AI Implementation and The Modern Workplace | Arturo Ferreira

How do you prepare your business for AI when the biggest challenge isn't the technology, but the people expected to use it?

Artificial intelligence is changing the way organizations operate, but successful implementation requires far more than new software. It demands new ways of thinking, new habits, and leaders who can help people adapt to a rapidly changing workplace.

Arturo Ferreira is an AI educator, business owner, and workplace strategist who helps organizations navigate the intersection of artificial intelligence, leadership, and the future of work. Drawing from his experience implementing AI inside businesses, Arturo focuses on helping leaders move beyond the hype to build practical, responsible strategies for AI adoption.

In this episode, host Chris Allen and Arturo explore why AI implementation is ultimately a leadership challenge rather than a technology challenge. They unpack how large language models actually work, why critical thinking is becoming more valuable—not less—in an AI-driven world, and what organizations can do today to build cultures that embrace innovation while keeping people at the center. Arturo also shares practical guidance for business owners, HR leaders, and employees who want to prepare themselves for the next wave of workplace transformation.

Key Points

• Why successful AI implementation depends more on culture, leadership, and human adoption than on the technology itself.
• How leaders can build AI-ready organizations by creating governance, developing internal champions, and helping employees learn to think alongside AI.
• Why critical thinking, curiosity, and adaptability will become the most valuable competitive advantages in the modern workplace.

Quote from the Episode

"AI isn't taking anybody's jobs… it's coming for a lot of job processes." — Arturo Ferreira

Resources & Links

Arturo Ferreira

LinkedIn: https://www.linkedin.com/in/arturoferreira/

If this conversation challenged the way you think about AI, leadership, and the future of work, subscribe to The Entrepreneur's Studio and leave a review wherever you listen to podcasts. Then share this episode with a business owner, executive, or team leader who's looking to build an organization that's ready for what's next.

https://www.auris.io/

Follow The Entrepreneur’s Studio so you never miss an episode:

Apple Podcasts: https://podcasts.apple.com/

Spotify: https://open.spotify.com/

Youtube: http://www.youtube.com

Instagram: http://www.instagram.com

The Entrepreneur’s Studio is sponsored by Auris, helping small and mid-sized businesses simplify payroll and HR with powerful tools and real human support. Learn more at https://www.auris.io 

Transcript

SPEAKER_02 0:22

AI and the workforce, what makes this exceptional is you have an opportunity to learn what I believe and many believe to be civilization changes technology on your company's time. And you need to be on top of it. You need to learn it, you need to accept it, you need to understand it, and learn how to think in it.

Chris Allen 0:40

Today's guest is someone on the front lines of one of the most consequential shifts in business history, the collision of AI and the workforce. When much of the business world was still debating whether AI was real, Arturo Ferreira was already learning, testing, and teaching it. Not as a developer, but as a business owner with a company to run. Today, Arturo teaches AI the way every time-strapped entrepreneur needs to learn it. Not as theory, but as a roadmap that you can use. In this episode, Arturo pulls the curtain back on the real challenge of AI adoption, which was never about technology, but about the people. Well, not everybody's there, right? Um, you know, one of the things that uh I I'd like to do is kind of demystify a little bit about AI, because not a lot of uh people and not a lot of executives know specifically how this thing works and what the fears are. So let's just just break it down. Like, what is a context window, what is an LLM or the model, right? Just give us kind of like the easy visuals to help us know like how does this thing work?

SPEAKER_02 2:30

Sure. So I think the easiest way to do it is even before beyond the uh vocabulary words and so forth, is just it's helpful to understand that an AI is not a thinking machine. It doesn't reason in the way you and I would. It's an advanced probability algorithm that mimics intelligence. So that's an important distinction because when you realize that it's not actually reasoning, but it's just guessing the most likely next outcome, it changes the way you use it, right? Because all of a sudden now it goes from, oh, it's gonna figure out how to steal my data to no, not if you don't give it your data.

Chris Allen 3:00

Yeah.

SPEAKER_02 3:00

Because it's for instance, if I don't know if Arden's participation is acceptable in this. Oh, it's totally fine. So let me let's try, let's try an experiment, right? So I'm gonna, I want you to finish my sentence, all right? So I'll start it, you finish. Are we good? All right, once upon a easy. Once upon a time in.

Chris Allen 3:17

Orlando.

SPEAKER_02 3:17

Or a little different, right? If I would have said once upon a time in and then told you it's where Sherm 26 is, Orlando becomes 100% probability. The context is what creates the AI. You just acted exactly as an AI would. We have been trained to understand that the context is time in a fairy tale. So that is basically how an AI, and I oversimplify, but that is generally how the process works.

Chris Allen 3:40

I love it. And and one of the things that I think is important is uh let's just say there's one of the ways that I I test me on this. It's like a context window is the whiteboard. There is a meeting that is occurring, right? That is a session, right? And then everybody coming into the meeting are the people feeding it the context, and they brought sort of their brief with them. So that's the context that they get brought. And these AIs wake up and those are the resources that they have to do stuff. It isn't like they're thinking and going into the database of all of your stuff and sort of mining things and things like that. The the model gets brought to the meeting.

SPEAKER_02 4:18

Yeah, I would say so. And even beyond that, you have, if you think of the meeting as the whiteboard, right? Going a step beyond, it's almost as if every sentence or question in the meeting, you redraw the whiteboard.

Chris Allen 4:28

Yes.

SPEAKER_02 4:28

Right? Because an AI doesn't actually have memory, it's just really fast at compressing what has been told. So every time you ask a question, it goes back to what you've been discussing, back to its training data, and has a whole new instance. Each instance is its own reality, it's its own sort of new uh expression of the AI. So you kind of, when it loses the thread, it means there's too much for its context window, meaning it's working memory. The whiteboard's full. The whiteboard is full. Yeah, precisely.

Chris Allen 4:54

Well, the the reason I wanted to talk about that is because there's this fear of uh, you know, with a lot of IT organizations that, like, hey, don't bring AI into your desktop because it's gonna go mine our data. It's got security risks and all these kinds of things. And I I wanted to I wanted to talk about that fear a little bit and how you address that when you're having conversations with IT professionals.

SPEAKER_02 5:18

Yeah, it's it's interesting because everyone kind of brings their own perspective, right? And I think we all become very uh guarded when it comes to what we are responsible for. So I think legal is probably, before I get to IT, legal is probably the best example of this. The job of the legal department is to overturn stones that we're not considering, right? But legal is panicking because the job of AI is to create infinite stones. So now, how do you reconcile your primary responsibility with what AI can do? IT does this just at a technical level, at a coding level, right? So there are concerns around how do we protect against data breaches that can happen very quickly. And not even data breaches, right? It could be the thing functioning as intended. About a month ago, there was a company, and I don't remember which one, I could look it up, but a company essentially had an agentic system working within their database. It uh it ran into a roadblock, it couldn't access its data, and in 13 seconds, it decided that the way to access its command was to delete the database and all the backups. Three months of data wiped in 13 seconds. This goes back to human in the loop. It's not a question of don't have AI or it's gonna eat your data. It's a question of have the safeguards in place to adapt with it. Because the adaptation, the acceptance of this as a changing technology, of a world changing very quickly, that that should be self-evident at this point, right? It's not going away. And we need to accept that as truth. How do we change our perspective around what's changing us?

Chris Allen 6:42

I love it. I think the thing that I was most enthusiastic about, because you're probably gonna hear me nerd out on AI, and I apologize in advance. But I will say one of the things that I love is this intersection of human resources and emerging technology is kind of where you sit. So talk about how you look at the world every day when you're getting up to run your business.

SPEAKER_02 7:01

Um, before I run my business, I have to run my children and get them up, right? So, and that's very human, right? AI is not doing that.

Chris Allen 7:07

Yeah.

SPEAKER_02 7:07

Um, so I would say when we're looking at the business, it is like you said earlier, it's the pivots, it's the changes, but AI factors into everything. And I think that's probably the biggest lesson to learn is marketing transformed with the internet, with YouTube, because all of a sudden you weren't marketing against competitors, you were marketing against everything on the internet. You were marketing against Instagram, against cat videos, you name it, right? So the internet transformed where our attention was going. AI is now transforming who your competition is because all of a sudden now, I don't care what level you're at, your competition is now expanding because smaller firms, smaller shops are rising because AI gives you access to these tools. The bonus of being part of a large organization is you have uh a war test, you've got people behind you, you've got expertise that you can use. The downside is it's a big ship to turn. So smaller firms, small to mid-sized companies right now have an outsize advantage because there's less roadblocks, there's more ability for them to really engage with AI and start to use it. Yeah. So, in terms of like the way we look at it, is what are the opportunities? What can we go after, and how quickly can we pivot to integrate AI, starting small and finding those edge cases that we can apply it into?

Chris Allen 8:19

That's good. Well, let's say you're uh someone in the room and you know the company's not letting you use AI. What do you recommend that they do? Uh, because the world is changing and the company saying no is maybe a different story than what we as individuals need to do.

SPEAKER_02 8:35

You just need to use it yourself. Like you so $20 a month for most plans, right? To use a paid plan, just pay it. You spend you spend $20 a month on dumber stuff, you're still gonna spend it on the dumb stuff, right? It's worth using it, it's worth engaging with it because it is happening now. Like you must be in charge of your own destiny in this case. This is, it's not, it's no longer science fiction, right? I was a giant nerd growing up, Michokaku, Ray Kurzweil, all the futurists that I grew up with are functionally nowists. This is happening. This is the world we live in. So it behooves us all to stay current and stay aware of what's going, most importantly, to understand the limitations and the capabilities of AI. Because at some point, either your organization is going to change its mind, it's going to look for the champions that know what they're doing, or another organization is like, hey, you know what you're doing. I want you to come work for me.

Chris Allen 9:24

Yeah. I mean, I I would say there's two classes of people that are developing right now. It's you're either leading a team or an organization and being told not to use it and you're doing nothing about it, or you're at night learning how to use AI and not to ask great questions inside of an app, how to actually enable it to drive different parts of your business and understand different things. Those are really the two that I'm seeing.

SPEAKER_02 9:47

Yeah, and I think that's that's where there's some fall-off to some of this because people have this idea of like AI expertise, right? How do I learn AI? Well, you just talk to it. And if you get confused, you continue talking to it and it'll tell you what to do next, right? It's being a good communicator within the context of what makes you good at what you do, right? It's what's the irreducibly human quality that you bring to your job, to your everyday, and how can you apply that? Because so at a coffee shop a while ago, I saw a sign that was like coffee, do dumb things faster and with more energy. That's AI, right? AI without context is that sign. So, what context do you bring? Do you enjoy cooking? I've used AI to help create, choose your own adventure stories for my kids. You know, do you need exercise plans? Do you want to plan a vacation? Anything that you can apply it to, it's extremely helpful for, right? If you like to make food, one of the hardest things is getting the food to your table when it's warm. AI will tell you precisely the timing. AI is now our primary care physician when my kids come home with inevitable rashes and so forth. So it's all the ways that you can do it and engage with it so you understand again how it functions, even as simple as it's a probability engine. By gaining exposure to it, you'll start to understand how that really plays out in real life.

Chris Allen 11:00

That's good. Well, uh let's just talk uh real quick about, you know, this the future is now. And what do you think is the maybe the gap in what and what period of years do you think the gap of the businesses and people who fail to adopt AI now and the people, you know, a few years from now that have? Like what do you think is what do you think is gonna be different about those two populations of people or companies?

SPEAKER_02 11:27

That it's a really good question. Um, and and I'm hesitant to answer because I I don't know that any of us can really put a number on. For sure, right? Um, it feels like one of these moments where it's gonna happen and we're gonna have just seen it pass. Like we're gonna realize the train's already passed us by the time it happens. Um, I think there's a there's a school of thought that would say it is already happening. There's already an outsized impact in being an early adopter. My instinct, my gut, my experience, and all that tells me we're talking to three to five year window max, three to five years before whatever comes next comes in, right?

Chris Allen 12:04

The last six months has been insane.

SPEAKER_02 12:05

It's wild, it's wild. Like the mythos class models with anthropic that just you know, fable just got pulled out for you know for reasons, and you know, there's so much happening at once. There are a lot of ethical and philosophical questions that come into play there that I don't know that we are gonna get into here. But when it comes to it, it is happening. That is real, right? So we look at this three to five year window and think, what can I do to prepare? You know, how how do I get ahead? How do I just get that edge around the people? And this is where the entrepreneurial mindset comes in at an individual level. You know, we have very close friends of ours, my wife and I, that have um that work for companies and they're like, oh, how did you start your own business? I was like, you know, it was a lot of work, but we also started doing this in our 20s where our risk profile was different. I don't know that I could do what I do now with three kids, right? So we've already kind of gotten accustomed to that. So all I can say is find that human quality of resilience and critical thinking and just hang on to it and start trying to identify how it plugs in. You are already an expert in something, personally and professionally. AI just adapts to that and it makes you better.

Chris Allen 13:10

I think uh if you think about the force multiplier that this thing can be, like if you we we started implementing it on pretty much everything, and we really went three to five times deeper on the things that we were doing, and we went probably three to five times faster, right? So we we it really has been a force multiplier. And if you think about over, let's just say even 12 months of doing that, somebody not doing that and going at the same pace versus people doing that, it is an accelerant. Like people really don't understand. That's one of the reasons why I'm enthusiastic about your advocacy for ethical use of this thing. And I think it's a really, really powerful uh message. I liked something you said to me recently, which was like this is the issue, right, of the AI sort of adoption gap is more of a literacy issue than a technology issue, right? So maybe unpack that a little bit to help us understand like what where people are struggling.

SPEAKER_02 14:04

So the last few months uh have been I've shifted gears from how do I teach AI to how do I understand humans? And it's been looking at it from an evolutionary biology lens. We find shortcuts. We're wired to do that, right? That's our job. We're constantly balancing energy in, energy out. And the hardest thing, one of the hardest things a human does is change a habit, particularly a mid to late career human that has been successful on those habits. So when we're looking at AI, AI is probably one of the biggest habit changes because it transforms the way you've just been successful, the way you've done your work. To give you an example, the lesson plans and the decks that I create to teach people, once upon a time would have taken me three or four weeks to build out, you know, 70, 80 slide deck, right? I can build that now in an hour and a half. Yeah, and that's everything, all in, done, ready to ship. But the one that used to take me four weeks, I could proofread in 30 to 40 minutes. The one that takes me an hour and a half to build, I will spend three or four hours editing. It's a very subtle way in the way we perceive our work, but it's critical because now we have to understand that we go from the actual doer to the editor. The work itself no longer matters, it's the proofreading, it's the being the arbiter of truth. So that's one way of AI literacy that's not using it, that's easy. Just talk to it. Be a good communicator, be concise, be specific, provide context. That's it. Those are the three rules of good prompting. From there, it's how do we actually think in AI, how do we understand what it's going to give back? And most importantly, how do I get accustomed to identifying false positives or hallucinations? Because remember, hallucinations are not a bug, they're a feature. It's the entire point. And AI has no context around true, false, right, or wrong. That's from our perspective. Generative AI literally just creates something based on its training data. So when we understand that our job is less about finding a needle in a haystack and more about getting rid of hay where we know the needle does not belong, that transforms the way. So literacy may not be the best word. I probably misspoke that day. It's definitely just AI thoughtfulness, perhaps, but it's that way of understanding it's the way it functions, really just speaking to it.

Chris Allen 16:12

I love that. I I think the evolutionary biology thing in AI is uh a very practical way to look at it. Go deeper on that and help us make a couple of connections on how you think about that, you know, from a scientific to a daily use kind of point of view.

SPEAKER_02 16:29

I mean, everything is habits, right? Our habits that have gotten us here, the habits that built this amazing convention center, Sherm is an organization, your own organizations. The repeating of a successful pattern is what has brought us here as a species. So now the question becomes how do we adapt to the environment? Because in all of nature throughout history, the organism that is most successful is the one that recognizes and adapts to a changing environment. And that's true throughout, you know, if you look back eons, right? So now, being that we are these conscious creatures, how do we consciously understand that there is something that is changing our world immediately now? It's happening actively, right? At an exponential rate. We won't keep up with it. So how do we prepare to blunt the impact? AI isn't coming for your jobs, right? So I interviewed, I was on your seat, and I interviewed uh Dr. Sam Simon and I asked him, like, what do you say to people that are afraid of losing their job? And he goes, AI is not taking anybody's jobs, it was going to do the jobs it's always meant to do. The problem is that we spent decades training people to think like machines. And that's resonated with me because that feels true. We we focus so much on the good student, the good employee, do what you must. And that's changed now. We need critical thinking, we need reasoning, we need you to be out of the box because AI can take over the menial work, it can take over the data. So AI isn't coming for jobs, but it is coming for a lot of job processes. So the processes now you have to pay attention to which of your processes can AI take over, which of those can it at least automate or augment? And now what does that free you up to do? Interestingly, that's also how an AI model works. And a mixture of experts is this type of AI that functions where you have a lot of super expert AIs in very specific fields, but then the problem becomes how do you identify which one's which? Well, you have one super generalist that essentially feeds the request to the super expert. That's, in my opinion, the next phase of people in their work is how do you become that expert generalist that can send to the agent necessary to execute a task?

unknown 18:38

I love that.

Chris Allen 18:39

I think uh there's an uh element of responsibility that I think is important. So maybe uh talk to us a little bit about uh what you would consider, you know, maybe elementary and maybe an advanced example of using AI responsibly.

SPEAKER_02 18:58

I would say an elementary example of responsible AI use would be be conscious of pictures you upload. So I gave the example earlier that it's our primary care physician. So if I take photos of one of my kids' rashes or anything, there's not gonna be any faces in it, right? Like I'm gonna crop the photo so it's just whatever I'm trying to look for. That's a very basic way of doing it. You know, a lot of people I think get caught up in AI is gonna take my data. Maybe I can't speak to that, but let me ask them how many times in your life have you written your social security number or a piece of paper and handed it to a stranger? Tell me exactly the number, right? Car notes, doctor's dentist's office, right? Any number of places. You don't, I don't remember. I got notes how many times. So your data's out there, it exists. So now the question becomes how do you effectively communicate to get what you need? Right? And AI has this unique ability to make you a lot more open. I give an example in my classes where when you Google something, you might Google, does vitamin C treat COVID? Right. When you use a generative AI, you're more likely to say, hey, I'm a single parent, I'm between jobs, I can't afford to go to the doctor. Can I use vitamin C to treat my kids' COVID? That's a lot more information you just gave the model, right? Because it mimics that human interaction. So understanding the fundamentals of prompting of what you really need to do to get the output you want, that's probably the most critical piece of AI safety and appropriate hygiene that you can use when you're doing it. It's just give it precisely what it needs to get the output that you need. An advanced version would very much be under understanding and identifying the minimum amount of data a model requires to execute on its task. Same idea, just a larger scope. Especially if you're working with personnel data, sensitive information, medical health history, that kind of thing. You need to make sure it's fenced in, sort of blocked off, and this is where we're looking, you're going nowhere else.

Chris Allen 20:46

Yeah, no, it makes a lot of sense. Does does anybody remember when people put on their resumes that they were a good Googler? Right? I I've seen a couple that are like, I'm really good at writing prompts. And and the weird part is like, uh tell me more. And then you see people the way that they think and then the way that they prompt, it's like, man, maybe that is a maybe that is a skill. Um, but one of the things that I think would be interesting to hear your perspective on is this idea of a closed market versus maybe open source. Let me tell you what I mean by that is there are a lot of creative ways that people are coming up with to leverage uh AI sequencing, where you were talking about orchestration and getting agents to work and things like that. And there's this tendency for those people to have a choice between, man, should I package this up, put it on GitHub, and tell everybody about it so they get this library of free skills to enable this to go further faster, or should I close it off so that I don't allow my competition or other people to make these discoveries to outpace me. I just want to know, like, because that that's a that's a very legacy way of thinking, the open source world, but this is a totally new version.

SPEAKER_02 21:56

And this is an interesting marriage of economics and science, right? Where the scientific communities often peer review, get your findings out there versus like let's hoard the data. Yes. There was a transformation at some point in the in our in our past where scientists were like, hey, we'll probably do better if we just share some stuff. Not blanket truth, right? But for the most part, you see that peer review. Um, there is a lot of argument for sharing the things that you have come up with. I think it's inevitable at the speed that AI Moves that you're not going to have much time with an edge case scenario, right? You can pretend that you can patent something or trademark something, but AI functionally gives you infinite possibilities at reaching and approaching a problem or reaching an answer. So I think the market itself that will shake out, but then there's another level to that, right? The economic side. And there's a um there's this idea that we are in the last economy. Because if you think of economics, you think of a market, what makes a market function is edges, right? The misvaluing of things, right? Someone sees the misvalue, takes advantage, capitalizes, makes money. And AI is not going to make those mistakes. When AI starts to run a market, what happens when things are correctly valued at all times? Where are the edge cases? So there are a lot of questions that keep feeding into the overarching idea that the conversation clearly around AI is really less about the technology and a lot more about the social, cultural, and even philosophical implications of what this means for us.

Chris Allen 23:16

Like when uh uh let's just set doomsday aside. What what are the things what are the things that are relevant, I'm gonna say logical or reasonable fears with AI in the workplace?

SPEAKER_02 23:31

It's interesting because AI in the workplace might be the way we look at it, but just AI in general, I think my doomsday aside, my biggest fear is just the lack of critical thinking that you really do see two classes of humans start to emerge in the coming decades where you've got a group of people that are the producers and the others that are consumers. We already see this playing out with social media, we see it playing out with all our networks, we see it playing out with our TV, you know, like the iSlop. There's it's just it's everywhere and it's unavoidable and it's going to get worse, right? So there is very little we can do other than hang on to that irreducibly human quality of critical thinking and make an effort to understand it so that we are prepared to take personal responsibility. I think for too long we've allowed outside forces to kind of say, okay, here's what we're doing next, and here's what's cool or what's not, or how to be involved. And I think I hope to see this sort of return to a more simplified social sort of experience where we've got, yes, we've got our AI-based virtual experience for personal and professional gain, but then we can all go kind of touch grass together. Yeah. I would say losing that that that human texture, that, that, that ability to just be and talk and be together, I think that would be a fairly big concern about.

Chris Allen 24:49

I think your perspective that you basically just said one of the biggest things to fear is that there's gonna be nowhere to hide. Ultimately, is is what I what I was translating as to what you were saying, is if there's not a place to hide, you're gonna, you're gonna actually what I just heard was that potentially AI could reveal more precision or accuracy instead of people being able to hide or mask certain things. This is a a revealer of things that are more accurate and more precise.

SPEAKER_02 25:15

Yeah, I I would, I would, I would say that's that's pretty accurate. And I I've often felt, even from the earliest iterations of generative AI, that this is something that we can no longer pass the buck, right? We have to face what we are, who we are, what we've done and haven't done. Because you we've all heard the phrase garbage in, garbage out with AI. When an AI makes a mistake, it's usually not the AI's fault. It's either the person that uh trained it or the data it was fed. And that's on us. So at this point now, it starts to really look at it from a workplace perspective. It's data hygiene, right? Cleaning up data so the AI can use it effectively. But if we pull the lens back a little bit as a just a human, it's well, how do we create our own? Like how do how do we clean our own data? How can we be authentic and real and approach this from a perspective, otherwise we're lost? You know, that that that truism of just being uh real about who you are, what you do, what you're capable of. And I I I don't enjoy going down these like long philosophical trails, but I do think it's important. And I think if any group is ready to hear that, it's an HR, it's an HR team, right? It's it's the nexus of where all of AI happens because policy, personnel, data all runs through HR. And there is a lot of philosophy in an HR's day-to-day. There is a lot of how do I deal with the people that are looking to me to answer my questions. So by by really honing in on what makes what is authentic and true at an organization, at an individual level, I think that's where we start, we stop needing to hide. You know, is the idea that there's nowhere to hide. Okay, so let's stop hiding, let's start owning it, and let's start making it ours and not the other way around.

Chris Allen 26:55

It's awesome. And one of the things that I think we should spend just a couple of minutes on is uh, you know, instead of AI sort of theory, right, which I I love how practical you are with it, uh what are some of the cultural uh must-to-dos, right? That that you you we need to have in the sort of the ethos of an HR or uh group or uh executives leading a business. What are some of the cultural things that you think about, like this is how you should institute these pillars in order to have sort of the right cultural aspect to using AI?

SPEAKER_02 27:27

Um the the first the first two pillars is always governance and people, right? So you need a governance structure to begin with. That's the first step. How do we use it? How do we not use it, and how often do we meet to change it because it's changing. So let's let's bake in the fact that we need to figure out what comes next. The governance strategy should be everywhere. And it can be three sentences, but make an effort, right? That's that's the first step culturally, is just how do we apply AI, which is interesting because a lot of people make the connection to this will change things like the internet. Mostly true, but this is not the internet, right? The internet was a way to connect, this is a way to create, and that changes the way we need to look at it. The other side is people. You need to have AI champions that understand and connect the AI systems to the day-to-day. And that group of AI champions needs to be cross-functional, cross-departmental. DHL had a really good rollout a few years ago where they did this AI system to improve drivers' routes, and the drivers were very uh resistant at first, but they brought them in, got their opinion, and it's been ACEs since, right? I mean, not without its issues to work out as any. But the point is you had actual adoption, which tends to be the biggest issue with most initiatives, right? We all have experience where something's like, oh, do this from the top down, and then two years later you've got 15% uptake. This needs to be a grassroots sort of like multidisciplinary, multi-departmental effort, or it doesn't go anywhere.

Chris Allen 28:49

You know, uh one of the things that just sort of jostled my memory or just thinking was this idea that the AI uh champions have to come out of tech IT. And that's not happening. There are so many different places that this is coming from. How can we, as organizational leaders, think about how to assemble the champions when they don't sit in this sort of mandated IT or tech department?

SPEAKER_02 29:14

I mean, just look for the curious people. Look for people that try to want to solve problems, the people that show up on time. It's not an AI problem, it's a people problem. We've always had that problem. You've always had people that do work and people that don't. People that kind of, eh, and then the people that are really going after it. Find the people that are curious. So you, you, you know, when you introduce me, you're like, oh, it not only is he a business owner, he's a developer, right? I'm in a developer in a very loose sense that I developed my business, but I am not a developer. I was not trained in technology, I didn't study coding, none of that. At best, I'm an accidental college graduate, right? I was in the military, I got out, I went to Loyola, Chicago with my army transcript. Like, what's my fastest way to my degree? And she's like, psychology? I was like, done.

unknown 29:54

Right?

SPEAKER_02 29:54

That was what that is 100% what happened. So at that point, it's just what do you bring to the table? How can you really look at what's in front of you and find people like you? Because again, AI melts away the mode of technology. You don't need to learn Python, you don't need to learn how to code, you don't need to learn how to build a data warehouse. AI will help you with all that. You just need to understand what you are doing, what you want to get to, and how to communicate.

Chris Allen 30:22

100%. We've talked about a lot of stuff, Arturo. Let's let's leave the audience with this. If there was one concrete step that an operator or leader or small business can take this week to really build something smarter or a more AI-ready business, what would it be? And what is it, what really matters to start there?

SPEAKER_02 30:43

I would say it's creating a plan to upskill a group of people that you trust and can rely on. Get people trained in how to connect it, not just using AI. That again, that part is easy. It's how do you connect the dots from using it to solving a real world problem with it? So it's thinking in AI, identifying a problem, and then building to that problem. It doesn't matter if it works or doesn't, because if it doesn't work, you prompt three more times and you're gonna find a solution that you didn't get to. At an individual level, just take your phone, move your web browser out of the way, and put your favorite AI app where your web browser was and make that your go-to search engine so you start getting into the habit of actually using it in your day-to-day.

Chris Allen 31:24

Man, that is awesome. Well, everybody give Arturo a hand. This was amazing.

Narrator 31:34

Thank you for listening to the Entrepreneur Studio Podcast. Check the show notes for resources and links from today's episode, and follow us on Instagram at theEntrepreneurs.