.

Sure.

You don't have to have the you know, I mean, there's there's so many factors on it between the, you know, the attitude that you might get from an employee to, you know, the the there's a one person working the register and the front counter and this, that, and the other, and you're creating a line versus that

Right.

That AI agent at the speaker box having that more natural conversation taking your order, that just streamlines it. But somebody's gotta maintain that when that breaks, somebody's gotta fix it. Somebody's gotta maintain that when you change the menu. I mean, there's there's things around it. So you may have taken the order taker from the fast food restaurant out of the mix, but you still have a problem to be solved.

Now, what you might have to do is, let's say, you take a hundred, I guess, I'd be a cashier slash window worker for a restaurant. You may take a hundred of them out, but did you create maybe 20 tech jobs product?

No. I think it I think it's a hundred to one. Okay.

Well, I mean I mean, there's some there is a a a scale. I don't know what the scale is.

Yeah. But, like, if I was having to solve that, I would say, look, I don't wanna build the AI. Apple's already built it with Siri. So funny. My phone starts lighting up when I say it.

Right? Like Daniel's iPhone I would just use the AI that's already built there and tie it to my menu. And that way, people can just walk up and order

Right. But somebody still has to that's that's the downfall of AI at the moment. Sure. Is AI still has to be very micromanaged. AI is very good at programming a particular task.

And the second it's outside of that, it either flounders or it gives you bad results. And so the problem is is you still need someone to orchestrate all of this, you know.

Yeah. But I need one guy to upload that menu and keep it working, and I can replace every cashier in 2,000 restaurants.

Oh, well, I mean, let's take it a step further. You could build an AI worker that takes the menu and does the formation and does it over. My my point is is you still need somebody to maintain the infrastructure to make sure that AI system is working. Yeah. Okay.

Make sure the servers are online. Make sure that And

you need

a systems.

You need a disaster recovery solution in case something when something goes wrong, it doesn't kill your entire business. So, so yes, but I think a vast majority of these non complex order taking kind of simple follow instructions jobs. I think they're gone in the next ten years.

Well, exactly. Well, I I think those particular jobs are gone. The question is what where does the work the labor force shift to? Because every time we have a generational step forward, the workforce just evolves. Now we have another problem is to a degree, the workforce evolves so much that we ran out of, you know, guys to do skilled labor.

I say, you know, people to do skilled labor. We didn't have enough welders and craftsmen and plumbers. So there's a level of technology forced a whole bunch of tech jobs and then we ran out of the jobs that still have to be done. Right. So I I think there's still a level of those jobs would be around.

But here's another question. Okay. So you implement the AI. You've got your robot that hands out the food, robot that makes the food. You've got the AI, you know, assistant taking the the orders.

And maybe you have a, you know, restaurant that was normally staffed with 15 or 20 people that's now staffed with maybe two. Mhmm. There's there's two things I wanna get on that one, but I'm gonna go one way is, okay, that should be a cost savings. Will that actually drive price down because you don't have the labor cost, or people gonna maintain the current cost even though their margins should be better? But that's a little bit of a gotcha chest 22 because you don't know the technology cost for it.

Are you gonna have to have a $2,000,000 capital expenditure to put in a series of robots that at the end of the day are going to be more efficient, but it's gonna take five years to pay that off versus I can just hire people to do the work today and not have a $2,000,000 capital expenditure? So there's that component of it. Then there's the other component of, okay, let's say we got the cost down that's more cost effective. It's equivalent to two years of operating with employees. That's reasonable.

You know, the systems are, you know, designed to run for five years. We have to replace it. Okay. That's still good. And then it comes down to, will businesses utilize that cost savings to bring prices down to drive more volume, or will they keep prices high?

And then the other component of that would be what happens for those one or two employees that are in the facility. What are they expected to do? Are they still expected to run a restaurant, or are they expected to to be machine engineers to make sure they can fix a machine when it breaks.

Yeah. Because it could be a potentially very different type of person. Right? It's it's it's not the, the lead cook in the back who's now your, IT hardware support guy.

Yeah. You you might have a hundred thousand dollar engineer working at your restaurant, and now you need one of those at every restaurant to maintain this high-tech system. Right. So I I think I think that's where it kind of evolves is, there's there's a level of of adding the technology is gonna reduce the actual skilled people like this like, the the reduction in welders and craftsmen and and plumbers, electricians Right. By reducing that labor force.

It's that it's I mean, like, how much a welder right now can have a you make a much better living as a welder than you can doing many things right now.

Yeah. Certainly early in your career.

Right. Right. Right. So I I I think it's still too early to really tell where where things are gonna shape. But I think at the end of the day, we're gonna see the job market morph.

You will see more of it in there, and I think the jobs are gonna shift into your you're just operating the tool.

Yeah. I think there's some data here. If I remember correctly, the World Economic Forum says that AI is projected to create about $39,000,000 jobs, but destroy about 85,000,000 jobs. Right? So so your net down about fifteen, sixteen million jobs, over the next couple of years.

I think it's interesting how many businesses are investing in automation. I think a McKinsey study says I'm like 85% of organization investing in automation, but automation isn't necessarily just robots. Right? It can also be that's not just hardware. It can also be software.

There's a lot of software things that are now being automated, that are replacing

jobs. Oh, I mean, I'll give you a perfect example. There's a a company I'm invested in that, it's more of an ecomm business. Mhmm. And right now, there's a large call volume, and it's it's it's high volume, low margin.

Mhmm. And there's people that have to take these phone calls to answer very simple questions. Yeah. We're investing heavily in AI right now, so we don't have to have this call center force. We should be able to reduce the call center force by 80% and only have enough call center to take the really hard stuff that can't be answered with AI.

I mean, I think every business is looking for something like that right now. So it's not surprising that, you know, 85% of businesses are employing automation.

Mhmm.

And and I do think there's there's a level of technology. If you look back over the past, you know, let's say I mean, it was definitely prevalent in the nineties and the early two thousands, but we'll we'll just go last twenty years. Mhmm. There was a big rush in building software systems, but a lot of those systems were built to basically house and display data. They weren't built for to to to tell the employee what to do or to do the work that was needed.

It was just to present all the information so a human can make a logical choice. Right. So so I think a lot of companies now are taking that they're taking it to the next level and embedding that piece into it. And I think those are the jobs that are most at risk. The data analyst, the data Yep.

The data an data processors, data analyst, people, their job is literally to look at a system, make a decision, and put an action into it. That can that entirely can be replaced with AI today. Yeah. And I think that's what people are doing today.

Yeah. Which is interesting because there's also I mean, you could use that description to describe lawyers, financial advisors. I mean, there's a there's a lot of jobs that it's like, read all this information, take it in, make a decision. I mean, to some extent doctors are that lawyers are that like that. Those are, those are not just minimum wage jobs.

Those are really high skill, high dollar jobs. Do those go away? What do you think?

No. I I think I mean, let let's let's talk attorneys for a second. Okay. Somebody's still gonna have to duke it out in court. Somebody's still gonna have to understand.

And and let's be honest. Every courtroom, it's it's the greatest showman. Right? Right. It's who can be the better showman on the information.

But I think where it's gonna go, where it's gonna streamline it and hopefully drop my legal bill. Well, not that I not that I have a lot of legal stuff going on, but in the sense of just in general, is paralegals. You know, the people that do the data collection and pulling all the facts for the case. I mean, I think if you could drop a bunch of documents into a repository and the AI can categorize it and collect it and put it together and summarize it for the attorney, in theory, they should be more efficient. They shouldn't have to sift through, you know, phone records and record logs and emails.

Like, somebody's gotta read all that stuff right now and come to conclusions and hand it to the attorney for a case versus if it can be fed into, an AI system, you're you're really removing the support infrastructure for the attorney, but somebody still gotta interpret the law and and defend the law and present the case and this, that, and the other. I think it can be another added tool of you could you're probably gonna see, like, predictive models of, like, okay. Here's the case. Here's what we have. Here's the the suit.

You know, what's my probability of winning? Mhmm.

Yeah.

So I

think that's that's probably gonna be a layer. Where are you seeing AI right now? Because it's really hot. Everybody's talking about it. But there's this, you know, there's this great quote, and it's been attributed to lots of different people that says the future's already here.

It's just unevenly distributed. What are you what are you seeing as kind of the cutting edge right now in AI? Who's doing this well and what are they doing?

You know, I struggle I struggle a little bit with that. I mean, I think the leading in AI right now is just open AI opening up the interface since they put out chat, it has just opened the door for so many things. So I think right now what's the core to AI that's doing it well is I think the AI systems that are being generated. I think everybody's still trying to figure out how to interface with it. And what I'm what I'm what I'm seeing and what I would like to see are two different things.

What I'm seeing is a lot of people taking an existing process and streamlining it with AI. Okay. I'm not seeing anything, and I'm not saying it's not out there. I'm not seeing anything that is really leaping and bounding what OpenAI did. Now there are some caveats that, like, I forget the name of it.

There's a couple assistants out there, and I know a OpenAI has, one. But we're like, they can recreate an entire, scene in a movie. You know, they can give it the parameters. It can make a car chase and blow up in this, that, and the other, which is really cool.

Mhmm.

That's a very narrow use case. Right. Where I'm seeing a lot of usage for it is really in the marketing world where you need quick content, you need, scripts, you need, you know, blog posts and stuff like that because it really is helping create that content at a faster pace. Yeah. But at the end of day, what I'm also seeing is I'm seeing the quality of content kinda come down because it's kinda as as the AI has let much less emotion into it I mean, it has a degree of emotion, but you're you're starting to see kinda generic hosting start.

So original content is is starting to fall by the wayside, which is ironic because then if you put the time and energy, the human goes back to baking original content. It soars right now. Yeah. Yeah. So it's it's interesting the cycles we go in, but I I've yet to see anybody use it really, really well.

And let me let me get one difference between AI and machine learning models or Mhmm. Ling well, there's large language models, but, model data. I think there's a lot of, like, big enterprises that's using models to use model data to do more predictive. It's not really AI. Right.

It's just they're just using kind of an AI buzzword to do, you know, model data. I see a big I see a lot of that going on. But as far as, like, true generative AI, I think we're still on the still on the very, very tip of of unlocking it.

It's funny. I'm working with a client right now that does a lot in the big data, data science, data engineering space. You know, they've identified this opportunity that everyone's talking about AI. Right? We should go in with an AI offering.

And I'm like, great. What does that mean? And they're like, well, that's the problem is everybody wants to do something with AI, but nobody really knows what that means. And worse than that, when you really press on them and say, okay. Let's let's imagine a world where we have built the exact thing that you want.

Right? And it's done. We've rolled it out, and you go ask it this you know, you go ask the magic box a question, like, you know, how should I price this product? And it gives you an answer that doesn't make sense to you. Do you do it?

And they're like, oh, of course not. We would have to sanity check it. It's like, okay. So you've spent a lot of money for a black box to give you an answer that it can't explain to you, and you're not gonna listen to it. So why are we doing this?

And they're like, okay. Maybe we shouldn't. Well, so that that's a good question. Because it's like, if I could explain it to you, you would have gotten it, and you wouldn't need me. The fact that I have to explain it to you might indicate I'm right, but you can't understand it.

And so are you gonna, are you gonna follow it blindly or are you just gonna ignore it and keep doing what you've been doing? Because you could you could sink hundreds of millions of dollars into building models that will tell you things, and you're not gonna know if it's right until you do it.

So you you hit a very solid point there. One, AI is just the new buzzword like cloud. Remember back in the day, it was like, everybody's gotta be on the cloud. Oh, are you on the cloud? You got the cloud?

You got the cloud. Cloud. Cloud. Cloud. What's our cloud strategy?

Right.

It's like, the cloud is just a buzzword for the Internet. Anyways, again, AI is just a a buzzword for, you know, language or a a model data model processing. Again, we are branching into the very, very early stages of actual AI, and I think, you know, in the in the mad science labs of these of, you know, some of these companies, I'm sure they're on the cusp of much further ahead. But what we have today, and like you just said, the biggest problem we have with AI right now is we have the potential to do so much, but we distrust it.

Mhmm.

That then we build all these systems and tools around it to verify it. Just to to your point, what's the point of doing this? We don't trust the black box. It's almost the same thing with self driving cars. You know, there's still a large percentage of the population.

I'll never drive I'll never be in one of those. I distrust it. It can't. Statistically, self driving cars have crashed a order of magnitude less than humans. You know why?

They don't drink. Just take They don't drink. The fact that they don't drink and drive is already a huge stat boost, but we distrust it. Right. So I I think that's where because we distrust it, we've taken AI and we shrunk it down to what is the minute task we can use it for because we believe it.

Like, rewrite this

before me. I can understand it.

Understand it. And it

and I'm comfortable outsourcing it. Right? Like, I'm I'm comfortable with the AI scheduling a meeting for me. I'm not comfortable with the AI deciding my, you know, the the mix of my investment portfolio.

Well, exactly. Well and I mean, let's just use I think there's there's a little bit of, societal programming that's happened here. Mhmm. I mean, not not political and by any means, but how many people believe every single news outlet that they listen to?

Oh, yeah.

It's all over the place. Right? Like, you know, there's big establishment. I'm for the local guy. I'll only read, you know, x or I'm Fox News.

I'm only CNN. I don't just trust one or the other. I think there's so we built so much distrust in information Mhmm. That that's compounding into AI as well. We just distrust it.

Yeah. So would you say we're kind of in the hype phase of AI or we actually starting to see it some real adoption?

I think we're starting to see again, using AI as the buzzword. I think we're starting to see low lower level task automation. Mhmm. I think we're starting to see because those are the tangible things. We can give it a small task.

Let let let's proofread my email. Right. You know, I I mean, I'm dyslexic. I use I use ChatGPT every single day to send hundreds of emails. Mhmm.

It used to take me an hour to write a well thought email for some of these things I have. Now I can just go to ChatGPT, bang, bang, bang, bang, bang, bang, bang. You know, it knows my writing style. It knows what I'm trying to convey. I just give it the crap.

It it's got spelling errors. It's got typos. I'm dyslexic, blah blah blah blah. And in, you know, a fraction of a second, I get a better crafted email. And now I'll still go in there and tweak it.

I've gotten some of those emails that you spent an hour writing, and I'm very thankful for a for, chat g p t. It's it's much better on the receiving end.

Right. And even after me spending an hour trying to proofread it and ask my wife to read it or you to read it or somebody else, it's still not perfect. But I think I think that's where we're starting to see traction is it's a tool. We we really have gone from, you know, the the let's put ourselves as a roof for a second. I would hope there was never a roofer that used a rock to drive in a nail, maybe back in the stone ages.

But, well, I guess maybe the original hammer might have been a stone on a stick.

Sure.

But then you evolved into, you know, the actual hammer, what we have today. And then now you've got the, you know, electric or pneumatics, you know, nail gun. Right. I think OpenAI or AI in general as we know it today is the pneumatic nail nail. Nail gun.

It's just a better, faster tool that can do what was, you know, a normal hammer. Right. Anybody could drive a nail in, but you might put some dings around the wood you're doing. And if you're an experienced craftsman, you can probably get the nail in in one hit perfectly, but most of us aren't. Mhmm.

Whereas with a nail gun, you just gotta line it up and hit the button. Right. You could still screw it up. Don't get me wrong. And so I think that's really where we're at is we've got a great tool that'll allow us to be more efficient.

And think about it, if you got a roofing team and they all are using hammers, they probably aren't gonna get two or three roofs done in a day versus you have a roofing team that's using, you know, pneumatic nailers, you're probably gonna get three times the work through.

Yeah. I

think that's where we are with the

employ less people or do more work in the same amount. Right. But it's interesting. I like this analogy because it's like, I don't see the the the pneumatic nail gun isn't gonna go up, knock on the door, and say, excuse me, sir. We had a really bad storm that came through your neighborhood.

Most of your neighbors got their roofs messed up. I'd love to go up on top of your roof, take a look and give you a quote. Like AI is not there. AI is not ready to do that part yet.

Well, and here's what I would say it is, but it's not worth it yet. It is, but it's it's a it's a game of numbers. AI, you could probably go in there and say, you know, find all the areas that were impacted by the storm, you know, source this database to give me all the contacts. You could you could make that human more effective. You could tell that human, you need to go knock on these, you know, hundred houses because statistically, they were the hardest hit versus guessing where you think it went.

But you could also use it to send text messages and and emails to those people. But there's the folly of it because everybody gets so much spam chunk in emails that it's it's a game of numbers. Right?

To an email trying to or a text message trying to sell me a new roof.

So the most the most effective sale is actually person knocking on the door. So then how do you balance the two? Yeah. You use the you use the systems to find the houses that are the most impacted, you know, basically your ICP. You can tell your your sales rep, you know, get exactly here's where you need to go to make them more efficient.

And then you can use it. You know, they upload pictures or whatnot of the damage and, you know, maybe use a drone to get a, you know, the the top view. Mhmm. And then they could feed that back into a system that can then better communicate with the the homeowner more effectively than the human can. So at the end of the day, it goes back to the the pneumatic nailer, the

the the

nail gun. Every step that process got more efficient, but I didn't remove the human. I made the human more efficient.

So you said something earlier when I asked about what are you seeing in AI. You said there's a difference between what I'm seeing and what I want to see. So I'd love to go back to that and say, you know, what what's the vision that you would love to see for AI?

Oh, I would love to see.

It pertains to corporate and and making work not suck.

I would and and this is a scary thought. I want AI to prompt me back. Oh. I want AI to prompt me. So I'll give you example.

I write code. And I was working on a project the other day, and I'm going through it. And I'm prompting the AI to, you know, like, hey. Write this function for me. Do this function.

And it was it it it really did help me out. But my problem is is it one it's weird. It forgets. I was going through this this the the code, and I'm like, wait a minute. You know, three steps ago, we added this function.

You just removed that from the equation. Why? Oh, yep. I'm sorry. I forgot to add that.

Let me add it back in. Like, now I feel like I'm dealing with a with a this is probably horrible. I feel like I'm dealing with an outsource resource from The Philippines where you kinda have to give them, like, train them on every little single step step by step process. And if, like, you go out No disrespect intended to our Filipino listeners. Nope.

Nope. Not none whatsoever. Just you you've got a it there's there's some classification of employees that you have to spell every you know, if the process isn't perfect, anything out of bounds, it falls apart. Mhmm. That's what I was experiencing with with the AI.

And and what I would love it is to say, like, are you trying to do this? Or or maybe it would be, hey, I see you've got this. Would you like to try this instead?

But hold on. That was Clippy back in the nineties, and we hated it. Like, do you like, man, I said more dirty words about Clippy that I care to admit. So Let's be honest. Why do you say you want that?

Clippy was just, like, do you wanna add the like, Clippy was, like, I mean, yeah. No. We're not even going there. Alright. What contextualization, taking it in context and improving upon what I'm trying to do.

Right. Because the one thing that drives me insane when I'm using AI today is it's almost like it's constantly trying to teach me. Like, no. No. I don't need you to teach me.

I don't need you to explain it. And I can go in there and change it. I can change the prompt, like, stop trying to explain it to me. I just need you to produce the code. Right.

And it's one of those it because it doesn't have context, it's just literally, like, swinging all over the place. And I and the other like, this this thing I was doing the other day, I spent maybe a total of sixteen hours, you know, of course, of a couple of days working on this one particular segment in application. And I used AI to it my AI was my programming buddy. At the end of the day, it probably saved me maybe two to four hours overdoing it myself Okay. Because of the prompting back and forth Yep.

Because it was just swinging all over the place or it would just forget an entire block of code. It just, like, it just was all over the place. And again, that could be user error. That could be me. I mean, someone can tell me how to use it better.

But it did save me two to four hours and the code quality was a little better. There were some things about it I was like, oh, that's better. That's more pedantically correct in how you should write the software. Okay. I'm gonna incorporate that into my functions.

And then I did use OpenAI, and I dropped in the code. And I said refactor using this, and it did it, which was nice. But it doesn't have that contextualization to the level of going, but do you want this, or I think you mean this, or, hey, here's a library. Like, I want it to be suggestive in a forward progression. Not it like, right now, it's it's like a glorified teacher or, like, it wants to explain everything to me or it wants to give me all this context about why it did what it did as opposed to understanding what I'm trying to do and trying to drive the program forward.

It's it's solving the surface level problem as opposed to getting to the root problem.

So it's interesting that you would say that because one of the things I've spent a lot of time thinking about recently is the difference between analysis and synthesis. Right? I studied engineering in undergrad, and we spent years figuring out how to analyze problems. You take something, you break it down into pieces, you bake those pieces into pieces, you break those pieces into pieces, you solve all the pieces, you put them back together again, you've got an answer. Right?

And and that is really what the whole world has been working on for, I don't know, maybe the last fifty to a hundred years. Right? What is interesting is is that they teach people how to do that in lots of different schools. The thing they don't teach, at least that I have not seen, is how do you take the thing and go up, right, and put it into higher and higher levels of context to give it extra meaning. And there's a lot of us that are really good, you know, particularly technical people, engineers, very good at analysis, but we don't have a framework for synthesis.

We don't have a framework for where does this thing belong in the universe of potential contexts and how do I help it find its place so that it has meaning. And I think that's a really interesting problem that I don't think AI I mean, maybe somebody's working on that, but that I think that's the next level of AI for what you're talking about.

Oh, yeah. I mean, if you remember, think think of software in the, you know, early two thousands. There was there was so much it was nice to actually have it in a software stack as opposed to on paper. Huge leaps and bounds. But.

Oh, yeah. Many of these softwares, there was like a hundred buttons you had to choose from to choose the next step. Mhmm. And, like, every button was a little micro thing, and we just kept on at the at the end of the day, we just kept band aiding more stuff and these especially some of these, you know, mainframe systems or, you know, big point of sale systems, etcetera. And and you had to have so much knowledge on all the components and where to click.

Mhmm. That's where we are with AI right now. And people are looking at problems, today's problems. They're solving today's problems with this technology, but all we're doing is we're just going surface deep because I mean, for one, that's the limitations of the technology at the moment. But we're we're just looking at how to to solve it with with that.

And I feel like we're back into, like, an an early February software package where, like, with these AI agents people are talking about. Mhmm. In some cases, we mapped one out the other day. We're gonna need, like, 38 agents to basically do what one human can do. Once we get it all designed and developed and this, that, and the other, it'll be great, we think.

But but you have to, like, know

a lot of you better need a lot of scale for that to make economic sense.

Well, that's and that's the other part of it. Like, what's this actually gonna cost? Because now you got these agents. Those take cost. You gotta feed it.

What happens if it routes, you know, does a human have to come in and fix it after the fact? Is it gonna actually work? And so that's that's that's where I think and this but that's bleeding edge. Mhmm. We're still in the early phases of this technology as a whole.

And, again, if we get that deployed, we will reduce some call center staff, and we'll make our existing call center staff more effective, or we can grow without having to add more head count, which is great. We can even afford to pay our call center staff more

Mhmm.

And and take on higher caliber calls as opposed to the the lower caliber calls. So there's a lot of options there, but we still gotta prove out the technology. It's at the end of the day, we still need a human to do the hard work.

Yeah. So you talked a little bit about the vision that you had for AI of really understanding the context, predicting what you need, why you need it, and kind of prompting you in the direction it knows you where you want to go. I like that. I think we're a ways from it, but I I I love where you're trying to go with that. I want to take maybe a little bit of different if you were leading an organization, let's say it's a large organization.

You've got a lot of people, you've got a lot of processes. I don't really care what industry it's in, but, but you're the senior leader and you've and you know, that AI is coming. I would love to kind of walk through the vision journey culture results with you on that. Right? Like what would be your vision for AI and its impact on your business?

What's the journey that you would take both technically, but also with the people and the processes culture wise? Like, what impact do you think this is gonna have on your culture? And then also, you know, finishing with results, what impact do you think results would have? And if we've got to pick an industry or type of company to make it more specific, that's fine. But I'd just love to have you walk me through your thinking on that.

I I think there's two ways you can take it. And there one the way I'll walk it down, and then I think there's the other way which is more, you know, squeeze profit more money, you know. We'll say the greed route.

I I Yeah. But we don't wanna recommend that because that Right. Right. So

right. Right. Right. So I'm gonna I'm gonna set that aside, and I'm gonna go with for me, if I if I'm running whatever, you know, company a here and I'm looking at this, I think the vision is how can we achieve our mission more effectively? How can we you know, there's there's a level there's a level of of balance.

Right? A a company needs profit in order to grow, to scale, invest, provide raises. You know, if there's no no margin, no mission, no money, no mission. Right? Right.

So for so from a vision standpoint, okay, if we wanna meet reach more people more effectively, more faster, then there's, you know, just in general, you know, okay, we need more income so we can hire more people. So are we going to or there's two ways to do it. You can either cut cost, which doesn't always work to get the margin where you need it to invest Right. Or you increase pricing, or you can try to increase sales. But if you increase your sales volumes at your current pricing, you're end up having to invest, you know, more hires and stuff.

And so it can be done, but it's not as effective as either raising prices or cutting expense. So then if I'm if I'm going through the vision of this is how do we reach more potential customers? How do we serve our mission better, faster, more efficient? And then from a journey standpoint,

I would go Hold hold hold on. Tell me. An an interesting question that comes to my mind I would wanna ask my clients is, what would what will AI enable tomorrow, or how will AI enable you to achieve your mission and vision tomorrow in ways that you couldn't have yesterday?

That's a phenomenal question.

And and and chew on that for a while, like, you've got a mission statement, but there's there's some sort of a vision, something that you're trying to accomplish as an organization. What does AI enable you to do in the direction of that vision that you couldn't do yesterday?

A %. So for my my standpoint, I'm I'm literally that's a better way of saying what I'm trying to allude to. Okay.

Yeah. That's I was trying to think through the question because it it's gonna be different for every industry, every type of company, every size company, but I I think there are legitimate things that are becoming open or becoming possible that were not possible five years ago.

A a %. And remember, at the end of the day, if we look at what we can do right now, AI is just another tool. It's no different than if you're gonna go from, you know, QuickBooks to NetSuite or you're gonna implement HubSpot. Like, it Right. It's just another tool.

The problem with it is I mean, and I hate to say this, the amount of systems and tools I've implemented in companies that ended up with either workforce reduction

or Mhmm.

The workforce staying flat or not flat, but no new hires and being able to double the workload. Like, the thing is is is that happens every single day.

Mhmm.

And I think the problem with AI is because it's starting to encroach on the jobs people do as opposed to when you bring big systems in, it's just a reduction. It's just a, okay, we have a system as opposed to per as opposed to a person manually inputting this data. Right. You know, we have a Salesforce that puts data into a system as opposed to a person that types in all the data manually.

Right.

So at the end of the day, it's the same thing. But on on the on the under the hood, on the surface though, you're encroaching on people's actual, you know, the components of everybody's job, I guess you could say.

So

instead of attacking one or two jobs, you're attacking all the jobs. So in the sense of going back to to this, it's a tool. From the journey perspective, I would go down to, okay, how can we and again, I'm going on the on the other side of this. How can we, for the benefit of our better serve our customers Mhmm. How can we provide better, benefits, maybe raises for our people, better work life balance Mhmm.

Using this technology? So what can we automate from the what can we take off your plate that will help you do your job better, faster, more efficient so that the company can benefit so that we can do those things like again, you can't if you don't have profit, you can't provide raises. Mhmm. So then it's it's part of the journey of this is how do we better live the mission, and how do we make our people how do we make the the the work the the people side of the equation or I'm gonna start with the people side of the equation. How do we make that better so that we can also make our customer side better?

And at the end of the day, we should be able to get the same level of or we should get it, an expense decrease, which will maintain our profit margins without charging our customers more, or we we may be able to we may be able to decrease our fees and maintain a higher caliber. If we can decrease our fees, maybe we can serve a wider audience. Mhmm. I mean, in some cases, maybe we need to increase our fees because we're adding this exponential value. So I think there's it's not about increasing revenue or decreasing revenue and bringing the balance.

At the end of the day, the vision is how do we get how do we serve our mission better, faster, more efficient? Next step, how do we how do we serve our people better, faster, more efficient to serve our customers better, faster, more efficient? And AI is the current tool we're looking at to do that.

Yeah. It strikes me that if you're the senior leader of the company, you're not gonna have all those answers. I think you need at least your leadership team spending a decent amount of mental bandwidth saying, what does AI enable me to do tomorrow that I can't do today, couldn't do yesterday? And and what does that look like for sales? What does that look like for operations?

What does that look like for HR, IT, finance? Like, there's just whatever your specific, set of responsibilities are. You need to put that AI hat on and think down into your organization and begin to almost dream of what, what capabilities either already exist or will exist here shortly. And how does that enable me to serve our mission given that I'm responsible for finance, right? Or marketing, whatever your your functional responsibilities are.

That's that's gotta be a team effort. One person's not gonna know all that.

Agree. And and let's take it to the culture component. I think one thing that everybody's gotta keep in mind, people don't fear change. They fear loss associated with change. That's why we get resisted.

We resist change until we understand it. It goes back to what you're talking about with the AI company you work with, and it's the black box. I don't trust the data, so, therefore, I'm gonna do it my old way. Mhmm. I think if you're bringing AI into the business and it starts with what I just said, if you're going in there to squeeze profits and you're going in there to cut head count and you're doing it for all of the the results reasons, you're gonna drive fear in your organization and then people are gonna fear their jobs, etcetera.

Right? Whereas if you're approaching this and you gotta be legit, not just say what I'm about to say, but actually believe what I'm about to say. If you're approaching the culture with we want to we want to make this better for us, we wanna utilize tools to make our work life balance, better serve our customers, etcetera, then it comes down to what can what what can come off your plate or what can be automated or how can we use technology to achieve this. And if you can rally the culture around the value of what it means, then you'll actually get great feedback from every employee in the organization about how they can automate their job because they understand the reason why. Goes back to, you know, starts with why.

Right? Yep. So if you're coming in and you're like, we're gonna use AI and we're gonna do things and you build this fear, my job's gonna be automated and I I may not have a job and, you're gonna get more people resisting, and they're gonna say, well, AI can't do my job. Nope. Nope.

Nope. And they're gonna and they're gonna push. Yeah. But acknowledge the fact it's just another system. It's just another tool, and you can do great things with it within the business to make your current people and customers better and the help the business more healthier.

You'll lower that barrier of of fear. Right? Because people aren't afraid to change, afraid of fear or, loss associated with it. You're removing the the potential loss, and now it's how do we do that? Because the other thing is I've gone into companies and say, look, guys, we have to we we can't hire any more people.

There's five of us in this team, and we have to double our workload. So the answer is not where everybody work harder and work till midnight every night. Yep. So what tools can we do? So we could still do a you know, I I I'm a big fan of, you know, everybody's paid forty hours, you know, salary, blah blah blah.

How can we actually only work thirty hours? So if we can find a way to to do the work of 10 people with five and do it in only thirty hours, I'm willing to bet any business would give those people a bump in pay because the profit margin they just you know, going to yesterday's podcast. Right? Be touched that that number, that revenue, that, yep, that profit. Uh-huh.

So if I can give you a 30¢ pay or 30¢. 30 percent pay increase, not a 30¢, 30 percent pay increase and get your job to thirty hours a week, would you not help me implement AI?

Sure. Yeah. But it's there there is a fear there. Right? There is an anxiety.

But it's it's interesting because as you start framing AI as a tool, it reminds me of a situation that happened to me several years ago. Do you remember my, my assistant, Julia? You worked with her a little bit.

Yep. Yep.

A couple years ago, I had a a great assistant. Her name was Julia, and we were on I was onboarding her. She just started working with me, and I showed her my to do list. And my to do list was, in a sticky note on my laptop. And I know you're a big fan of sticky notes, so cover your ears.

And she looks at me and she's like, why are you doing that? And I was like, well, this is just kind of how I keep track of all my stuff. And she's like, why don't you use Trello or Asana or like, and she has listed all these tools. And I'm like, guess I never thought of it. And she's like, here, can I show you something?

And she pulls up one of them. She's like, why don't you just keep your to do list here? That way I can see your to do list. I can do some of the things on your to do list. I can put my to do list there and then you know what I'm working on.

I'm like, I'm not gonna fire her for that. That's brilliant. Like, it's like, it's a better tool than the sticky note I had on my laptop, but she found a way to make herself 20% more valuable to me by augmenting herself with a tool. And I think that's a, a good analogy for us to think about AI. It's like, how can AI help make you 20% better at your job?

And go talk to your boss about that. Don't be scared of that. Go find it, bring it to him and say, Hey, I bet you, if I use this or this or this, I could do forty hours worth of work in thirty hours. And then there's an opportunity for you to go learn something else, do something else, take a promotion, like, walk your dog. I don't I don't know what it is, but there's there's so many opportunities there.

But if you're scared of the consequences, you're gonna run from it, and I think you actually need to run towards it and embrace it.

Well, you're you're basically talking the Jim Collins good to great part of the flywheel effect. You know, he talks I'm probably gonna butcher this a little bit, but he talks about, you know, find you you can have a job that has 10 people in it, and you pay 10 people the wage of 10 people. He says, or you can find five people that can do the work of 10 people efficiently, and you pay them, like, eight. But what does that mean? It means the work of 10 is getting done.

You're two x ing the throughput. Right? Those individuals are getting paid like there's eight people on the team, so they're getting a higher wage.

Yeah. They're getting a 30% of Right.

What they were getting paid. And because they're high capable, high caliber, and leveraging tools, they can do the work of 10 people at a pace that is equal to five.

And as the business owner, you're saving money because you're only paying for eight, but you're getting 10. Right. And they're happy because they're getting paid a 30, hundred and 40 percent of what they were getting paid because they're producing twice as much.

So if if I I well, I as of this is this is the way I look at it as a business owner, and I would encourage other business owners to look at it this way. If you can apply the Jim Collins good to great formula there and AI be the means to get that, why wouldn't you? Where this is gonna fall apart is when greed kicks in and people are trying to use AI to squeeze more profits or squeeze more out or like, you have to balance the equation. You can't bring in AI to squeeze the employees more and not provide the benefit on the other side. You can't bring AI in expecting it to be a perfect replacement and fire half your team and expect perfect AI.

Like, it it's it's a give and take. Yeah. You know, just just like when a lot of companies brought in, you know, big, enterprise systems, like, when we all or not even in the SMB space when email was a thing and everybody needed email server and computers in the office and, you know, you had to hire an IT guy or a fractional IT guy to come in and fix it. Like, that was a cost that got added by leveraging the technology.

Mhmm. So I think we're as as many, secretaries or people running memos back and forth across the city, messenger bike style. Yep. But you're right. You did for every 10 of those, you had to hire a IT help desk guy.

So I think businesses that think they're just gonna fire this this is the crux of the red line. Right? I'm gonna fire my team. I'm gonna deploy this AI software. It's just gonna be perfect.

Great. I news flash. You're setting yourself up for failure. If you can look at it realistically and actually try to make every aspect of the business good, the employees, the customers, and the bottom line, then you'll find a path to success to use AI because at the end day, it's just another tool to be leveraged.

I really like the way you start with vision there of, like, how does AI enable us to do our mission better? Go from the vision to the the journey. What's the process? How do we all get 20% better? Then to the culture.

Right? Because my big concern is I I'm worried that some percentage of people will embrace AI, and they will get better paying jobs because they're able to do the work of two people in the time of less than one. Right? And those people are gonna have more and more opportunities. And the people who fight this, the people who run, the people who dig their heels in and try to resist are going to not only lose their job, but they're going to begin this downward spiral becoming less and less valuable because the next job's gonna expect you to be able to use that tool.

And now you can't get that job because you don't know how to use it. And I'm worried for those people, and and you're right. That's the culture side of this. If we're just going for results, we're gonna create a there's no vision, bad process, bad journey decisions, just gonna wreck the culture and you're gonna screw those people for the foreseeable future as opposed to vision centric AI strategy partnering on the journey with your people and say, hey. Let's all find a way to use AI to be 20% better a year from now than we are today.

It builds trust. It builds effectiveness. It builds their capability so that even if something terrible happens and they're not with you a year from now, they're still more valuable to their next employer.

Oh, %. And and you said something in there that, I didn't think about when I was talking through this earlier. It it falls into, like, using it for the wrong manner. I think there's a level of people are gonna use AI to create more task for the employee. You know, it's gonna mine the data, and it's gonna give them all the work they need to do.

And all you're gonna do is just pile on more work for the human to do because you just automated the to do list. Right. I I think that's a very surface level solution. And and though that may be a first step is is building a a to do list, I think you gotta go full journey on this stuff is not how do you stack a to do list for a human. It's how do you actually get the work done either without it.

Like, you have to elevate the human in this equation, not just try to ring more out of the human by having AI drive more on their plate. Yes. And that that's the the difference between the red and green line. Red line, you're just gonna squeeze your people more by having AI throw more at them as opposed to actually taking work off their plate, going full journey on this?

I think there's a there's an AI race to the bottom and an AI race to the top. And the race to the bottom is probably like that red line of how do I use AI to micromanage my people, to give them more work, to make them do more. And and I think there's gonna be people who do that, and it's gonna end poorly for them and for their employees. I think there is another option, which is how does AI elevate? How do I get rid of the crappy work that nobody wants to do that is in every job?

Right? Your best job, just as a side note, your best job is 80% what you want and 20% suck. Right? There's just every job has some part of it that sucks. How can we make that as small as possible?

So you spend the majority of your time doing the thing that's truly valuable. Doing the thing that's you love to do, that you actually get excited to get out of bed for. Like, I want that to go from ten hours a week to thirty hours a week. And I gotta get all these other things off of your plate. That's where the AI gets focused.

That's what we're trying to do. I wanna get rid of the low value add repetitive work to free you up to do more of the high value add, which would be creative work, which would be, relationship building. So, you know, high touch, service, sales, creativity, product, like, you know, engineering, like building things, not building version 10,000 of the same thing, but, like, building new things. I think that's where humans are really gonna be able to always be differentiated from AI and and robots is our ability to create and form connections. And so that's where the value is gonna go.

People who know how to use AI to automate the repetitive so they focus more on the creative, and the connection, I think those are gonna be the winners in the new economy.

Yeah. Well, I'll I'll throw one out there, and then I've got some stats I wanna throw out. There's, I've always said there's a difference between a programmer and a developer. A developer is one that creates, you know, the somebody's got an idea for an application. They gotta, you know, start the architecture and the the codes, you know, the the the framework they're gonna use, the technology, start actually writing the code to build the functional system.

Versus a programmer is someone that comes in and refactors codes, cleans up, bug fixes, etcetera, etcetera. OpenAI is not a developer. Now maybe there's an AI system out there that's getting closer to it, but Mhmm. Like, even me, I've taken some existing systems or some, some ideas, and I've tried to prompt OpenAI to get to get it there. And and me as the human had to put so much more intellect into it to get the AI to a destination, Whereas I've taken a a particular file, threw it in, gave it the parameters, and said refactor it.

Ten seconds. That's the thing is is we still need developers, whereas OpenAI can replace some of the programming, bug fixes, QA, stuff like that. Yeah. But here's here's going back to the culture impact. According to this, this Pew Research here, 50 per 52% of workers feel AI implementation is poorly communicated in their companies.

Why?

I'm surprised it's that low. Well, you know I I would have said, like, 90%.

Well, I think I think you got two forms. I think there's a lot of companies that that just don't know how to even use AI that they're they're probably the owners the small business, you know, they're going back to the pirate ships. I don't know. That may be, I won't use that analogy. I think there's a level of of maybe older, small business owners are not messing with it.

I'll figure it out when it becomes a thing when I have to. Mhmm. And then I think there's a level of of organizations that are leading with that trying to figure it out. I think a lot of startups are using it. I think legacy companies are not.

I think big big enterprise is probably kind of implementing it more behind the scenes. But I think the real reason why that's 52% is for those that are doing it is because they're not communicating why. And I'm gonna guess a vast majority of those is because they're trying to, get the business equation in line. They're trying to increase profits and reduce cost. Here's another interesting one.

IBM paused hiring 7,800 roles citing AI automation. That's from Reuters.

Go ahead. Didn't Meta recently lay off 11,000 people, a lot of them in development, because they're saying that more and more of that, you know, entry level and mid level development roles can be automated?

Maybe. But this is interesting. They paused hiring 7,800 people. Not they laid off 7,800 people. They paused hiring 7,800 roles because and I'm gonna I'm gonna assume in the in the study or the little bit I read in the article, it's because they're trying to figure out how to make the people more efficient so they don't have to hire the people.

The reason why people are so resistant to this is because it impacts literally every role in the business, anywhere from, you know, person taking phone calls to a call box at a at a fast food restaurant to sending emails to the guy door knocking, you know, on roofs Mhmm. To, you know, engineering, development, code writing, marketing. It touches everything. Right? Which is why which is why I think it's such a, gonna have such an impact.

So have you ever heard of the word Luddite?

Don't be a Luddite.

Give give me the definite as I've heard it, but I'm blanking on the definition.

Okay. So I think this is an interesting historical analogy for you. So the the Luddites were English workers who, you know, back in the, you know, 1800s, whatever, saw the cotton gin and other sorts of mechanical automations coming, worried that they were going to lose their jobs in the fields and in the mills. And so they started burning down these, the machines. And and it was their way of saying, you know, I'm scared of my I'm scared of losing my job.

I'm scared of losing my livelihood, and so I'm gonna go burn this thing down. I think there is a risk. I think there is a very strong risk. Right? A likely probability that some portion of our population is going to respond to AI like the Luddites.

Right? Burn it down. Fight it. Don't let it near my job because it's going to be, bad for my business. Right?

And the opportunity here is to rethink your business and to say, look. If if you are, if you work with, you know, wool garments like the Luddites did, right, And and you have a mission to make high quality clothes for people in your community. Well, guess what? That machine now gives you the ability to take your mission and reach more people.

Right? Is it gonna

look the same? No. It won't. But if you just get focused on the task and not the mission, you should be threatened. But if you zoom out and think about what this will enable you to do, I think it's actually a very exciting time to be working.

Oh, a a %. I mean, I think this this this is why I say, you know, it's history repeating itself again. Mhmm. A little over a hundred years ago, maybe maybe a little more ish. Yeah.

I'd say a little more than a hundred years ago. Think about farming crops. You had Mhmm. Teams of people that went out and picked the cotton, the corn, the, you know, pick pick the crop versus now you've got these big automated machines that I mean, there's, like, what? You know, a a small handful of humans in these machines can can clear hundreds of acres

Oh, yeah. You know, in

a in a very short amount of time. That's just the evolution of technology. The big the thing that brings AI to it is when farming was revolutionized, it it didn't impact the average worker other than I don't know if I'd have to go back and research this. Like, did grocery prices get better or was food faster at the table? Like, there was some impact to the consumer that was in the positive, but not every consumer was also a farmer.

Right. So this is bringing this is that revolution in every industry as technology's evolved. I mean, you go from the, you know, the car, airplane. I mean, just, you know, big things over over the years. So I I think if you go to if we switch from the culture side of it to the results side of it, I do think there is a level of short term either layoffs or restructures.

I think companies that are doing it to squeeze profits, they'll lay people off.

Mhmm.

I think smaller businesses will either like, the the IBM stat, they'll stop hiring and forced to figure it out. So I think there will be a little there's gonna be some, dissonance in the switch over. And so I think there will be some short term pains, but the long term on the other side of it, it should be a win for society as a overall.

My con my biggest concern in this is the entry level jobs. Right? When I came out of school, I got a job as a procurement analyst, sat in a cube, built in access databases. Right? That job is not going to exist much longer if it exists at all.

Right? But that's where I got my start. I spent a year doing that and then got, you know, more and more opportunities. My concern is that if all of those jobs disappear, where do you start your career? Like, what's step one?

I think I think that's exactly what I'm trying to say. It's just gonna be an evolution. As as the farming technology I just talked about evolved, they just went from one to another. Now there's there is a a a, you know, change over, change management process, and there is that that gap in between, But it'll just be a new normal. I I mean, I know this is very simplistic, but, like, when we learned how to drive a car, we didn't have a backup camera and all the sensors and beeps and all that stuff.

Right? Right. Versus kids today, they're taught with the backup camera and the sensors. It they didn't think I mean, you know, they kinda still teach it, but they don't need to look in the rearview mirror unless the camera doesn't work. Mhmm.

So there's just a new normal. I think what we're what we're talking about is there's going to be a new normal on the other side of this for that role that you're talking about. It's just if you're judging the new normal based off your experience, the gap is gonna be wide, and that's gonna be where the the the fallacy comes in. So the real question is is, like, what's the new normal for that role? If you're in this middle part right now, you're coming out college and you're trying to figure it out.

The best thing you can do is figure out how to adapt AI into what you're doing to understand it. Right? Like, learn as much as you can right now. We don't know what the new normal is. A billion jobs what what what was that?

That was by

Is that the twenty

twenty thirty five. It's 2025 right now. A billion jobs in the next ten years. We don't know what the new normal is gonna look like yet. Yeah.

It's one of those, it's coming. You can either be on the leading edge of it, you know, the inventive side of it, which is a very small percentage. You could be on the early adopter side of it, which means you're gonna feel the woes and the pains and and the the bleeding edge of it. You can be on the early adopter side of it. You can be on the the late majority, or you could be on the laggards.

The laggards. The luddites.

We're trying to burn it all down.

Right. Statistically, sixteen percent of the population is gonna fall into that category. Sixty four percent is gonna fall about in the middle, and then you've got the 16% on the front end of it. And the real question is is where do you wanna land? Because if if you're 65 years old right now and you're two, three years away from an exit, you probably should just double down on getting your business sold, get it for value, and get it sold versus if you're, you know, mid forties, early fifties, late thirties, take your pick, and you've got a business that you're gonna hang on for the next ten years.

Mark Cuban, who owns the Dallas Mavericks, He can be a little bit of a jerk sometimes, but he's not stupid. He says that pretty soon. And he said this years ago, pretty soon running a business without AI will be like running a business without electricity. And I think that struck me because he again, he's not stupid. He's predicted a lot of things and made a ton of money doing it, and he thinks that AI will be as foundational to a future business as electricity is to current businesses.

And if if you don't have a plan for what that means for your business, you need to get one very, very quickly.

So, this thought just popped in my head when you said that. There was a point in time where learning to type was useless. Then it became you know, when the typewriter came into the mix, then there are people with typing skills that would type, and there was a percentage. And then the computer came in, and you had to learn how to versus now typing is just a thing. Mhmm.

I think that's kind of I mean, it it's it's a different scale. But this, this McKinsey statement right here says 90% of future jobs will require some level of AI literacy. I think that's the equivalent of people learning to type. Mhmm. We're in that transition period where kind of some of us that were pre AI, or say some of us, most of us that were pre AI are learning to type AI, if that makes sense.

Yeah. And so I think the best thing, like, you're talking about is it is coming. Mhmm. You can be on the lagging scale, but it will catch up to you. Just like having a, you know, machinery when doing no maintenance on it.

If you run it in the ground, eventually, you're gonna have to replace it, and it's probably gonna be more expensive than if you just maintain the other one. You don't have to

get an oil change in your car, but you'll find your car. It it will force you to to make a much more painful decision.

Right. So I think that's where again, you can pick where you want to be on this continuum, but just know how it impacts your people, know how it impacts your business, know impacts your customers, your profit margins, etcetera. And I would say, if you are a business that's choosing to lag behind, you are at risk of losing some of your top employees that are on the progressive side because they're learning it. Everybody's learning their sales. Right?

A vast majority of people are trying to figure this out. And so if you lag behind, you may lose some good people, because you lag behind. And then maybe you may be okay with that. I'm just you gotta think through the pros and cons of this. It does have the potential to increase your, you know, bottom line, increase the value of your business, especially if your business is more future proofed by using AI.

If you incorporate now, you can increase the value of your business.

Right.

But you can't do it at the expense of your employees or your customers. You gotta keep the whole equation in balance. And I mean, I think at the end of the day, you know, nobody knows, you know, only only the almighty knows what the future holds. So all we can do is adapt with what we have in front of us today and keep moving forward.

Yep. Alright. How would you future proof your career in an AI world? I've we've hit a couple of these already. I think everyone needs to be learning something about AI, finding a way that AI could make your particular responsibilities easier, faster, or make you 20% better.

The macro trend here is is that anything repetitive, or anything that requires a lot of data is going to become automated. The value is going to be in creativity and connection. The ability to make something new, the ability to lead people, the ability to connect with customers, emotional intelligence. Like, that's where the value is gonna be in the long run. Right?

It's not tomorrow, but over the next ten years, creativity and connections where the value is, automate monotony repetition analysis, all that kind of stuff is gonna be the robots.

Yeah. I I think, like like you said, what can you do to future proof of your career? Learn AI tools, develop soft skills, stay adoptable.

Yep.

Adaptable. Adaptable. Not adoptable. Adaptable.

I'd say AI is not gonna replace most people, but people who use AI will replace those who don't. You can either tell the robots what to do. In the future, there will be two kinds of jobs. People who tell the robots to what to do and people who do what the robots tell them to do. Yep.

You've gotta decide what kind of job you wanna have.

Well, and I think that goes down to what can make work not suck. Mhmm. What can make your work not suck is by learning how this impacts you and how you can leverage it. What will make your work suck is if you push it, head the sand back away because it is here. It is coming.

Yeah. And it's it's it's like we're right now, we're in the the calm before the storm or the recession of the water before the wave comes. Mhmm. So if you wanna make work not suck, make AI work for you. You wanna make work suck, use AI to work against you.

I like it. I'd love to hear what other people think. I'd I know we've got people listening from, all around the country, maybe even all around the world. I'd love to hear what they're seeing with AI, where it's making work better, where it's making work worse. Please drop us a note.

Let us know what you think. Give us your opinion. And, next episode, we're going to be talking about how AI is impacting the job hunting, how recruiting and hiring is changing. Very timely because I'm in the process of trying to hire a couple of people right now. Look forward to hearing your thoughts on what AI is doing to that space.

Make work not suck. Our podcast that talks about exactly that, our process, vision, journey, culture, and results. We present real world business solutions that make the difference. Our goal is to make work not suck, hosted by Ryan Hodges, co host Daniel Steer. Join us each episode and make work not suck.