Are You Ready for AI Adoption? AI Readiness With Tom Baker
Learn how AI readiness helps organizations align data, systems, teams, and strategy before launching sustainable technology adoption initiatives.
Learn how AI readiness helps organizations align data, systems, teams, and strategy before launching sustainable technology adoption initiatives.
Consulting Manager of Technical Advisory Services at Integrated Solutions Group (ISG)
Tom Baker is the Consulting Manager of Technical Advisory Services at Integrated Solutions Group (ISG), a consulting firm helping organizations execute complex transformation initiatives. In his role, Tom advises clients on data modernization, technical feasibility, enterprise strategy, and large‑scale transformation, guiding where and how AI can create measurable value while ensuring foundational systems, governance, and processes are in place for sustainable adoption. He helps organizations align strategy, talent, and technology to solve practical problems and improve operational outcomes.
In today’s rapidly evolving business landscape, organizations are feeling pressure to adopt new technologies at breakneck speed. Many are diving into AI initiatives without fully understanding their readiness or the long-term impact. How can companies ensure they implement tools that actually drive measurable value?
As a data modernization expert, Tom Baker explains that successful technology adoption begins with a strong foundation in data, systems, and processes. He emphasizes the importance of aligning people, infrastructure, and strategy before implementing AI, suggesting incremental approaches to modernization rather than attempting to solve everything at once. Tom offers practical guidance on identifying critical challenges, streamlining workflows, and establishing metrics to track improvements. By taking incremental steps, focusing on foundational systems, and engaging teams early, organizations can turn technology adoption into lasting operational improvements.
In this episode of Cyber Funnel, Thorn Compton sits down with Tom Baker, Consulting Manager at Integrated Solutions Group (ISG), to discuss why AI readiness is crucial, how to modernize legacy systems, and strategies for sustainable adoption. Tom shares insights on prioritizing key pain points, aligning teams, and measuring success. He also touches on mentorship, leadership, and avoiding common adoption pitfalls.
This episode is brought to you by Amplifyed.
Amplifyed is a specialized SEO agency, and we partner with in-house marketing teams to boost search visibility, drive qualified traffic, and turn organic search into real pipeline growth.
From technical SEO to content strategy, Amplifyed handles the heavy lifting so your team can stay focused on building and selling. If you want to show up when your buyers are searching, Amplifyed helps you get there.
To learn more, visit us at amplifyed.io.
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Intro: 00:02
Welcome to the Cyber Funnel podcast, brought to you by Amplifyed. Where we feature the top minds in cybersecurity.
Thorn Compton: 00:13
Welcome to the Cyber Funnel podcast, where we talk to some of the top minds around cyber security and marketing. I'm your host, Thorn Compton, and some of my great past conversations include Amplifyed owner Scott Johnson and digital marketing expertise and just extraordinaire Renee Haas from Redseal. Today, I have the pleasure to welcome Tom Baker, Data modernization expert, as we like to call him, into the cyber funnel. How are you today, Tom?
Tom Baker: 00:40
Good, Thorn. It's good to see you after so long, man.
Thorn Compton: 00:43
It is always good to see you, man. I'm real happy to have you on today. I've been really excited about this conversation.
Tom Baker: 00:48
Likewise my friend.
Thorn Compton: 00:49
Yeah, yeah. Hey, before we get going though, as always, I have to remind everybody that this episode is brought to you by Amplifyed the SEO and GEO agency for cybersecurity companies. Amplifyed serves cybersecurity marketing teams by driving more leads from Google and AI search. We handle all the heavy lifting and know the exact levers to pull to get you more sqls. Tom knows all about that.
As a former client, we really loved working with him. He you'll see from this like we love to work with great people that have great minds. Learn more at amplifyed.io. That's amplified.io. Alright, like I said, I have Tom Baker, data modernization expert, joining me today.
Tom really is deep in the world of AI adoption, data modernization, and I'm excited to get his take on the current landscape of AI and AI governance. So I hope you're ready for some good questions. Tom.
Tom Baker: 01:43
Ready, man? Expert. We'll unpack what expert means and what it doesn't mean here, but I'm excited nonetheless to just have a good conversation.
Thorn Compton: 01:52
I, I, you know, if we have to get into, you know, expert in like what you feel like is expert versus like, what actually is? We can totally get into that. You know, everybody has a little bit of what's the term? I'm, I'm looking for a place where you don't feel like you actually belong in the space that you're in.
Tom Baker: 02:08
Imposter syndrome.
Thorn Compton: 02:09
There we go. Imposter syndrome. And I'm just here to tell you that you're not an imposter. You're fantastic. Tom.
Tom Baker: 02:14
Thank you. Foreign.
Thorn Compton: 02:16
All right. Hey, man, I gotta hit you with a lightning round real quick, though. This is where if we had, you know, like, graphics and stuff like that, we'd go, but we don't. So we just do it with our mouth. All right, man, my first question for you, and I think I've asked you this before, but we're going to get it on record.
Are you a Doctor Who fan?
Tom Baker: 02:32
I know of Doctor Who because of my name.
Thorn Compton: 02:34
Because of your name? Yes.
Tom Baker: 02:36
I've only visited the wiki page because who hasn't looked up their name in Wikipedia?
Thorn Compton: 02:41
For those that don't know, is the fourth doctor in the Doctor Who franchise. He was a doctor back in the 70s, one of the longest running ones. He had a really iconic scarf he wore that was kind of like a patchwork scarf. And every single time I've been. I've known Tom for years, and every time I see his name, I'm just like, he's perfect.
Doctor Who fan name.
Tom Baker: 03:04
And it is not the first time you've asked me that.
Thorn Compton: 03:06
I didn't think so. But hey, you know what? It's the first time I've asked you on the podcast, so. Hey, we're going to roll that into, I think, I think a good transition into what did you want to be when you grew up?
Tom Baker: 03:18
At first, I wanted to be a pilot for many years. And when I was starting in ROTC for the Navy, I realized that pilots don't just get to fly around like in the movie Top Gun and do whatever they want. They actually have to follow plans. And that seemed a lot more boring than what I thought for like 12 years. So I changed my path.
Thorn Compton: 03:43
You know, I have to give you props though. You did at least do the hack of going to the Navy where they actually, like, weirdly have more planes than the Air Force does. They do. Yeah, yeah, that was so. So at least you understood the assignment on that end.
Tom Baker: 03:56
So yeah, I guess so. So it's funny, my mom was super shocked by that. She's like, you went to the Navy and didn't fly after all. I was like, well, that's how it goes.
Thorn Compton: 04:07
That's how it goes. You know, it's just like, it sounds boring. And there's other fun things to do there. So. Well, hey, what are you, a music guy?
And what was your first concert?
Tom Baker: 04:17
My first concert was Rush 2112 in Las Vegas as a 14-year-old with my best friend and his parents. And that's the genre of music I grew up with. My dad was always playing classic rock in the garage. My mom was like a hardcore 90s-era country fan. So yeah, it was like Reba McEntire or Rush at my house at all times.
Thorn Compton: 04:44
Would you, would you classify that as your favorite concert too, or do you have another one?
Tom Baker: 04:48
It's, but yeah, it's the, it's the best concert. I've wanted to see Metallica before they're off the road, right? They have a dome tour going on, ironically back in Las Vegas and like.
Thorn Compton: 04:57
Interesting.
Tom Baker: 04:58
Experience. Yeah. Yeah. But I can't swing it with a baby on the way, man.
Thorn Compton: 05:02
So dude, I, it was funny when we had our baby last year, we made a point of like, all right, we're going to go to concerts here in Kansas City. So we went to like 3 or 4 concerts. We went to, you know, some of the more modern and modern country ones. But yeah, like he, it feels like you have to squeeze things in. But then it's sometimes like you gotta get stuff ready.
So yeah, man, I'm so jealous. I'm a bassist. I also love Rush.
Tom Baker: 05:24
Yeah. Daddy Lee.
Thorn Compton: 05:25
Oh man. I'm it's fantastic. All right. Well, that's what blows out my next question. But we're just going to go into it either way, especially with like a baby moon kind of maybe on the horizon.
What is your preferred vacation destination?
Tom Baker: 05:40
Kauai hands down.
Thorn Compton: 05:42
Nice. So you're well, Hawaii's weird because you can get beaches and mountains in that, right? Yeah.
Tom Baker: 05:48
Kauai, the island, specifically the Hon Khoai Island, grew up in the Pacific Northwest, so we like the outdoors. We like hiking, the rainforest, and the trails. So, you know, that's Garden Island. And our second favorite is Maui. But Khoai is so compact, you know, you can get around Maui's Maui's big.
And so we keep returning. My second destination is Japan. And, you know, I, I was there for a couple of years in the Navy and just fell in love with the culture. And it's so different from everything we've got here in the West and clean, safe, amazing food. So if I have a runner-up, it's Japan.
Thorn Compton: 06:30
I could just go eat my way through Japan all day. Just give me all of the ramen that you can give us. Yeah, man. I'm okay, so we need to have a second, a second podcast about Japan and about the, the, the outline because I've been to Alaska as well and I need to get to Hawaii. Yeah, yeah.
So. All right. So cool. So, part two is coming up. All right.
Hey, man, let's get into the actual thing here. I'm really excited to hear your thoughts on this. I'm just going to kind of hit you with a big generic one at the beginning. What are your thoughts on the current state of AI and what it's doing to businesses right now?
Tom Baker: 07:07
Yeah, man, I was first exposed to this technology pressure problem while I was in the Navy and had a day job. But on the side, just, you know, there's a push in every industry, whether it's government or private, that whatever the next big thing is, I feel like it follows. There's a common pressure that if we don't adopt this, we're going to get left behind. And, and so I'm seeing that on such a massive scale. And that's, that's the way I feel like it's being marketed as well, is almost don't get left behind, be an early adopter.
So I think what that's doing to businesses is putting pressure on them. It's putting pressure on people to use it from the ground up at the operational level, for sure. And then obviously, maybe more for leadership, they're looking at it strategically and thinking. They're thinking in terms of threat dynamics for their competitors. If they don't adopt or or they're thinking pragmatically and just trying to apply it to specific solutions, you know, whatever that business is solving for.
So my thought on that is some of that pressure is healthy and positive. And that's what drives competition and innovation and good on the AI wave, right? You know, because if not, AI would be something else.
Thorn Compton: 08:32
Yeah, exactly.
Tom Baker: 08:33
Like the.com era, you know, that I was like in diapers for but, but the other side of that is I think it's, it's producing some unproductive effects as well. And. I am seeing, at least from my seat, you know, an adoption without readiness.
Thorn Compton: 08:54
Yeah.
Tom Baker: 08:54
So trying to slapstick the house up without letting the foundation, you know, even taking inventory of a foundation. What is a foundation? You know, data infra systems, cyber processes, people readiness, all those types of things, right?
Thorn Compton: 09:13
Yeah. When let's dive into it right at readiness anymore, a little bit more when you say AI readiness, like, what do you mean? And like adoption and that kind of stuff. Are we, are you talking about, you know, using AI internally? Is it, is it how you're storing your data? You know, explain that a little bit more.
Tom Baker: 09:30
Yeah. Well, so that's an interesting way that you frame that is interesting because there is an infrastructure way to look at readiness. And I think if, if I had three buckets, I would say it's your data. Number one, because every AI model out there is really just an algorithm looking back at a data set and using compute power and memory storage to produce, you know, a set of outputs based on conditions that you really help drive, especially if you're good at writing your prompts. Right?
So data is a big one and that's definitions, standards, data governance, you know, the management, the pipelines. I think the other one is like integration. So your systems abilities to talk between themselves and their overall connection is either an inhibitor or an incredible, like enabler for like an AI model. Right? So does the AI model have to look at 26 disparate systems because and again, I have data and all of those.
Or do I have this interconnected web that's really well managed and sequenced. And so Integration is like just one in itself. And then I think there's like a shared systems perspective.
Thorn Compton: 10:49
Okay.
Tom Baker: 10:50
Cloud. Cloud or DevSecOps pipelines and things like that. You know, those already reduce a lot of costs for businesses when they focus on shared services capabilities. I think it's more and more an imperative not only to move to the cloud, but to enable AI. Right?
So a lot of the principles that enable cloud enable, I think, readiness, if you will, around AI. So that's the infra side of the house. You know.
Thorn Compton: 11:18
That's it.
Tom Baker: 11:18
That's pipelaying. There's a people side of the house around AI readiness. That's super neglected. And man, that requires first and foremost, vision and leadership. Like anything that you set out to do at a company.
It's not just we're going to adopt AI. We're going to use AI for these specific applications in the same mindset that you build products to solve certain problems. I think getting people around that vision and getting everybody to swim in a singular direction, that would then require a certain type of orientation, a certain AI product adoption that fits that for you, right? Training. Right.
All of those. We're not talking about a lot of these concepts that have been around for hundreds of years in businesses.
Thorn Compton: 12:14
Exactly.
Tom Baker: 12:15
And, and so I think that people's side, though, is often neglected because, hey, we've got minimum data integration, shared services. Let's go. Right. And you're required to use the X AI system for the following work report.
Thorn Compton: 12:30
Right. Right. I love that you touched on training there because like so first shout out Scott Johnson because for a year and a half, Like we at Amplifyed have been really in on the like we're training, we're doing trainings, we're talking with people that are on the forefront of utilizing AI, how to utilize it to better do processes, how to utilize it to better do the, you know, the actual optimization side that we're worried about and how to better show up in front of those. But that's, that's time, that's effort that's putting in actual training. How much of the actual like making sure your workforce is ready to even have that change? How much does that play into it?
Tom Baker: 13:11
Yeah, yeah. And a lot of AI training that's out there is, is we are so early in this wave, the training that we can find, whether it's open source training or MOOC courses or, you know, Coursera, you name it is orienting you to what AI is and the types of opportunities that you could do with it. But for, for AI training to stick at your organization, you need to hone and create AI tooling that matches up to the product or service that you're delivering. Right. And that requires it.
It's like, wouldn't that require an investment of expertise before we brought it out to our people from the training team? And so that foundation, that's another foundation-laying component, right, is we need SMEs purely around AI flavor for our business before we can create the tailored training that dot dot, dot right enables success.
Thorn Compton: 14:09
Success. Absolutely. Yeah. You know, I think a quick little history lesson for those listening, if they didn't know this already, the internet actually was available before the 90s. It was just to the military. I find your military background really interesting because obviously you like the forefront of technology a lot of the time.
How did you get into AI? AI, you know, ready to space, really just this whole this whole space. What was your journey like and did it like, I know you mentioned it kind of even started back when you were in the Navy?
Tom Baker: 14:36
Yeah. Like, long story short, personal dabbling expanded out to more. Yeah. So in the Navy, it happened to be my first command at my ship. There were some brilliant people.
One, one of the men that I met, his name was Dave Nobles. And he pioneered this, this, this innovation program that we dubbed the Athena Project. The entire concept was to take innovations, ideas, areas for improvement from sailors, from the deck plates, the people actually turning the wrenches and, and working on those systems, right. And taking those all the way up to the developers, the engineers, the, the, the complex, if you will, that created it in the first place or, or could improve it. And, you know, they would never otherwise really have the opportunity to work through the military-industrial complex to voice, hey, this is really what I need.
And I think the fix is a $3 bolt rather.
Thorn Compton: 15:39
Then $1 million.
Tom Baker: 15:41
Improvement. That would take three years, right? It's so I thought of that idea that really sparked something for me. I was really privileged to like a partner on that and, and kind of help with facilitating some of the sessions and stuff. But that innovation mindset is where it started.
And that was sort of a pre-AI boom.
Thorn Compton: 16:02
Yeah.
Tom Baker: 16:02
We started to look at AI as a concept through data in the military, obviously, like on a naval ship with all those systems, you process huge quantities of data, a lot of algorithm coding complexity. And so that is where the seed was planted for me. And then when I started to get into consulting work, naturally, we have a pressure on the consulting side to learn while we are also delivering.
Thorn Compton: 16:31
Constantly.
Tom Baker: 16:32
Like we are having to absorb the same things that our clients are. And but they're paying us to get out in front of that for them and to absorb some of that risk and to advise. Right. There, there are best practices and things like that. And so I found AI to be a huge opportunity to start to deliver.
And, you know, I would put that analogy like today, like that's why I was laughing about the, the word expert is every day I feel like I go to work as, as a junior learner and so many of these concepts and then, you know, flip the head in a meeting and, and I'm trying to advise genuinely and truthfully and give the limitations of my knowledge, but also deliver something for my client that's valuable. And, you know, if that's not your AI journey anywhere, I feel like there's a little bit of smoke and mirrors happening, right? Because I work in an AI company, I feel like I am doing that.
Thorn Compton: 17:31
So it's so funny because that's like, that's kind of where we're at. Like Amplifyed is cybersecurity and we're experts. But the reason that we're experts in is because four years ago, five years ago, we just, we were doing SaaS and we kind of fell into some cybersecurity. And at the time, there was no, there were no experts. So we're kind of experts because we do it and because there's just not a lot of just in that niche, like there's not people that are specifically focused on helping cybersecurity, helping AI readiness, like, you know, governance, data governance, IT and that kind of stuff.
Specifically with, with, with, with SEO. There are a few, there's a few now. It's always fun being a trendsetter, but, you know, getting out in front of it is really interesting. I also love that you kind of touched on the dirty secret about LMS that they've actually been around for years. And it's just now getting into the public space where they're being where everybody sees the clouds in the chat and that kind of stuff.
You know, what are they saying? Like, obviously everybody knows about that. Everybody knows about, you know, kind of some other LMS and how they're being used to it. What are some other data, data modernization tactics or things going on that are a little lesser known?
Tom Baker: 18:37
Yeah. Well, I think there's a lift and shift trap. We are talking about not being ready to pick up and move data, whether you're picking it up and you're trying to migrate from on prem to the cloud. That's kind of a classic example.
Thorn Compton: 18:56
Yeah.
Tom Baker: 18:56
Or you're just trying to throw your data into an AI model. This lift and shift trap is that the technology will just auto solve what gritty foundation work really is still the, the best path for me to get that stuff figured out, right? That's the one. I think it has the biggest financial bite. I feel like vendors will not tell you that, right?
Thorn Compton: 19:19
Because yeah.
Tom Baker: 19:21
They love your problem set and they love to turn a feature set into kind of a magic pill. Solve for all your ailments. And there's an accountability and ownership journey in that. I would like to be ready, but can I soberingly state whether I am or not? And that in itself, I think, is a leadership capability.
That's the one that stands out. The other one for me is that we're not really seeing a technology problem. We're seeing failure to failure to agree on what modern means for a specific business. That's so, you know, a lot of organizations are buying platforms before they've been able to define the problem and cloud migrations that are supposed to take like 18 months on paper, they become these three year sagas again, because data quality and governance and things weren't addressed at first. And now we're having to parallel those with our infrastructure.
Thorn Compton: 20:28
Yeah, it seems to be a recurring theme in these discussions that that we've been having on this podcast, that understanding who you are, like a real snapshot of who you are at this moment is kind of the, it's the, it's the base point because you can't make yourself move forward if you don't know where you are, if you don't even know if you have wheels, you know, you can't miss a train. If there's no tracks laid, you know, fine, the train's going to get moving, but it's not going to go anywhere because there's no tracks actually moving.
Tom Baker: 20:56
Yeah, exactly. Yeah. And you know, on that Thorn, the other thing is like, do we understand ourselves what our capabilities are? But before we set out and this should be no secret, you know, but it's like you need to define success.
Thorn Compton: 21:12
Yeah, yeah.
Tom Baker: 21:13
You after solving for that's step one. The other classic piece that follows there is, are we going to be able to measure that to tell. Yeah. And so I think a lot of times I end up recommending taking an incremental approach. You know, I love the agile methodology.
I love lean process improvement. Just this concept of man AI is a big wave. My data problem set is humongous. Look, the most logical thing I can do with limited time and funds is to take a bite. And for that bite of that problem and the bite of the solution to be right-sized, measurable, and that also just allows me to get started without having that, that planning stall where I have to solve everything on paper.
Thorn Compton: 22:02
Again.
Tom Baker: 22:03
Something that the vendor would love is for you to look at your entire data set as a singular issue. And for them to bite it off as a singular solution. But that's, that's your, you're not limited to that, right? You can take logical bites down verticals, systems, and data elements that make sense to you.
Thorn Compton: 22:26
So say I'm okay. That leads me into this hypothetical. Say I'm a data manager for a state entity or something like that. With 20, 30 years of backlog data, I want to simplify this thing. I want to make this more modernized.
Am I screwed? Like what's what's the what's the plan of attack there?
Tom Baker: 22:48
Well, you're not screwed. I would say there are a lot of tools to identify hotspots, pains, problems and how big and little those things are relative to each other so that you can find your good places to start. One example is pointing to the eight waste model of six Sigma. So you gotta love the Japanese in coming up with methodologies that are tried and true. And I, I believe I read a book called Toyota that was recommended to me by a line coach, Holly Valkama. She was outstanding and explained that, you know, lean was born in a factory and it was really a Toyota born way of thinking.
And they were looking at everything in terms of efficiency, of course, but also through the lens of pain. So if you're that data manager and you've had tenure at an organization that long, chances are if we put a piece of paper in front of you, you would scratch out pain pretty passionately. And you know, you need more paper, right? Like, and those are super logical places to start. You don't need sophisticated tools.
You can, you can run assessments. I think those are great validators though.
Thorn Compton: 24:03
Right through.
Tom Baker: 24:04
Certain lenses are to run assessments and say, oh, let's quantify.
Thorn Compton: 24:08
Right?
Tom Baker: 24:09
But people know, man, I mean, people know where the pain in the business is. And that usually relates to problems like data problems, systems, issues. I have a spreadsheet because I don't trust this system. Right? This thing works better for me.
Why? So does that answer that? That question?
Thorn Compton: 24:28
It 100% did. And it leads me into another one, which I think is a great thing with, you know, you displaying so much expertise which you have on this, which anybody listening to this is like, wow, this guy knows what he's talking about. So this is an expert. So there we go. We've defined what an expert is.
Tom, who has helped you along the way? Who are maybe some mentors and some good pieces of advice that you've gotten, you know, on this journey?
Tom Baker: 24:51
Well, some key mentors I've had people like Sultan Baig at ChangeAnalytics, who I know you know well, Thorn.
Thorn Compton: 25:02
He's great.
Tom Baker: 25:03
A great brain in the space who can work between the tech and the people side of an organization. And man, what an incredible skill to be able to digitize.
Thorn Compton: 25:14
Yeah.
Tom Baker: 25:15
People's change pains.
Thorn Compton: 25:16
Yes.
Tom Baker: 25:17
What he can do is transform pain into code to solve for things, right? If we could all do that, I think we'd find success in our career.
Thorn Compton: 25:25
Yeah. Not a skill I own.
Tom Baker: 25:27
Yeah. So Sultan, you know, Beth Montag, Schmalz and Kim Bailey. A couple of owners along with like Jenna Train and Aaron Daley and others, were also leaders at 71 & Change who just built one of the greatest people practices that I've ever been a part of. And the change management methodology that no matter what type of flavor of project, whether it was at an apparel company or like an energy organization, to be able to apply a change methodology and let it chameleon into any type of business is just an awesome trade. I mentioned Dave Nobles back in the military. I believe that he's over at Microsoft now.
Thorn Compton: 26:13
Oh, fabulous.
Tom Baker: 26:14
Right. But while in the Navy, somebody who can operate as a military officer, which would be a metaphor for you have a day job at X Department and be able to carve out the time and the grind and the passion and the the networking and diplomacy that's needed to like start an idea and ideation lab and sell it to leadership, get it formalized by the secretary of the Navy, which he did. So those are people that come to mind, you know, is, is to your point, maybe I've had some incredible pillars of people along the way. And every time I've hit one of them, it's like getting smashed with a fire hose right in your face.
Thorn Compton: 26:58
Yeah. Not only speed.
Tom Baker: 27:00
And expectation that they operate, but like such, such optimistic ways of looking at the world, right, in these business problems and, and twisting it into, wait, there's an opportunity here because, because that's really what it is.
Thorn Compton: 27:15
That's that's so funny because it's, it's really interesting how it does feel like it's, it's, it is a people thing almost first, like you can kind of teach yourself some of this other stuff, but like you, you kind of are on the mentor side, like a little bit of an amalgamation of all the people that have made you like some of the editors I've had, like Ross over at the Marshalltown Times Republican, and, you know, people like that have really, you know, determined who I who I kind of am in a business space, even though they don't know what they don't know SEO, they don't know it doesn't matter because they shaped you as a human. And that's, that's beautiful. I love that. Hey, this has been amazing. I've loved having you on, man. I've actually got one last question for you. If you need to find Tom, find him on, on, on LinkedIn, there's going to be a thousand other Tom Baker's on there. But you know, he's, he's, he's, he's fantastic.
He's out there. My last question for you is, what is one mistake that any business is making right now when they're going into the AI adoption side.
Tom Baker: 28:16
One mistake.
Thorn Compton: 28:17
That. The main mistake, maybe.
Tom Baker: 28:19
Yeah, I think it is. I think it is adopting without asking your people first. And the asking is a series of questions which requires a genuine interest in what they think about what you're setting out to do. They probably also have some incredible ideas of the actual application to save you some time and money. And I think businesses are over-procuring out of a fear of being left behind.
Thorn Compton: 28:48
Yeah.
Tom Baker: 28:48
Without mapping it to the things that made them a successful business up to that date. Right. I know I'm generalizing that, Thorn, but I think that is what we're seeing everywhere. I feel the personal version of that same pressure. Right?
Thorn Compton: 29:03
Yeah.
Tom Baker: 29:03
Right.
Thorn Compton: 29:04
Yep.
Tom Baker: 29:05
And so, you know, if there's an opportunity for a quick flip on that, I would just say, you know, there's a readiness journey. It doesn't mean that you can't purchase or start trying something right away. It's just that you need to parallel that readiness as you take bite, bite sizes of the AI journey, right? And let it grow like you would any other capability. I think that's the Tom version of that.
Thorn Compton: 29:32
At least we are staring at one giant AI elephant right now. And how do you eat that elephant? One bite at a time, one bite at a time. Hey, Tom, this has been amazing. Thank you so much for joining us.
You've been spit out the cyber funnel. You're you, you, you still have your clothes on. You're all, you're a good man. So I appreciate you, brother. And we'll talk to you next time.
Tom Baker: 29:55
Yeah, we'll talk to you. I'll be in touch. Thank you.
Outro: 29:57
Thank you for listening to the Cyber Funnel podcast. Tune in next time for more tips and insights. And be sure to click subscribe for future episode updates.
