What Business Leaders Must Understand Before Scaling Agentic AI

AI is getting faster, cheaper, and easier to access, but that doesn’t mean it’s safe or ready to run your business unattended. We talk with Wilfred Morgan, an AI systems architect working at the front edge of enterprise AI automation and multi-agent orchestration, about what actually matters when you move beyond prototypes and put AI agents into production. If you’ve ever wondered why an AI rollout can look “successful” on a dashboard while quietly failing in the real world, this conversation is for you.

We break down the jump from prompt-driven generative AI to agentic AI: systems that don’t just write a good email, but can execute tasks, pull from multiple sources, and operate like structured digital workers. That power comes with a dependency most teams underestimate: context architecture. Clean data, clear processes, and well-curated knowledge artifacts become the fuel, and legacy data becomes drag. We also talk about the competitive reality that AI-native companies can build modern workflows from day one while larger organizations often wrestle with legacy systems, governance, and compliance overhead.

Then we go straight at the risk side: subtle errors, misplaced trust, and why confidence can trick humans into believing incorrect outputs. Wilfred shares a practical evaluation-first mindset inspired by high-stakes domains like aviation and healthcare, plus a grounded checklist for small business owners using systems thinking to map the customer journey and decide where humans must stay in the loop.

If this helped you think more clearly about AI automation, subscribe, share the episode with a friend, and leave a review so more builders and leaders can find it.

Thanks for tuning in to this episode of Follow The Brand! We hope you enjoyed learning about the latest trends and strategies in Personal Branding, Business and Career Development, Financial Empowerment, Technology Innovation, and Executive Presence. To keep up with the latest insights and updates, visit 5starbdm.com
.

And don’t miss Grant McGaugh’s new book, First Light — a powerful guide to igniting your purpose and building a BRAVE brand that stands out in a changing world. - https://5starbdm.com/brave-masterclass/

See you next time on Follow The Brand!

Transcript

Welcome And Why AI Pulls Us

SPEAKER_00 0:02

Welcome everybody to the Fowl Rand Podcast. I'm telling you, I live in Omaha, Nebraska, but something keeps pulling me back to Florida. I'm not sure what it is. I think it's this whole entire AI buzz, and it just just just magnetizes me back to the Florida area. We're going to be talking to Wilfred Morgan in Orlando, Florida. He's an AI systems architect that's operating at the front edge of enterprise AI multi-agent orchestration and production-ready automation. This is what we're talking about because this is going beyond prototypes. He's architected, autonomous agent systems with more than 20 specialized agents. So we're going to talk about this. He does a lot of this with no operate, like zero operator execution. This is big. He understands compliance, QA gates, and context architecture across more than a thousand knowledge artifacts and AI, what we call driven SDLC transformation for large-scale engineering teams. So I feel what makes his perspective especially valuable is that he understands both enterprise governance and autonomous agent design. And he knows what happens when AI looks successful on the dashboard, but quietly fails in production. So today we are we will explore evaluation first architecture, failure engineering, trust, security, token economics, and what leaders must understand before scaling AI across regulated environments. So Wilfred, would you like to introduce yourself?

Wilfred’s Path From Banking To AI

SPEAKER_01 1:50

Sure. Thanks, Grant there. Thank you for having me on. And so uh yes, my name is uh Wilfred Morgan. And uh so I have been uh technology professional for almost 20 years, actually 20 years. And uh how I started, uh technology wasn't even my initial interest. Uh you know, I was studying international uh studies, and right around that time was the internet explosion, and I was just fascinated and I got pulled into it. And so my technology path is very uh self-taught, self-driven, uh figuring things out and breaking a lot of things there. And from from that, uh, you know, I was working in the financial uh the banking industry, uh running technology platforms from there. Uh, you know, and so regulation security was a big thing. Internet banking was uh exploding. And so it wasn't about just securing your branch, it was securing your networks, you know, uh securing your platforms there. And so I had done that for a number of years. Uh and then through technology consulting, I actually uh latched on to software engineering. Yeah, this was about, oh gosh, almost 10 years ago. Yeah. And uh it's it's strange. I went from help desk system admin, managing an IT department, uh CIO. And then I got into software engineering and kind of took, I don't want to say a step back, but a step sideways and started to learn how to build software, not just work with vendors who built the software. And so that was very enriching. And I started learning data science back when it was big data uh and it was just um, you know, machine learning and more conceptual. Uh, and so you know, from that process, I've been able to, I would say, become a jack of all trades in technology and master of none. And usually it's better to specialize, but because of that, where we are now with technology has been such uh a blessing because I understand how different parts of it work. So then now taking AI and being able to, it's like accelerant. It is so different the way I'm working now than I was even two years ago, even two years ago, 10 years ago. Uh, you know, and it's it's it's exciting. But at the same time, uh, you know, part of you know why I started to become vocal about the work I'm doing, and I've I've never been that. You know, I'm not someone that uh gets out there. I'm too I'm too busy in the lab tinkering and breaking things there. But you know, I think there is so much that is happening right now that has such big impacts, and some of which we haven't even begun to really see yet. This is still the beginning. Uh I said, okay, it's similar to what happened with the internet, you know, and technology goes through these cycles there. But the difference is that, you know, unlike other technology waves, the internet, the mobile uh wave, this is a much bigger, faster, and more dangerous game in technology.

SPEAKER_00 5:43

Uh I want to stop you there, and I want the audience to really lean in on what you're talking about. There are changes in technology over time that have marked the human experience, the cultural experience of being human and human behavior and what we do for work every day has changed or changes. Now we think about the advent of just the computer itself, or personal computing, as you stated, or the internet, mobile computing. Now we have we in the background, we've seen, like you brought up big data, cloud computing. This is going on in the background of most everyday life. We're not realizing now, and I tell people all the time, you live in a digital reality now. You you live and work and dwell in a digital reality. The richest man in the world now got rich on digital technology. He didn't reinvent money, he just gave you a different way of processing money. That was PayPal. Now he's done other things further than that. This is a platform shift. And so if you've been used to working in a certain way, and I gave this analogy earlier when I was talking to Wilfrid, and I'll say it again now. It's like if you can take a group of cows and put them out in the pasture and fence them in, they're gonna stay in that particular uh area because you know there's a barrier there. But even when you remove that barrier because of habit, they're gonna stay kind of there. Because of AI now, it's a platform shift. Think of this, that we've removed the barrier where enterprise AI was only available to this people with major resources. Uh that same enterprise uh application, business intelligence, the tentacles of information and data are just ubiquitous throughout the planet now. You can micro-learn just about anything if you put forth the desire and you want to learn it. You don't have to have an IV lead education, but you still need to understand context so you can ask the right questions. Help us understand from your lens, when I say we've removed these barriers, and now AI is unleashed into the wild of human creativity. What are you seeing?

AI As A Platform Shift

SPEAKER_01 8:08

So I think what uh there's a couple of things. Um in terms of the accessibility of platforms that only the largest companies in the world have access to, that's a big, that's a big deal of being able to, it's it's like saying that, you know, before uh only the biggest companies are allowed to do business, uh, you know, let's say in this building, uh, because they can afford the rent there. They can they're the only ones that can afford to set up shop uh on Fifth Avenue uh because you know they can afford the rents, they have all the connections, uh, you know, they have the teams to be able to properly zone for it there. Uh but now individuals that have something that the world could uh value can also set up shop along those same lanes there at a fraction of the cost there. You know, this notion of it takes money to make money there uh is a falsehood. And never before in human history has it been more so the ability to create value out of seemingly nothing there except your own drive and knowledge and applied knowledge uh there. Like you don't have to uh worry about building something in order to get something, this massive thing in order to get something there. And and that's and that's that's what we're we're working with. And it's available to all. You know, it really is available to all.

SPEAKER_00 9:54

It's totally available as you stay. Like when we started tinkering, I call it tinkering with cloud computing, and I understand, hey, I don't have to buy a massive server, or I don't have to have buy my own IT uh data center because that's what they were doing, right? You have to have enough money to invest and buy this whole you know racks and racks of servers into your own data, which is very expensive to only not just buy, but then to maintain. Well, guess what? You can swipe a credit card and then have access to the same kind of compute power that this guy just spent a million dollars. That was cloud computing. So now we now we're scaling up because of COVID. The good thing out of COVID, it exposed the world to technology applications, just like video conferencing. Like, wow, you know what? On load, and no one really knew this. On load, I could do video conferencing at scale when I got millions and millions of people on my platform. Nobody really, you couldn't test that. You couldn't, you know, engineer that. But now you see it worked. So now you got a lot of people exposed to enterprise type applications that they weren't, even though it was on your phone for years. You could video conference on your on your cell phone or your smartphone, but you weren't utilizing it. You don't really need to do that, right? But now you had to do it during COVID. They started saying, well, what else can I do? They had this very standabout metaverse with, oh, I can go inside this digital reality. Okay, that was kind of a cool, kind of a fad. But now we're seeing now with AI, I can live and breathe in this thing all the time. The things that I'm doing on an everyday basis, whether it's simply writing an email all the way to enterprise identific AI workflows, this is becoming real life. You're like, okay, this is interesting. Now, I'm gonna tell you a little bit about Wolfra's telling me. He went to school for international studies and affairs. He now became a CIO and now doing his own software engineering. He has no electric or electrical background, electrical engineering background, yet he has expertise in this area. Talk to us about how this is such a game-changing industry and now that the everyday person has the ability to actually create in these platforms, also.

SPEAKER_01 12:23

Yeah, I think what what's so remarkable is uh, you know, unlike practicing medicine, you're gonna have to go to established institutions of knowledge there. And I know there's various forms of uh, you know, uh types of medicine established versus more holistic, but there still requires uh formal education, uh, a formal process there. And you you can learn some things, but there is barriers. There's real barriers uh, you know, to it. Technology is not like that. And the thing is, it's never been like that. Uh Steve Jobs started it in a garage. Uh, and so that spirit is very much so, and now it's just hyper-accelerated. All the things, you know, that Grant, you're talking about how cloud computing has changed things and it's been around for a while.

Orchestration And Digital Workers

SPEAKER_01 13:26

Video conferencing has been around since the early 2000s, late 90s there. Um, but I think what's happening now is we're taking all these technologies that have been built over the last 25 years and we're stacking them. And now AI is able to then allow you to really use them in a much faster way with more impact and with less resource out of pocket there. And to do so much, you've got so much technology available, and then AI allows you to be able to almost build your own team that you can direct there. Uh, you know, and so that's why, you know, orchestration is is a it's really one of the most powerful things about uh AI. Uh is once you start to use it uh and organize it, orchestrate it in a way to do work that you don't have the time for. Do work while you're working on one task, you can start to do other things uh and process there, and you start uh getting some strong results, then you start to think, whoa, oh wow. What you can start to bring out of your head into reality becomes much easier. You can start to experiment faster, learn faster there. It is, it is definitely uh, I think the the best part of it for me is the acceleration. Uh, the internet was an accelerant in terms of access to information because I didn't have to get into a car or hop on a bus and get to the library and sift through all these books. I can now go through a lot more information and text faster. Now, AI then has the ability to have the work that you do uh accelerate in a similar manner and also take information there. And that that's what's really that's what's really important. That's what's that's where the transformation uh is is is happening and can happen there. And that's why there's so much excitement and so much money being poured into it. Because uh, and it it it seems irrational, and I understand that. Um, but it's it's part of the understanding of how things get done, how work is gonna transform, and that's what's captured the attention there.

SPEAKER_00 16:02

Well, you said there, I want people to really lean in. Work is transforming the way we work, and think about this. Think about then uh the beginning of the 2000s. How did you work? How many people are really utilizing Microsoft tools, PowerPoint, Word, you know, these types of things. And before that, well, you didn't have to do all that, right? And you see, it fundamentally changed how you had to work. You couldn't get a you can't get a job now without having fundamental digital uh uh literacy, right? They're gonna look at you. If you can't open up a laptop and send an email and and draft some kind of uh uh or work in a CRM system or anything like that, uh that's gonna limit you your your your uh ability to get a job. Exactly. Exactly. AI is going to be on that level. Now it is on that level, meaning, and I I need you, I want you to help people understand now that, okay, I think there's a lot of AI curiosity, and they might have dabbled in what we call large language models, generative AI. Like, hey, yeah, I see what he's talking about. I can access information quicker, better than just Google's 10 links on a search. I got that. I know that I can search for information and it can frame um uh different types of text in a way that's very uh professional in manner. I get that, I understand that. Well, that's an engine. I call that the engine. When you get into the transmission of that kind of capability into what we call AI agents, and then we go to that next level of addictive AI, help people understand what you're talking about, that multiplicity and an acceleration of work that's now can be done at such scale that I don't think we're gonna recognize the workplace by the end of this decade.

SPEAKER_01 18:03

Right, right.

Agentic AI Versus Prompting

SPEAKER_01 18:05

It's I think in terms of uh, you know, when I try to explain uh the impact of what the technology can do, and going from just prompt engineering, just chat GPT is uh something, versus having uh your business, having your organization uh being run on this technology. I think it's when you talk about agencai AI, uh, you know, versus prompt engineering, uh, you know, agenc AI is now it's not just producing a nicely worded resume, uh, a nicely worded email. It is actually has the ability to execute work that a human person was doing, uh, and not just execute work, but also take information from one source and analyze information from a different source, and then produce an input or an output, produce uh either some kind of report, answer a question you want, or they use that information to then more accurately execute what you want to do there. And that's that's what's really exciting there is that it becomes uh you have potentially exponential productivity uh because the uh the better data that you're working with, um the more organized that you have your business with. AI allows reward for running your business properly, it rewards good data uh in a way that you're able to um not just execute, but make better decisions because you have a clearer idea of what is uh you know what is happening there. So, okay, here's an example in terms of uh the day in the life there. So, you know, I love to read uh about technology and I look into the latest news, or I, you know, I'm listening to podcasts, you know, like uh grants there and uh watching the YouTube videos there. And a lot of people in my position, you know, when they absorb this news and information, you know, the things they ask themselves are well, okay, what is the salient, what is the important information uh that Grant is telling me of something I don't know? And then how is it relevant to what I'm doing? And then do I have to change what I'm doing relative to this new information? So those things uh would take time uh because you have to uh you know process everything, you're uh going through the uh you're reading the article, you're watching uh the YouTube video, or you're listening to the podcast on your way to work there. And then you're thinking in your mind, okay, how does that relate to what I'm doing, or is there any piece of information that's new? Are things that of course uh we'll continue to do, but then making the switch of okay, how is that going to change what I'm doing? Now, if you are uh a solo operator, you know, with a very straightforward business, you can make that at a snap of uh uh of your fingers there. But when you're working with uh a sophisticated business with multiple systems in it, there, you're gonna have to talk to someone. You're gonna have to uh, okay, how are things going in this part uh of the business? Get their feedback, and then you can say, okay, take a look at what Grant has uh uh shown us in this his latest podcast and see how it's relevant. And then they're gonna have to run with it and you have to wait for them to get back uh to you. Uh no joke, the ability to now with AI techno uh tools and agentic AI in particular, uh this transcript, you can use this transcript that we're uh having here and not only process, okay, summarize what uh Grant and Wilford are talking about, uh at least the bullet points. And then you can just drill down. And then what's most important to me? But having agent systems that already know my business, this is the powerful thing. It's I don't have to just type it into Chat GPT. The agent system runs independently of the chat GPT browser, it runs there and it already has the information of how your business is run, which is what we call context. And that is such an that's the fuel that runs this is the context. And it has to be the right fuel. You can't just serve it any old thing. Oh no. If it's a diesel engine and you're giving it credits, that's gonna be a problem. And yes, it's gotta be premium. And that's where having the good data, you get rewarded for that. But now imagine being able to then receive in your feed uh this podcast, being able to get the transcript, and then the agent is reporting to you, okay, uh, based on the new information in this latest podcast, in this latest article, um, here are the things that are new and important, and then here's how it affects your particular business. And depending on the rules that you have set up uh there, because AI agents then kind of act as uh kind of independent, very structured workers. They're digital workers, and they can then say, look, um continue with what you're doing, but change these things. That is powerful. You and that can be as soon as you log into uh your laptop or or or hop into your phone and have that information available, but you have to set that up. That's where the orchestration comes in. It's not you just uh inputting, it is now proactively giving you information there. And that is why the money is get uh coming in. That's why the biggest tech companies in the world are pouring money in because the enterprise, their customers are looking to have that level of white glove service. This is the opportunity for technology to provide white glove service for a business there. Uh and that can be the difference between uh you having a successful fiscal quarter, uh hitting your goals, or pivoting on an opportunity uh or avoiding something that doesn't work. Oh, this is not working. We need to pivot there. And that is the money saved and the money made from that is very massive.

SPEAKER_00 26:15

Now I'm gonna go, I'm gonna stop you there because this, I want you gotta lean in what what Wilfrid just said.

Context, Data Quality, And Legacy Drag

SPEAKER_00 26:21

And a lot of this hinges on I call legacy data and context. Because this is this is the problem, I would say. What's the big problem that has to be solved in order for this, what you just described, to be successful? There's a lot of legacy data out there and bad data, just just garbage information. One of the things when ChatGPT and that kind of thing came out, it's it's ingesting internet data, which could be it's just bad water, put it like that, because it's just a lot of garbage out there. So if it doesn't have the right context, as Wilfrid said, it doesn't understand that, you know, good from bad, it's just taking information and trying to make the best out of it. So I think the most successful companies coming out of this, big, little, small, single, single person business is the clean data yeah, and that you're not having to bring forth legacy data that is not going to be uh beneficial for you, that's gonna clog your systems because it can't, you know, it has to fight through all of this, you know, historical data that really is not beneficial. Who's gonna win in that case? And I'm gonna give you a case in point, true story. I worked for uh AT ⁇ T Lucya back in 2000, right? And I worked in the uh telephony world, right? And we had big telephone systems and they they were analog systems, some of them they became digital systems. These are these were they were the they had a monopoly more or less on these types of big uh um uh PSTN uh systems, PDFs systems is what we call them, right? Then voice over IP came out, right? That you can do voice telephony over a data network and not just a telephony network, the analog, the older systems. Well, what happened is that technology started to mature is that the ATT Luther Viber had to maintain those old legacy systems while still going forward with the newer voice or IP systems, where the newer companies, uh aka Cisco, C A S C O didn't have to maintain that older system. And the newer people that were getting on board and learning these detects, well, they were the data people, not the telephony people, right? So, what are they gonna prefer? They prefer these things, this is just an application on the data network. So nobody in the telephone would want to hear that. Oh, what are you talking about? Well, that's exactly what it is. It's just packet technology, right? So, not to get too technical about it, is that Cisco did not have to maintain old legacy systems. And they were able to move quicker, faster, better with the newer tech that actually overcame the market and became the market leader. I'm going to say right now that the companies that have to maintain these old legacy systems are going to move slower. While the newer system the newer businesses can now say, hey, I can build flat and use this AI foundationally and this orchestration layer day one and outperform my competition. I want our small business owners to understand this, our solarpreneurs, our our mid-sized business to understand you have an incredible opportunity if you follow what Wilfred just said. If your data is right, your infrastructure is right, you can orchestrate. Because you can take bad data and run it into a tree.

SPEAKER_02 30:07

Right.

SPEAKER_01 30:08

Exactly, exactly. Uh and I think actually, and this this is a great point because uh and tell uh the telephony transformation, that's a great analogy. Because before you were either a telco guy or a network engineering guy, and it became it converged into one. And you know, I right and it's funny because Lucent IVA was the lab that developed the technology uh that Cisco used. And so they were they were now getting competed on their own technology that their labs had developed there. And that's that's the real irony. And this is the thing that keeps businesses up at night is because we are now at that inflection point where if you, like Grant said, if you do not adopt this technology, you can get left behind. And I think the difference between the other technology revolution uh evolutions that we've experienced is that this is happening much quicker than anything before it. Right. The transform the speed of the transformation, and that's why I said the the game has gotten bigger, it's faster, but it's also more dangerous there. Uh and it's one of those you could give yourself some time before you had to take out your PBX old legacy telephone system and switching over to uh IP. But now the cost of waiting too long is can be really high because the business, the first business, the first few businesses that figure out how to really harness this are going to explode so much faster. So this this race is really we're we're in that part now of uh yes, we're still in the frontier part, but this is definitely an extremely high stakes, high speed race there. Uh because the rewards of getting it right, or at least getting it right enough to get to the next level, uh, it's too big. And it can be one of those situations where uh it's not even can be. There are going to be companies, well-known companies, that we all know, and they are not going to be around. I remember Sears, I remember Blockbuster, I remember exactly. That's why that's why there's so much attention there. Uh, and I think one of the things that uh uh you know we can also dive into, Grant, is the the dangerous part of

The Real Risks Behind The Hype

SPEAKER_01 33:11

this game. Yeah, let's do it. And so one of the things that has uh kind of spurred me to be more uh vocal is well, one, there is a lot of opportunity and it's exciting. Uh there's opportunity and there's access to more people than ever before. And that is great. But also, there's a lot of danger. Now, part of it is the information itself, the hype cycles. Who do I trust with this? Um, you know, is this like the Terminator? Are they going to take over? I mean, it it just taps into fears. Uh, there's a lot of distortion, and there are people that are trying to profit off of that fear and that distortion of information there. And that's the part that is is really uh concerning. The other part, too, is that now going into medicine and healthcare, there are right ways to do things and there are wrong ways to do things. And okay, if I try to do something in Microsoft Word that doesn't work, okay. Uh I may get an error, or I may have a typo, or formatting gets a little weird. Okay, no problem. When it comes to making an error in, let's say, surgery, now we've got a very, very different consequence there. And AI, although it accelerates and enhances our opportunity uh and the benefits there, if it is done incorrectly, the consequence can be devastating. And and this is this is one of the things that in in the frontier part, I am making every mistake in this field. Absolutely. It is the best way I try to explain it to non-tech people is I'm in this jungle. Me and a couple of us, uh, frontier architects and engineers are cutting through this jungle, this massive jungle. There is no roads, nothing is being paved, no rules, no nothing. No, no traffic lights, no electricity there, and we're just cutting through this jungle, and we're getting bitten by snakes and mosquitoes. And I've got my foot caught in a couple of uh ditches there, and oh, to pull myself out there, it's like okay. Uh and part of what uh uh concerns me is that it is easy to produce results. Uh, but Grant, you said something, and I think it's important to uh really impart in the viewers there. If you do not have knowledge of what you're trying to do, fundamental knowledge, and then you put it in the hands of AI. Uh, if you don't know how to cook and you ask AI for a recipe, how do you know what you're gonna get is going to taste good or not kill you? And I think that's that's the thing that's really important is that AI can't be a shortcut for not knowing anything. You can't, you have to be knowledgeable in your field, you have to understand your business or your practice, you have to have that field of expertise. Now, the great thing is, is that for those that have that uh experience, now is a great time to jump on it. You can create so much more value now than you could three years ago with what you already know, with what you've spent a lifetime of learning and perfecting and you know, improving over time and being able to do that. And we're going to need you, the pe the those of us that are implementing these systems, we need the experts in the field to make sure that what these uh these uh digital workers are producing are um accurate there. So one of the things I've started to do, uh, Grant, is I've I'm taking all my my learnings. I I've been journaling my journey through AI and I've captured it onto uh you know my website there, and I'm I'm sharing posts through uh through LinkedIn of what I've gone through so that people can see and say, oh, I've gone through the same thing, or ooh, that's something to look out for. And I particularly want to help people avoid uh the traps and the pitfalls there. Don't step up. And and then to say, okay, you're a business owner or you're you're an experienced professional. Where do I start? Now, this person is saying this thing, this person is saying this thing there. Okay. You know, because I've got, you know, my wife is asking me questions about uh uh AI there. I've got friends and family or whatnot. And so I said, okay, let me start to put information together, uh, help them distill what are fundamental uh information that's not hype driven. Uh and coming from a place of, I'm not selling a course. Uh, you know, this is just I to be a responsible citizen, this is information that people should know when they want to understand this technology. And what I also realized is that to help mitigate the danger to not shoot yourself in the foot, uh I started to say, okay, what are the things that one should look out for when they're building the system there?

A Safety Framework For AI Rollouts

SPEAKER_01 39:28

Uh and so uh something I had uh done recently, uh released, is a framework that uh a professional, uh a business owner, uh team lead in a company can use to see where they are in the AI spectrum and to think about, and I try to distill it to four principles of what you should think about, regardless of what your industry is, yes, and the the particular, you know, whether you're using Claude, uh Chat GPT, you know, those are tools, but there should be a fundamental understanding of how to use those tools in a way that's responsible, that's safe, that gets you the results you need there, especially in a regulated industry there. You can't afford to improvise. No, when you're uh you need those checklists there. When you're flying a plane, you need to have precision systems there. And in fact, actually, uh where I actually based my framework from is uh uh aviation, aviation engineering metrics there. Because they can't afford to get it wrong, just like the medical field. We cannot afford to just okay, wing it there. Um, and so you know, those those what I would call disciplines are, you know, as you're building the system, you have to think about what can go wrong. And you have to now start to think about that sooner rather than later. AI will help you to execute a task faster, but there's a price, right? And the price is you now have to give yourself more time to think through what you want to do, you can't rush that part. And so the first question you have to ask is what can go wrong? And give yourself time to do that. And that's why you still have to know your business, you can't blindly do this there. And then second, you have to say, okay, if something goes wrong, who gets hurt and how badly uh there. And so and and this is why uh using regulated industries, uh using guidelines that need to be bulletproof, such as aviation, such as the medical field there, uh they look at what's the consequence of getting it wrong is. And that's the right approach when you're working with AI. Even if you're in an industry that isn't regulated, I really employ people to approach it with that mindset there. Because unlike other technology where you can continue to just check on it because you're using the technology, but you're always in the driver's seat. Now we're talking about handing something to someone else, like driving a self-driving car. If you're the one driving it, you can react, you can make adjustments there. But if you are now going to program something to drive the car for you, and the car is a wonderful tool, and it's also a dangerous tool if used incorrectly. So you have to be more thorough about take uh doing that kind of uh thought process there. Um and then I think the other thing too is unlike previous technologies that we've worked with, Grant, AI has errors that are very subtle. Uh if I got something wrong with uh my PowerPoint presentation, uh, or if I'm trying to go to a website that doesn't exist there, I'm just gonna get an error. I'm gonna, I mean, I understand what that error message is. Like, oh, okay, it's just, you know, hence that's why you call help desk. I get this weird thing. You know, my mother's calling me. It's not doing this thing. I have this weird message there. And that's fine. Okay, you've just stopped it there. But AI can give you errors. And it looks right. Yes.

SPEAKER_00 44:04

Yeah. I think a lot of people are that the hallucinate, or it believes its own hallucinations.

SPEAKER_01 44:10

Exactly.

SPEAKER_00 44:11

In a way that is very confident in its mistakes. Exactly.

SPEAKER_01 44:16

Exactly. And you know, as humans, we attach trust and competency to confidence. Yeah. And so, you know, these are signals that we have been, for generations, we've been conditioned to look towards the the confident has competence there. And sometimes that has bitten us because we know someone can sound confident and not to be completely AI is like that, but it's it's more accelerated.

SPEAKER_00 44:57

But we're getting toward the end of our interview, which is this has been enlightened. I want you to on this last piece, think through like a small business owner, right? They got three to five, you know, employees. They they see like, hey, we can act like a company that's uh you know 15 to 20, because now I can automate certain, and I'd say backend processes to your point. You have to understand where you need this technology deployed. You need to understand where is the friction in your business, what can you, you know uh take, take uh uh take that friction out, and it's gonna open up new opportunities for you. Now, you said something and I want I you really said something that I the audience has to understand. Because speed can be good and bad, acceleration, just like when you're driving a car. Sometimes it's great to be going 100 miles an hour, but not all the time. Sometimes you need to slow that thing down to 20 miles an hour, depending on the situation. So just because you can speed things up doesn't automatically mean that that's a good thing, right? So if your employees are operating at a certain uh capability, and that's a speed, right? It's a velocity. So your business runs at a certain velocity. So if you speed up certain aspects of what they're already doing, that's gonna throw that harmony off. And getting back to what you were saying earlier, if you don't take this through and articulate the price, sometimes you don't know what you don't know. Because, as Wilfred said, he is a pioneer, he's going out there and he's hacking through the forest. He stopped for us today, and we made a campfire out in his wilderness. He's like, okay, guys, you know, I'm gonna stop. But but but he knows this because you don't know, he doesn't know when he begins his journey again tomorrow what he may encounter. Because now your business has been running at a certain speed and velocity. You're about to change that speed and velocity by automating certain things potentially. And have you really gone through it? So, for a checklist, if you can give that small business owner, like, hey, look, and you gave us some of that, I I I need to get, you know, process my my AR better, accounts receivable, or I need to understand my customer better. What are the some of those things like here are the things I want you to do and do today before you go out into this wilderness, your own wilderness, and start chopping down the forest?

Systems Thinking For Small Businesses

SPEAKER_01 47:48

Right. Actually, that's a that's a great uh question there. I think equally as important as learning how to use the tool of AI, uh, I business owners and professionals are also going to have to really stretch their skills of systems thinking. But what do we mean by systems thinking? So when you talk about as a business owner, you have to slow down before you really dive into this tool. And I know it's tempting to type it into ChatGPT, it gives you some answers. Oh, I can start doing this right now. And then you copy and paste those answers into your email, your document, you send it out, and and things happen. And next thing you know, you're you're now knee deep in your chat thread, copying and pasting things and going through and oh, wait a minute, I have to go back because I didn't tell Chat GPT this other thing. And then that can affect the marketing campaign you're trying to put uh out there, uh, or this product you're trying to get there, or uh setting up this chat bot maybe to deal with your customers. You now have to be disciplined enough to take a step back and to think through, okay, what is my customer journey from start to finish? And you have to be as detailed as possible because this is where uh doing it too soon. Uh, I think it was Klarna that did it too soon. They're like, we're gonna fire all the human agents and then just replace it with AI agents there or whatnot. And that's a cautionary tale uh there is that they didn't think the decision makers did not engage enough with the people that do the day-to-day work to really understand what that means there, where the parts of your customer journey. So let's say you want to use AI to be able to answer customer calls there, uh, customer emails, customer calls. Okay, that's great. You now have to uh what are the questions that they ask? Uh, how are they going? How are you going to give them the answers? And what if they have something that's a little bit different than what you're expecting? And then when it especially when it comes to customer service, I personally don't want to remove all the humans from it. They just need to be placed at the right checkpoints in that customer journey and to really enhance that. So that's that's one of the prices is having the discipline and giving yourself the space to sit down and talk that through. And if you have a staff of two or three, they have to be part of the process there.

SPEAKER_02 50:42

Thank you.

SPEAKER_01 50:42

Uh that I can't to to have this is not a top-down uh endeavor. Uh, and if and I know there are a lot of think pieces and business articles that talk about, oh, you have to get it engaged and then you just give it lip service. The thing about AI is that it will cut through your BS. It will cut through your BS brochure marketing brochure there. Because you can say, oh, I talked to my uh I talked to my staff about it, and I really got their opinions and we've really incorporated there, but you really didn't. That's going to bubble up so fast. So you now have to do that work. That's where the work is. Uh, and and so systems thinking, uh, and they're gonna start throwing that. And then for those that are interested in learning AI and how do I get into this? Because that's an important thing too, uh, Grant and I have been talking about. And this is important to people who are on the fence about it there. I think more so than learning how ChatGPT works. Uh, and the more that you understand it, the better you'll be able to use the tool effectively because you know what it can and can't do. But to also be systems thinking, you don't just think about, I don't need to get this task done. You want to be able to look at someone's business or business you're interested in getting into or that you want to work for and think about how that business makes money, how it provides value to a customer. And to ask that, you have to have that level of curiosity and to ask all the different parts. It doesn't matter that you're just an accountant. Oh, I just or I just do accounts receivable, I just do this process there, or I'm in uh delivery fulfillment, that's all I do. No, you have to look at the whole process. Those who know how to ask uh those those who know how to think in that way, well, and Grant said something extremely important for everyone: the right questions. Because this really is all about the right questions, which is why you still have to know your discipline, you still have to know your business.

SPEAKER_00 53:07

Uh, and if you're an expert in what you do and you need to still be an expert, you're not you're not outsourcing your expertise in what you do. You that you want to enhance it, right? You want to enhance it. Exactly. Exactly the whole thing. Uh and we have to conclude here. And great, great answer. Great answer. And I want people to really dive into this more because you gave a knowledge library that you built out because you know people are starting as they go deeper and deeper into their own forest, so to speak, you've already built out some resources that they can start to understand and know how to drive this brief, this brand new Ferrari that we're gonna give to everybody, right? But you if you gotta know how you you gotta know how to operate it and think things through systems thinking. I love how you said that. I want to add on there, you have to understand critical thinking, you have to understand design thinking and analytical thinking. This is where we're coming up the stock. You can't just just information and data are gonna be their commodities, but what's going to be valuable is the context of those things that we're talking about. That makes your human world valuable. I'm gonna hire you because you have a domain expertise that you bring to the table, but then if we can AI enable that domain expertise, we're powerful at this point, right? Right. So, you know, you don't want a misfired robot, you know, operating in your in your shop.

SPEAKER_01 54:40

Exactly.

SPEAKER_00 54:41

Exactly. So how do they get um, first of all, how do they get in contact with you and how do they attain this type of knowledge library

Resources, Assessments, And Closing

SPEAKER_00 54:48

that you have?

SPEAKER_01 54:48

Sure. Uh the easiest way is uh so I put everything uh together into my website, and it is wilfredmorgan.com, W-I-L-F-R-E-D M-O-R-G-A-N.com. Uh there. And I have uh the articles there. Uh I even have a uh short five-minute test uh or an assessment uh tool to see where you are, and then based on the answers you give, uh, you know, it can give you uh your particular roadmap of okay, this is where you are uh in your AI journey. Uh, here's some recommended steps there uh or whatnot. And uh you'll be, and if you have any further questions there, I believe that the information that I'm providing should allow 95% of professionals and business owners to at least have a good starting point. That's you know, cut through all the hype. Uh and they're gonna get sound information that they should be able to run with there. And if if there are any questions uh or anything, uh I can be reached through through there as well, there or whatnot. This is just this is too important to just hoard this information. I think the more that people know, uh, it does two things. One, uh, the more that you learn how these systems work and to use it properly, we're gonna have better systems.

SPEAKER_02 56:16

Yeah.

SPEAKER_01 56:16

So we all benefit. The the better that people execute on this technology uplifts the world. And then two, and this is most important, it eliminates the fear that's happening of AI is gonna take jobs and AI is just gonna make things worse. And it's just everything is bad, bad, bad. And it puts people in a in a place of helplessness. Right. Uh, you know, fear and helplessness there. And I think, and that's wrong. Uh, and so it's for me having sharing this knowledge that's available to everyone and accessible to it.

SPEAKER_00 56:54

I understand it, it is a machine, it's a tool, it's a very powerful tool, but we have to know we have because it it this is one of those few technologies I would say that actually not only affects of itself the the technological area, but it affects the human cultural experience. That's a big thing. So that's where you know people get afraid, and it's like this is changing, you're moving, you're moving my rice bowl, right? Well, that is true. But if you know how to drive it, just like the internet changed a lot of lives. Mobile computing changed a lot of lives. All these things, yeah, as you say, it's it's gonna change. Yeah, it is gonna change, but you have control of what it changes into for you, right? And that's because you're familiar with it, you're not afraid of it, you understand what it does and doesn't do, and how to enhance your particular life. And you remember the environment around you is also utilizing it. You don't want to be the person that you know still got a slide rule, and everybody else has got you know a Texas instrumental calculator, right? So you need to know where this is sitting. I want to encourage your entire audience to see all our episodes and also go to my website at five starbdm.com. I have my AI bot there. I call it Sentinel. You want to learn more about branding, know more about marketing of itself. I have my AI bot there specifically for that reason to educate people along these lines so they understand it better. And this is where I think our are to your point, our systems will get better because we have better information and better knowledge about, oh, I now understand that better. This is going to be smoother instead of it being a quonky type situation. So I think over time this will be uh a better experience overall for the human population. So thank you again for being on the show, Wilfred, and we'll definitely catch up again.

SPEAKER_01 58:49

Yes, definitely. Grant, thank you for having me there.

SPEAKER_00 58:52

Welcome most welcome.

SPEAKER_01 58:54

Thank you.

SPEAKER_00 58:54

Bye bye.