Josh Hadley once argued that ecommerce businesses shouldn’t waste time building software. Now he believes the best use of AI may be building a custom ERP and has reassigned a longtime employee to lead the effort. In this episode, he explains why he’s changing his mind, what Domino’s digital ordering reveals about competing with technology, and how his team is approaching a 12–18-month AI rollout. Get his five-step framework, problem, owner, prototype, proof and scale for choosing automations that improve profits or save meaningful time, rather than producing another shiny dashboard.

Bullet Points:

Timestamps:

00:00:00 Why Every Business Must Become AI-First
AI is changing competition; businesses must build software capabilities alongside their physical products.

00:01:06 Lessons from an AI Conference
Josh reflects on companies embracing AI and the risks of businesses delaying adoption.

00:02:11 Why Internal AI Talent Beats Outside Consultants
The strongest AI results come from developing curious, capable people already on the team.

00:03:27 From Physical Products to Technology-Enabled Business
Josh revisits his view on software tools and argues for building custom systems where they create value.

00:06:05 Domino’s as a Technology Company
Domino’s used digital ordering and better customer updates to reduce friction and improve sales.

00:08:29 How AI Can Speed Up Business Decisions
Connected systems can surface information faster, letting teams focus on judgment and action.

00:12:03 Find AI Champions on Your Existing Team
Give employees room to experiment, then identify the people producing valuable AI work.

00:17:35 Set Clear Goals for AI Projects
Leaders should define the problem and desired outcome instead of asking teams to build dashboards.

00:19:51 Measure AI by Business Results
Useful AI work must improve efficiency, reduce costs, increase sales, or otherwise deliver measurable value.

00:21:12 A Five-Step AI Implementation Framework
Identify a meaningful problem, assign an owner, prototype a solution, prove its value, then scale it.

00:22:27 Assign Business Owners and Build Narrow Prototypes
Pair process experts with technical builders and begin with small, reviewable workflows.

00:25:44 Prove the Improvement Before Scaling
Measure time saved, output accuracy, and whether teams act on the results before expanding a solution.

00:27:57 Create Ownership for Software Responsibilities
Businesses need people accountable for requirements, data quality, development, testing, and ongoing maintenance.

00:30:20 Roll Out AI Gradually and Stay Focused
Josh recommends incremental automation, disciplined prioritization, and focusing on the business’s main constraints.

00:31:34 The Weekly Automation Challenge
Choose one manual workflow to improve each week, building progress through small, consistent steps.

Links and Mentions:

Tools, websites, and platforms

“External AI consultants and AI engineers”: “00:02:11”
“Sellerboard“: “00:03:27”
“Upwork“: “00:12:03”
“Claude“: “00:12:59”
“ChatGPT“: “00:12:59”
“OpenClaw“: “00:12:59”
“PPC agents”: “00:24:37”
“Amazon API“: “00:29:05”
“LinkedIn“: “00:32:52”
“Slack“: “00:32:52”
“Facebook“: “00:32:52”
“WhatsApp“: “00:32:52”

Other named businesses and services

“Domino’s Pizza“: “00:06:05”
“Domino’s ordering channels”: “00:07:24”

Transcript:

Josh Hadley 00:00:00  You thought you were running a physical products business? Well guess what? Now you’re running a software business too. Whether you are ready for it or not. AI is changing how businesses compete, and if your team keeps doing everything the old way, your competitors are going to smoke you. It’s adapt or die. And today I am sharing why I believe every business needs to develop the capabilities of a software company and how to start with the team you already have. Welcome to the Ecomm Breakthrough Podcast, I’m Josh Hadley. I’ve scaled my own ecommerce brand from 0 to 8 figures, and I’m actively building towards nine figures in sales. This podcast is where I document that journey and share the systems, the strategies, and the lessons learned in real time so that you can learn what actually matters and scale your own business. My name is Josh Hadley. First and foremost, I’m a man of faith. I am a husband to a beautiful wife and a father of four children. I’ve been selling in the e-commerce space for over a decade, doing over $20 million in annual revenue in selling multi-millionaires on channels such as Amazon, TikTok, Shop and Shopify.

Josh Hadley 00:01:06  And I am also the host of the number one business strategy podcast for ecommerce entrepreneurs called Ecomm Breakthrough. I just returned home from a one day business conference that was centered 100% around AI, and it was pretty eye opening to see some of the really, really smart things that people were building. And then also kind of the naivete of some of the other business owners that haven’t even gotten started with AI and are almost like two apprehensive to or are unwilling to give their team access to these tools because they don’t want to expose their data or they don’t want AI recommending something that the business owner doesn’t actually want to have happen. And, to me, it was it was very eye opening. But number one here was one of the biggest takeaways that I want to share with you. And then I’m going to dive into exactly how we’re implementing AI into our business today and why I think this is the future, that you have to adapt and start leaning heavily into AI, or you’re going to get blown away within the coming years.

Josh Hadley 00:02:11  so one of the biggest things that they talked about that I think is a clear takeaway that we’ll start this episode with, is the fact that the best people using AI right now, and the best results that I’ve seen from businesses using AI, not one of them hired an external AI consultant or AI engineer or whatever. It is not one of them hired anybody externally. Rather, they coached and enabled one of their existing team members to nerd out on AI. And those are the businesses that are reaping massive dividends right now from all of the AI tools. And I’m going to dive into exactly how we’ve done that in our own business. How do you identify that the right person on your own team, and sometimes where it might make sense to maybe go external into the market and go find the right person for you. But look, I’ve been thinking about something that’s been changing how I look at our business. And to be honest with you, I have to kind of apologize to the listeners because six months ago I said, hey, you know, we are not in the business of being a software company.

Josh Hadley 00:03:27  So it is foolish to spend all of your time nerding out on all of these AI tools to go build your own dashboard when you could just use seller board or whatever dashboard you’re currently using and just pay five bucks a month or 20 bucks a month, whatever the cost of the software tool is. And that still is true. Like, please don’t spend your time, especially if you’re the CEO trying to replace $20 a month software tools like that’s not the purpose. I’m going to dive into how you should be setting this up to connect your own systems. If I were to be honest, I think the best way to use AI right now is to build your own custom ERP system. And that applies even to the smaller businesses that are doing maybe just a couple million dollars of revenue per year, all the way up to the nine figure businesses. Here’s the most exciting thing. I think NetSuite and big ERP systems, to be honest with you, should be a thing of the past. If you are actually looking at going to implement an ERP system and paying $100,000 plus per year to install something, I would much rather take that $100,000 to go build out my own ERP system, because I’m going to be able to light that thing on fire and get my business moving a heck of a lot faster than some off the shelf ERP system.

Josh Hadley 00:04:52  Because even if you go with like something like NetSuite, guess what? They still have to build customizations that fit the needs of your business. Okay. Duh. If that’s the case, I’m just going to go build it myself. And I’m certainly not paying the absurd cost that they are requiring today. So let’s settle on that. Look, I sell physical products, but increasingly I believe that I have two businesses to build. I have a physical products business, and then I have the technology that makes that business operates two different things. That second business needs attention, ownership and investment because the systems behind our products increasingly determine how effectively we can compete and most importantly, at the speed at which we can compete. The provocative way to say all of this is that every business right now is being forced to become a SaaS business. Now, SaaS technically means software as a service, and I’m not suggesting that everybody needs to go start selling software subscriptions. But what I am saying is you need to develop some of the capabilities that software companies have.

Josh Hadley 00:06:05  You don’t need a sales team to go sell them, but you need people who understand data. You need people who can connect systems. You need people who can build useful tools, test them and maintain them. And then you need leaders who can decide which problems are actually worth solving. Okay. Because look, AI creates an opportunity to change how work gets done. But somebody still has to turn that opportunity into a business result. So let me give you a concrete example that like makes so much more sense now in hindsight. And I remember when they went through all of these kind of like changes as a business. And I was like, that’s really interesting that they’re like going through all of these great lengths to become this more technology first business. Even though the business that they were in was a lot more basic. And this example is Domino’s Pizza. Okay. Because look, they sell pizza dough, cheese, tomato sauce. It is a physical product that somebody has to prepare and to deliver. By the end of 2015, more than half of Domino’s US sales were coming through digital channels.

Josh Hadley 00:07:24  They had introduced ordering through apps, text messages and even smart TVs. So a pizza company needed the ability to build software, connect ordering systems and make a digital experience work all the way through to a physical store. And that was the challenge they had. They still had to make good pizza, but making it easier to buy that pizza became the technological challenge. That’s the parallel I see for our business today. Domino’s went above and beyond so that when you order, you don’t just like guess when your pizza is going to be ready. It’s like, here’s the app and I’m going to send you a text and I’m going to tell you when the guy puts it in the oven, I’m going to tell you when the guy starts sprinkling the cheese on the pizza. I’m going to tell you when it’s coming out of the oven and when we’re cutting it. That is what they did. And it transformed their process and it actually increased their sales. They made it more readily available for consumers to more easily purchase.

Josh Hadley 00:08:29  They reduced friction. And that friction was I don’t even it’s unreliable. I don’t want to go sit at the pizzas like they told me 20 minutes. And then I show up and it’s like, oh, give me another ten minutes. Right. They flip that model on its head and they became more reliable. So I see that as the parallel for all of our businesses today. Domino’s had to lean into being a technological first company along with still being really, really good at creating delicious pizza. Whether you agree whether they create delicious pizza or not is a separate topic of conversation. But the point of the fact is they had to start running two businesses in parallel. And that’s what I want you to take away. Because, look, you might sell supplements, clothing, toys or home goods. Doesn’t matter. Your customer still wants a great product, but behind that product, there are hundreds of decisions and processes that influence all of your results. Somebody has to be making the decisions. How much inventory do we order? Which products should we actually pay attention to and double down on? What are our customers repeatedly complaining about? Which advertising concepts deserve more test more spend? Which creators should, you know, our team actually follow up with for affiliate marketing? How long does it take our team to gather enough information to answer all of those questions.

Josh Hadley 00:09:57  That is where all of this becomes practical, because I want you to imagine, like two brands selling similar products right now. The first brand someone downloads the reports, combine spreadsheets, checks the numbers and puts together an update. Then a manager reviews it and asks three more questions. And at this point, at least a couple of days have gone by. Honestly, if not a week. Because here’s the problem. So many of us say, hey, yeah, if you could just get this done by the end of the week, when in reality that’s like a 1 hour or 2 hour task. You just gave them an entire workweek, 40 hours to go complete that task. So yeah, it will come in on Friday, but it just is going to come in at Friday because they started it’s going to come in Friday at 5 p.m., but they started at 4 p.m. because they needed to get it off their to do list. So number one, even if you’re going to operate the old model, like tell people, hey, I need this report.

Josh Hadley 00:10:53  And by the way, how long is this going to take you? Oh, an hour or two hours. Doesn’t matter. Cool. Can you get that done tonight? Because it’s speed out, which you’re going to be able to outpace your competitors. Okay. By the time the team agrees on what happened in that former example, several days have passed. And here’s what’s happening in the second brand. They have connected systems that prepare all of the information flag exceptions, and a person checks the analysis, investigates the important issues, and makes a decision. At the end of the day, there is still a human involved, but the human is not the person pulling the reports flagging things. The human is executing judgment based off of what the AI is recommending. The second team still needs the judgment. They still need accountability, but more of their time goes towards acting on the information. Action. action, action! Not just execution. Let me go! Push buttons. Okay. Over time, I believe that difference can become a serious competitive advantage.

Josh Hadley 00:12:03  And if you keep operating manually while competitors figure out how to do that reliably with AI, they can put you in a very difficult position. But here is ultimately where I think a lot of entrepreneurs listening to this are going to get this wrong. They’re going to hear this and say, okay, I need to go hire an AI person, right? And hey, just go go find somebody on Upwork or something like that, and they’re going to write some vague job description. They’re going to find somebody who knows a bunch of random tools and expect that person to transform the company. But I want to share with you here’s what we’ve actually done in our business, that you should go replicate in your own business. So first off, as soon as you know, cloud code and all of these things began to become things that could actually operate on their own. And I think it all started with like open claw. Right. And you could have all of these, like, true agents working on your behalf.

Josh Hadley 00:12:59  Like, we’re still very fresh in all of this. Like we’re, yes, less than 12 months old. But here’s the point. I went out to my team, everybody on my team, and I said, hey, I want each of you to go experiment with AI. Here’s your Claude, here’s your chat account, and I want you to go take one of the processes that you do and go figure out how you want to automate, how it could be automated. And guess what I got back. I got back some things that were fairly basic or things that it was like that a really is not being automated and really didn’t even get us the result that we wanted. And then I saw some people that went to great lengths, put in a lot of time, but it was in kind of like the wrong it was not focused on something that’s going to drive a meaningful impact or save us a lot of time in reducing efficiency. It was it was super smart, but it’s not. It’s almost more burdensome now because now somebody has to do something that was more basic before.

Josh Hadley 00:14:05  So what I did find, though, and this was the most important part of this exercise, is everybody on the team now understood that we’re in AI first company, so that they understand that you should actively be searching for tools and processes to begin automating. So it doesn’t come as a surprise. But in addition to that, the other big takeaway is I found out of my team of 30 plus people, I found my team of 5 to 6 rock stars that would knock off the socks of a lot of other people that I’ve seen in the AI space, because they nerd it out on this AI stuff and produce some incredible stuff that I couldn’t even fathom producing myself. And guess what? I am not the AI guy. I am not the guy to go build dashboards. I am genuinely not even interested in it. Like I don’t get any excitement building or nerding out on all the AI stuff because as you know, like it takes time to connect things and then if things don’t go according to plan, so you have to massage that data, you have to go connect this and then inevitably it’s going to break.

Josh Hadley 00:15:19  Like it’s just not my area of expertise nor my zone of genius. And so with that being said, what I did find is five really hungry people on my team that really want to dive deep into this AI thing. And there was definitely one guy that has been kind of a shining star throughout all of this, and he has been a guy that’s connected all of our data systems, even going back five plus years. And he has taken to AI like fish to water, if you will. And guess what? I effectively took whatever job, whatever role he was in and I said, yeah, you’re no longer in that seat. I’ll go find somebody that can go fill that seat. You are now my my guy to go spearhead AI throughout the entire organization. And the good news is, this guy’s been with me for five plus years, and he has so much context about the business. And in fact, he’s moved around in multiple departments in the business that he has a very good idea of exactly what’s happening, where our bottlenecks are, what our challenges are, how where the data sit, why the data is so fragmented, and all of those things.

Josh Hadley 00:16:31  That is the beauty of being able to work with somebody on your team. And so that is the what I would recommend. Number one, you’ve got to very clearly articulate this to the rest of your team that we are going to be an AI first organization. It’s time to either adapt or die. And if somebody decides to exit the team, so be it that this is the future. But secondly, identify those individuals that are number one. Wow. Pretty technically savvy. But number two like are producing already meaningful results for you. And then you can double down with those team members. So that is what I’m actually doing. And then I’ll share with you kind of the framework that we are using to take it step by step every week there is something new being automated. And guess what? Over the course of 12 to 18 months we will build our own ERP system. We will have a heck of a lot more automated throughout the entire business, and I am excited about that. But I want I want to dispel the myth that I’m not talking next week.

Josh Hadley 00:17:35  I’m not talking next month. I’m not talking about a quarter from now. I’m talking about this is going to take us 12 to 18 months and we’re going to get better and better and better. But as soon as that thing hits in 12 to 18 months. We have a massive competitive moat around us, so here’s what I overall recommend. I would start with the people who already understand the business. Your inventory manager knows your exceptions for inventory better. Your customer service team knows which problems come up over and over again. Your marketing team knows where the creative process gets stuck. Those people have context that some new random hire from Upwork or something like that, that is an AI guru. Okay. They would need to learn over time. And honestly, it takes somebody at least six months, if not 12 months, to even get somewhat acclimated and onboarded to where they’re even providing value. Okay, that knowledge is extremely valuable. And before you assume you need to replace those team members or hire around them, your job is to help those people learn how to use AI to improve their work now.

Josh Hadley 00:18:50  That takes more than just buying everybody a ChatGPT or a cloud account and saying, go be more productive. As the CEO, you have to set the direction. You need to explain what problem matters, what outcome you want, and how the team will know whether the improvement worked. Because here’s what you do not want. I don’t want my team members just randomly creating dashboards for me. In fact, going back to the example that I shared with you earlier when I just tasked the team to come up with something using AI. Guess what? The people that just created dashboards, I was like, hey, that’s not what I’m looking for. I don’t need dashboards to just show me things. Dashboards are easy to create, and that’s honestly what I do here so often in the in the e-com space right now is everybody’s building their own shiny dashboard. Oh, I can see this now. Okay, cool. It might be better data visibility, but more often than not, you have this visibility, somewhere else.

Josh Hadley 00:19:51  Anyways. Like, you just spent lots of time creating something that you already had, but it looks cooler, and you’re proud of what you built. That’s a waste of time. What I want to know is whether the AI tool created something that is improving a workflow or process. Is it helping me save costs by making things more efficient, or is it helping me increase my ability to make profit? Otherwise, you can end up with a company full of people experimenting with tools while the actual business constraint stays exactly where it is. Ask me how I know because I’ve seen that AKA go listen to my last podcast episode where I talk about why focus and you as the CEO, is so important. And honestly, you as the CEO can be kind of the biggest bottleneck in your business because you have shiny object syndrome and then you send people down 1,000,001 different rabbit holes, and then everybody stays ridiculously busy doing lots of cool things and working on lots of things. And then ultimately, nothing moves. And that’s why our revenue over the Q3 did not live up to our forecast, because I kept people, kind of just scattered across too many things because I kept seeing so many fun things with AI that I just kept distracting them.

Josh Hadley 00:21:12  Because here’s what’s ultimately going to happen. Yes, you’re going to get more documents, you’re going to get more content, more dashboards, but still the same problems. And an AI rockstar, in my mind, is someone who uses all of these tools to produce a better underlying business result. That could mean reducing errors, saving meaningful time, improving a customer experience, helping the business make more money. At the end of the day, the outcome needs to be clear. Honestly, if what you’re working on in AI is not fundamentally reducing your expenses or increasing sales, then you are honestly wasting your time. So here is the framework that I’m using and that I would recommend you use. It is called problem owner prototype proof and then scale. So five kind of steps there. First identifying the problem. And this is the basic step that we make every single week. Choose one reoccurring problem connected to something that matters economically okay. Just use more. AI is not a business problem. We spend hours preparing inventory reports and we still identify potential stock outs.

Josh Hadley 00:22:27  Too late. That is a business problem that gives you something specific to improve. And I would start with a problem inside a process that you and your team already clearly understands. Because if nobody can explain how the process should work, then you probably have some work to do before you can even think about automating it or turning it over into AI. Step number two or second, this is the owner. Put one person in charge who understands the work and is accountable for the outcome. They don’t have to build every technological component themselves. They may need help. And in fact, that’s what we have. We have that guy, that nerd it out on data, and he’s super smart and he can connect all the systems. What he’s doing is he’s going to each department and there is a department head, and they understand the specific problems they’re flagging, the problems they’re identifying. This would be the solution to the problem. How can you help me automate this with AI? And then they have their own brainstorming session.

Josh Hadley 00:23:33  My guy goes out. He’s the builder, builds the AI, brings it back, and it’s like the 1080 ten principle, right, that Steve Jobs used. The department head identifies the 10%. Here’s the problem. Here’s what I believe the solution is. Cool. Go execute. 80% of the work gets done by this AI guy. Then it comes back. The remaining 10% is verifying whether that actually produced and the result that we wanted and solved the problem or not. Providing feedback. If feedback is necessary, we go make the necessary updates, changes, etc.. But here’s the key thing your department head, the owner of that problem. They should be able to explain what a useful result looks like. Identify a bad output and decide whether the solution fits the actual workflow. And if you’re improving inventory reporting, the person responsible for inventory needs to be the one that’s involved. You can’t hand the whole thing to some AI guru who knows the technology, and then assume the business requirements will just somehow become obvious.

Josh Hadley 00:24:37  Step number three is the prototype. You want to build the smallest version that can help. Maybe it prepares a weekly exception report. Maybe it organizing customer complaints or into themes with links back to the original messages. Start small. This doesn’t need to be this overall nebulous. Like oh, we need an AI head of supply chain. Nope, that’s too much. What you should be doing is getting incremental, like very, very specific workflows that need to be automated every week. And so it’s like, hey, this is my PPC agent that only focuses on reducing wasted ad spend. Doesn’t do anything else. No ranking campaigns, no day parting, no anything else, just reducing wasted ad spend. That’s the only thing this agent is focused on for PPC. Maybe it drafts. It’s just some other ideas. Maybe it drafts creator follow ups using information that your team has already verified. Start with something that is extremely narrow enough that you can inspect it and be able to say, yes, we got the outcome that I was actually looking for for an inventory process.

Josh Hadley 00:25:44  I would much rather begin with a recommendation somebody reviews than immediately connect a brand new system to purchasing decisions to say, oh yeah, so it reviews all of our reports and the daily sales from yesterday. Then it fires off an email to our manufacturer and they start producing. Nope, I don’t want that yet. Maybe 12 months from now I might have that that workflow automated, but not to start. You need to understand where it works and where it fails. Number four. Step number four. This is the proof. Did it improve the business if the old process took several hours, how long does the new process take? Once you include checking and correcting the output? Because guess what? If you’re like, oh, I spent the exact same amount of time, well, you basically did nothing other than just play with AI for the sake of it and actually cost the business money. You need to ask yourself the question, is the information accurate enough to use? Does the team catch important issues earlier? Does anybody actually act on what the system produces? Because here’s the point.

Josh Hadley 00:26:48  A report or a dashboard that nobody uses has very little value. No matter how impressive the automation looks and the time saved only becomes valuable if you do something useful with that excess capacity. That means make better decisions. Okay. If someone saves five hours a week, where should those hours go? As the leader, you need to be able to tell them where that answer lies. Last but not least, step number five is then scale, right? Once the solution actually works, decide what it needs to become so that it becomes reliable and useful across more of the business and get it integrated and people actually using it. This is where you may discover that a you need a specific hiring need, because your data might be scattered across a bunch of different systems that don’t agree with each other. You may need someone with a data architecture experience, okay? Or your prototype might work, but it might require too much manual intervention. And you need to hire like an engineer to build the integration properly. Okay.

Josh Hadley 00:27:57  or you might have ten departments asking for tools and no clear way to prioritize them. And you need someone that can actually own all of those decisions. It’s after you’ve gone through all of these processes, now you have a much better hiring conversation, and you know what you’re actually looking for, rather than just some random AI guru because you can describe the problem, show what you’ve tried, explain the limitations, and define the actual results that you need. That’s a much stronger starting point. Rather than hey, we just need somebody who’s good at AI. And then this brings me back to the responsibilities that software companies have, and why I believe that all of us are basically having to emulate and have the same responsibilities and roles that a lot of software companies have. Number one, someone decides what needs to get built. Number two, somebody makes sure that the data is actually usable and accurate. Number three, somebody builds and connects all of the systems together. And number four, someone test the output and maintains the thing after it launches.

Josh Hadley 00:29:05  Those are essentials in a software business, but it’s very foreign to us as a physical products business. Your company needs ownership of all of those responsibilities as it takes on more technology. So depending on your size, one person might be able to cover or cover several of them. You might use contractors, you might develop an existing employee and bring in specialist support. Look, the org chart can vary. The accountability still needs to exist because just building a tool is only the beginning. And that is where I think people are getting like so wrapped up in AI. It’s like you could build all these tools, but if you’re not thinking through who’s going to maintain them, who’s going to inspect them, who is your QA analyst to make sure that like the data is actually right? Otherwise, AI is going to start running you off a cliff. What happens when an input changes? What happens when a connection stops working? The API into Amazon changes when the output looks good, but is actually wrong? Who notices and who’s fixing it? Those questions are part of running the system, and for me, that changes how I think about developing our team.

Josh Hadley 00:30:20  That’s why I see this like rollout as a 12 to 18 month rollout. This is not AI tomorrow and everything’s automated. It’s we’re going to take off small chunks at a time, make sure they work, and then slowly begin hiring the right experts to QA. Check this to be our data architect and the data warehousing manager, etc. I want people who understand their department deeply and are willing to learn new ways to improve it. People who can say, hey, here’s a problem we keep running into, here’s what it costs us, and here’s an idea that we could test. That is the future for any of my existing team members. That’s all I’m looking for. They need to be able to execute judgment that says, here’s a problem we keep running into. Here’s exactly what it’s costing us, and here’s why. Solving it could lead to better performance. That’s the capability that you should be building throughout your entire business right now. And you, as the CEO, needs to you need to stay disciplined because you can spend an entire quarter building a clever internal tools or dashboards and still fail to improve the part of the business that needs the most attention.

Josh Hadley 00:31:34  So I want you to keep bringing the conversation back to the constraint. What is holding us back? What improvement would actually matter most? Who owns it and how will we measure the result? So my challenge to you at the end of this episode is to be very deliberate with the things that you are trying to solve with AI, and don’t get too carried away with all of the shiny objects of things that you’re going to see. Posted on LinkedIn or at conferences. The most important thing that you can do today is with your team members. Help them identify one bottleneck, one workflow that they have to do manually that, if automated, would save them a large portion of time so that you could use their judgment to create more strategic ideas and value inside of the business. So that’s what we do. Even my executive assistant every week. What is one automation that we’re doing okay. It happens throughout my entire team. Everybody is focused on one thing per week, one thing that we could automate. How do we just get that? And again, over the course of 12 months, 52 weeks, that’s 52 automations with my executive assistant.

Josh Hadley 00:32:52  That’s 52 automations with my supply chain team. That is the micro advancements that you have to do in AI, that you can look back and be like, we’ve got an AI first organization, so don’t be overwhelmed because everybody’s going to be shouting from the rooftops. Don’t get overwhelmed. Take it one step at a time. Your biggest value is the people that sit inside the business, that know the actual problems, lean on them and begin working with them. If you found value in this episode, the biggest thanks that you could give me is by sharing this with another entrepreneur who needs to hear this same message, or is maybe overwhelmed with AI and doesn’t know where to begin. Please drop it in the slack community, drop it in a Facebook or a WhatsApp group and let people know. Until next time, good luck!