Adopting AI Without the Overwhelm

AI is moving fast—and for many businesses, that speed feels more paralyzing than empowering. In a recent episode of Avidly Talks, Paul is joined by Mike Kaput, Chief Content Officer at Marketing AI Institute and host of The AI Show, to explore how marketers can cut through the noise and adopt AI with confidence. They unpack the difference between automation and true AI, share practical use cases for marketing teams, and offer a roadmap for leaders trying to drive company-wide adoption. If you’ve been feeling behind—or unsure where to start—this conversation offers clarity, strategy, and momentum. Let’s dive in.

Listen to the Full Episode here

Listen on Spotify

Takeaways from this episode:

• AI has been a field of study for decades, but generative AI has recently catalyzed its popularity.
• Many people still confuse automation with true AI capabilities.
• AI literacy is crucial for effective adoption across organizations.
• Practical use cases for AI can significantly improve marketing efficiency.
• AI can act as a strategic partner in real-time decision-making.
• Overcoming barriers to AI adoption requires awareness and education.
• A bottom-up approach can lead to successful AI implementation.
• Real-world examples show the tangible benefits of AI tools.
• Leaders should focus on a few key areas to drive AI integration.
• Feeling overwhelmed by AI is common, and leaders should prioritize manageable steps.

Chapters 

00:00 Introduction to Content and AI
02:33 The Evolution of AI in Marketing
05:23 Understanding AI Agents vs Automation
08:18 Adoption of AI in Business
11:30 Exploring Practical AI Use Cases
14:31 Strategic Mindset in AI Utilization
17:25 Company-Wide AI Literacy
20:34 Real-World Examples of AI Implementation
23:36 Advice for Leaders on AI Adoption
28:37 outro

Making AI Work for You: Insights from Mike Kaput on Smart Adoption Strategies

Artificial Intelligence is everywhere—but that doesn’t mean it’s easy to implement. For many marketers, the hardest part isn’t the technology itself—it’s getting their team to actually use it. In this episode of Avidly Talks, Paul sits down with Mike Kaput, Chief Content Officer at Marketing AI Institute and host of The AI Show, to unpack how businesses can move past the AI overwhelm and start using it to drive real value.

Whether you’re stuck figuring out where to begin, or you’ve tried integrating AI but it’s not sticking, this conversation offers clarity, direction, and practical strategies to move forward with confidence.

1. Why AI Adoption Is Hard (and What to Do About It)

Most companies aren't failing at AI because they lack tools—they're struggling because adoption isn’t prioritized or understood across the business. Mike highlights that real adoption requires leadership buy-in, cross-functional education, and a clear sense of where AI fits into current workflows.

Key Insight: “You can’t just hand people a tool and expect results. AI adoption is as much a culture shift as it is a technical one.”

2. Automation vs. AI Agents: Know the Difference

A big misconception? That AI is just another name for automation. Mike explains the critical difference: while automation follows predefined rules, AI agents learn, adapt, and make decisions. Knowing which use case fits which tool is the first step toward smarter implementation.

3. AI in Marketing: Practical Use Cases That Work

Mike shares several ways marketers are already seeing ROI from AI tools:

• Content Creation: Speeding up ideation, drafting, and editing workflows

• Customer Journeys: Personalising touchpoints at scale

• Campaign Testing: Quickly generating variations and optimizing performance

4. AI Literacy Is the New Digital Literacy

If only a handful of people in your org understand AI, you’ve got a problem. Mike emphasizes the importance of democratizing AI understanding—not just at the leadership level, but across every team. This includes training, experimentation, and safe spaces for trial and error.

5. Feeling Overwhelmed? Start Here.

Mike’s advice for leaders struggling to keep up:

• Don’t try to master everything—pick one high-impact area.

• Identify repetitive, time-consuming tasks and explore AI tools to support them.

• Foster curiosity. Encourage teams to test, learn, and iterate.

"You don’t need a PhD to use AI. You just need the right mindset—and a plan."

Conclusion: AI Isn’t Just the Future—it’s the Now
AI isn't a passing trend—it’s rapidly becoming the backbone of modern marketing. But successful adoption doesn’t happen by accident. It takes strategic thinking, clear communication, and a willingness to learn. This episode with Mike Kaput is a must-listen for any marketer or business leader who wants to go from feeling behind to confidently leading the AI conversation.

Ready to turn AI from an idea into action? Let’s go.

Transcript:

 Paul: So welcome Mike. I'm joined by Mike, kaput in this, I just saying your last name, sorry. I should have checked. cool.

Mike Kaput (00:48.206)
Right, right.

Mike Kaput (00:55.46)
Kaput, yeah, just like the word, yep.

Paul (00:57.624)
Sorry, I should have checked that before we hit record. And you're joining me this week to talk all about content and AI because of your role as Chief Content Officer at Marketing AI Institute. And you're the co-author of Marketing Artificial Intelligence and co-host of the AI Show podcast. Welcome. So talk us through your setup at that end. If you're watching on video, you can see it's very prompt.

Mike Kaput (01:00.974)
Thank

Mike Kaput (01:16.6)
Thank you so much for having me, Paul.

Mike Kaput (01:22.542)
you

Well, we are we're back in the office quite a bit more these days, which we're all very happy about. Actually, we've been we're in Cleveland, Ohio, actually. So I've got a nice view of the city behind or in front of me at the stage of our baseball stadium. So, yeah, it's we have a nice little office downtown that we've been going back into more and more as we've kind of hired new people. So I'm in one of our kind of conference slash recording, informal recording studios here at the office and just headphones.

Paul (01:30.06)
And where's that? Cool.

Mike Kaput (01:53.165)
and you know our nice little riverside set up here.

Paul (01:55.82)
Nice. I've moved out into the open office today. There's nobody in. The sun's out. It's Friday. In the UK, we finish early on a Friday and the sun's out. So yeah, there's only me in this afternoon. So I thought, I'll just do it here. So normally I'm locked in a little room like you're doing. Baseball stadiums. Right. I love baseball stadiums. The shape, the steep stands. Yeah.

Mike Kaput (01:58.787)
Yeah.

Mike Kaput (02:02.69)
You

Mike Kaput (02:10.084)
I love that.

Yes.

Mike Kaput (02:24.522)
It's so cool because like you can't obviously see it from here, but we can almost see right into it. So if there was a game going on right now, we often forget like every time someone hits a home run, they shoot off fireworks, which sound like they're right there. So it's always pretty, it's exciting because it feels like a lot of energy, lot of dynamism. But also if you're on a call, you've got to be like, they just scored. I'm going to mute for a second, but it's a little too early here for a game right now.

Paul (02:39.672)
Because they are.

Paul (02:48.568)
So who's the team and how good are they?

Mike Kaput (02:53.782)
The Cleveland Guardians, they're okay. I don't follow baseball super closely, but we're not as bad as our football team has been. So I think it's a good time to be a baseball or a basketball fan in Cleveland. Football is a little iffier.

Paul (03:01.144)
Mm.

Paul (03:10.646)
Yeah, well, I know a little bit about NFL. So yeah, I know where you're coming from. And I play the original version of baseball cricket. So yeah, so I do like baseball. I'm lucky to go once when we're in Boston. So you're obviously going to be talking about content and AI. This is part of an ongoing.

Mike Kaput (03:12.792)
Hehehehe. Hehehehe.

Mike Kaput (03:18.86)
Yes. Nice.

Paul (03:33.94)
series really we're looking at AI in marketing and inbound marketing inbound sales and customer service and we're talking about it in a way of like using technology and doing inbound in the industry 4.0 world and first topic to discuss with you is understanding the evolution of AI in marketing. Obviously we all know chat gbt exploded into the mainstream but

AI has been around in other industries in the past. We've all been using it unknowingly. Wasn't called AI when we were using features on our laptop and things like that. Why has it suddenly become so popular apart from ChapGBT? Because there were other tools. What do you think has made it so prevalent?

Mike Kaput (04:22.542)
Yeah, that's a really good question. think there's a few or at least a couple factors maybe coming together. So like you said, we've absolutely had, mean, AI as a field of study has been around for 70, 80 years, at least in theory, since way back in the 50s. So the term artificial intelligence was coined sometime, I think like maybe the mid 50s. So we obviously didn't have anything resembling the systems we have today back then. But in theory, there's always been this idea that, maybe

using some configuration of machines, can start, you know, quote unquote, simulating how humans go through thought patterns and reach conclusions. Right. So, but even in our lifetimes in the last two, three decades, there have been forms of artificial intelligence and most of them have been, as far as I can tell on the consumer side and for businesses, predictive, right? You feed in a bunch of data, it applies some type of machine learning algorithms or other types of statistical

methods to hopefully use historical data to make future predictions with some degree of accuracy. Now, not always the best accuracy in the world, but that's what we're trying to do. So a good example of this is, you know, for two decades, we've been using AI in the form of Amazon, Amazon product recommendations. This has been AI since before anyone was talking about AI and marketing. The big shift and chat GPT is the thing that kind of

Catalyzed this has been I think generative AI. So anytime we talk about AI pre let's say 2022 or so You're almost certainly dealing with some type of predictive AI. Nothing wrong with that can be super powerful But that's what it was much harder to deploy much harder to actually use within businesses and especially for consumers unless it was baked into something like Amazon So even though you were using it a lot, I don't think you were really thinking about using it and

Now that we have this whole generative AI. Yeah, exactly. Yeah. And honestly, if you go back, yeah, I wonder how much of our references to algorithms were just, yeah, what we would just call AI now. Exactly.

Paul (06:21.65)
We just called it the algorithms.

Paul (06:31.096)
what we now call AI. I was at an event last week and it was hosted by Andrew Beldeen. He was actually long career at Microsoft. He was, he shared that he was the guy, do you remember the Microsoft Clippy? The little, he's the guy who wrote that. And he was talking about how a lot of the things we call AI aren't AI, they're just automation.

Mike Kaput (06:44.126)
Mm-hmm. No kidding.

Mike Kaput (06:53.974)
Yes, well, you're seeing that already.

Paul (06:54.582)
So it's funny, like years ago we were calling AI algorithm and now we're calling automation AI.

Mike Kaput (07:01.876)
Yeah, we're seeing the next phase of that where a lot of people are trying to call automation or other forms of AI, AI agents right now, you know? the cycle continues for better or for worse.

Paul (07:09.42)
Hmm.

Paul (07:12.778)
Interesting. Tell you what, let's jump into that then, because we've just recorded a podcast about some big releases recently from HubSpot. We're a HubSpot partner. I know how familiar you are with the platform.

Mike Kaput (07:26.7)
Yeah, we run on HubSpot. So while I'm, you know, very, very familiar with it, I'm not as familiar with all the, say sales and customer service applications, because I'm not in that day in day out, but our entire company runs on HubSpot. Yeah. Right.

Paul (07:38.914)
So content agent then, so that's one we know. It's one I always hark back to with my background as well. But so yeah, talk me through then this agent set up because there's.

Mike Kaput (07:48.311)
Yeah, I think, I guess at a high level, at least today, I think the thing we kind of talk a lot about with marketers is, you know, AI agents are absolutely a thing. There are AI agents out there that are starting to be really interesting, really impressive, but there's also a lot of confusion because everyone is trying to put the label agent on stuff that often looks a little more like automation. Now there's nothing wrong with automation.

But if it's following like a workflow of a series of steps that are mostly predefined by human or using kind of basic conversational AI, there's nothing wrong with any of that. But I would say where we're starting to see really true agentic stuff is in like OpenAI and Google's deep research tool. O3, the new AI model from OpenAI is also somewhat agentic in the sense of being able to start.

deciding on its own which steps to take and then go take those steps. Obviously OpenAI has Operator too, which is we'll go use a web browser for you. That's really where I would see us going with AI agents and all of these tools for anyone that's used them, they're incredible. They're very, very cool. You can get a lot of value out of them, but it's still so early. So I'm always a little skeptical if someone says, hey, we have an AI agent that does A, B or C for you all together without you doing anything in marketing.

I'm not entirely sold where they're yet, this moves so fast. We very well could be soon.

Paul (09:21.592)
And where are people's heads at when you speak to, know, either not just your colleagues, you speak to people outside of our bubble, outside of like the digital marketing bubble even, never mind the AI adoption bubble.

Mike Kaput (09:34.476)
Yes.

It continually amazes me personally because I think within our, it's really hard for one to get out of any of these bubbles because I tend to think like I'm behind all the time reading about all this stuff and trying to work in this space. But when you talk to your average person, even your average very savvy, I don't know, business leader, everyone is talking about and hearing about AI, but it's still so early.

in terms of what they actually think those terms mean, terms around AI, around AI agents, in terms of what they think these things are capable of. That's often a big thing I see is like when the chat GPT moment hit, obviously everyone's reaching out, talking about AI, your average person had no interest in this stuff. It's on their radar. But then you talk to them today and they're like, yeah, like I've used chat GPT a year ago. It was cool. I don't really know where we go from here. It's like, well, no, no, no, no. Like the last year has been

a year you probably don't want to miss. So I think that really is where I find the majority of people outside our bubble is they are now aware of it. A few are really getting forward thinking about it, but the vast majority understand it might be important, but are a little scared of it, a little too busy to figure out how to adopt it. And also primarily just don't really truly understand.

how far we've come in the last 12 to 18 months.

Paul (11:08.536)
Yeah, whenever, yeah. I was in an office recently and the IT guy came, the third party IT guy came to get a printer onto the wifi or whatever he was doing, I don't know.

and he mentioned on his way out when he saw somebody's email screen, said, by the way, you know that, is it Windows 10, it's been sunset in September, you'll need to move then. And he was like, okay, this is where he's their IT provider. And that's where a lot of people's heads are at in of just adoption, awareness and education. But then it's weird, isn't it? Because at the same time, we're getting AI overviews forced onto us when we...

Mike Kaput (11:31.586)
Yeah, right.

Mike Kaput (11:49.612)
Right.

Paul (11:50.622)
was Siri intelligence and it's real. How do you see that sort of paradox that's happening?

Mike Kaput (11:57.773)
Well, it's a, this is such a cliche quote at this point, but as a big sci-fi fan, the sci-fi author, William Gibson, said something to the effect of the future's already here. It's just not evenly distributed. and like the, said that 30, 40 years ago, mostly in relation to the internet. I feel the exact same way about AI. it depends, especially even I go into industry events and do talks and like, you could have someone in that room that literally has.

done more, 10x more than I ever will with AI, you could have someone that doesn't even know what the term means. It's so different. And the industry as a whole is moving much faster, much forward, much more. Like we're making really good progress in my opinion. But your individual business person, business leader, whether in marketing or not, it is a total toss up where they might be today.

Paul (12:52.896)
I was amazed at somebody I arrived at the event with last week talking in the lift, in the elevator, and introduced themselves, not sure, I've got my head around it, I'm struggling to find the time to get to know how to use it properly and that kind of thing. Then we had the talk with the guy I mentioned and he talked about Google and think Amazon as well building nuclear power plants to power their data centers. Data centers as big as

the second biggest city in the UK. And then on the way out, I was like, how did you find it? she's like, nah, I just can't see it really catching on. I'm like, you've literally just heard about them building nuclear reactors, nuclear power plants to, yeah. It's just like, there's a resistance, there's people who have gone full steam ahead and using it too much. So that takes us onto the next topic. beyond chat GBT and proofreading my emails and.

Mike Kaput (13:28.29)
Ha ha ha ha ha ha ha ha ha ha

Paul (13:49.452)
helping me take notes in a meeting, these are quite common tools. Apart from generative AI and note takers and things, what are other things that people could be exploring that are pretty easy use cases that they can go and implement that you think of from a marketing AI?

Mike Kaput (14:06.038)
Yeah, so I'll focus in on one or two that I think are extremely high ROI if you're not really going down the rabbit hole with them. And the biggest one would be, I guess, for lack of a scientific term here, AI as a strategic assistant. So.

We see a lot of people are really rushing forward in a great way with all sorts of use cases for AI and marketing, doing all these one-off things that they do as part of their job, getting better at doing them, producing better work.

where AI is really starting to shine for us especially is acting as an in real time as a thought partner. So we will literally fire up, especially with how good some of the recent models have gotten like something like 03 will be fired up on a screen during a meeting and we will be actively.

not only recording what we're saying and using that material in different ways later with the model, but also we'll be working in real time with the model to game out different strategic scenarios, figure out answers to really tough questions and figure out very high level topics and approaches in our business and in our marketing. So to make that really tangible, I think every single person out there would be really well benefited by spending, and it would take you 10 minutes probably.

spin up just a custom GPT that acts as your co-pilot in your role. So as an example, I have a co-

Paul (15:37.048)
Sorry, Mike, an education point of view though, like that sounds really complex.

Mike Kaput (15:43.299)
That's fair. And I would encourage you to fire up custom GPTs and see very quickly how not complex it is. Because yeah, that's a good point. Because we do use the language, go build a GPT, right? That's typically how you'd refer to it. But really what I'm talking about is you're opening a window describing in natural language or with a pre-created prompt that you've just written out what you would like a custom version of ChatGPT to do. You copy and paste that into a window. You hit Save.

You grab the link, you start playing around with it, and you make tweaks to it. So it is tempting to start thinking like, my gosh, this is going to be so hard to do. Trust me, I am not a programmer. I'm not someone that's like building AI from scratch here. You can go build a custom GPT as long as you know how to type.

Paul (16:32.919)
And

Mike Kaput (16:33.678)
So given that, would say, like for instance, I have a GPT that's a co-chief content officer GPT. All it is is it's basically been prompted with a few paragraphs to say like, here's what I need you to do. You need to be a strategic partner to me. Here are very top line KPIs I'm responsible for. Here's my job description. Let's go. That's pasted into a custom GPT. It's saved, so I never have to copy and paste the prompt in again.

And then that is on my bookmark bar here, ready to help anytime I need help. You can do this for any use case you have, but I think one for your overall job is really, really helpful. Or using something like one of the more robust reasoning models, again, like 03 Gemini 2.5 Pro, with prompts to say, we're not just gonna go write email copy. We're not just going to go brainstorm headlines.

I need to think about this quarter. need to think about this year. I need to think about high level strategy. Let's work together on that for the next few hours.

Paul (17:36.524)
What's the, obviously it's a rough estimate, but what's the sort of blocker, do you think, for people to move away from just doing point solutions like landing page copy or headline drafting or proofreading my emails to switch into that strategic mindset?

Mike Kaput (17:53.577)
Yeah, that's a really good question. It's something I don't have a perfect answer to because I think we're still trying to figure it out. But I think at a very high level, first they have to be aware of what's possible in the first place. So whether so many people don't even get to the landing page copy phase, right? They don't even know how do I prompt this effectively to get really good output. So there's that. That's a whole other scenario, right? Where people don't even know how to get.

really good structured outputs from these tools for something very simple. So simply awareness of how to do that, what these tools can do. And then I do think you need to see what you'd like, know what you don't know, right? Cause some of these people sitting here might not realize that you can go have a two hour conversation with a reasoning model at a very high strategic level and get outputs that are as good as someone with 10, 20 years of experience. like,

you have to understand that's even possible in the first place. So obviously listening to conversations like this is really helpful, like getting different perspectives. So I always try in what we do, where I can to show as much as I tell, like just show people and especially in like LinkedIn where I post a fair amount, I could just try to say like, hey, here's a workflow I've used that's really helpful. You might want to explore it. It's just giving people as many ideas as possible because then from there,

You kind of just want to take that and run with it on your own and start experimenting in the context of your own work with how to get the best result.

Paul (19:24.554)
Imagine if somebody is, like you say, listening to conversations like this. They're obviously wanting to learn. They're obviously trying to improve themselves. That's the whole point of the podcast. That's why we get people like yourself on to pass on that knowledge. So.

They're probably then internally at their company at least, especially if they're in-house, at the forefront of adopting these technologies. So let's talk about managing that change into the business and going from you might be spearheading this usage or learning it for yourself because you can see the opportunity for improvements and efficiencies. But how do you get company-wide adoption? How can you effectively communicate, perhaps as a leader, the value and...

stop myself saying the word urgency because you can get tricked into it being like, just taking our jobs. There'll be no marketing roles left in a year, but the will. But you know, another classic quote already is just AI won't replace your job. Somebody using AI will. So how do people, or how do you help people adopt this change?

Mike Kaput (20:32.514)
Yeah, it's a complex topic. We've literally got entire courses on this at a marketing AI Institute. I will say where we start and where you need to really heavily invest, we would argue, and that people don't do enough, is the concept of company-wide AI literacy. So what I mean by that is, again, kind of back to the future is here, it's unevenly distributed. There's very likely, especially at a big company, we work with a ton of them, there's very likely some

people who are really at the forefront of AI. There's likely a lot of people that have no idea that your company is doing anything with AI and don't know what they're supposed to be doing. And then there's also probably a huge amount of people that are afraid of it or don't understand it or want nothing to do with it. Everyone, everyone in the company is at these different phases. So we always start with the first and most important step is general AI literacy. This cannot just be

A handful of executives who are really keen on AI pushing just from the top down, that's important. But it also has to be bottom up in terms of people actually understanding no matter what their role is, what their seniority is, what their function is, what AI is, what it means for their particular role, and how they can quickly and easily and in a responsible way within the company's policies get started with the technology. That's not the whole ball game.

but that is like the price of admission, I would say, because if you try to do all the other stuff, like forming AI councils, creating AI policies, getting the best, shiniest technology, that's all great. Building AI roadmaps and strategies, fantastic. But if at the end of the day, 85 % of your company still has no idea how they're actually supposed to be using these tools or how they're relevant to their job, if they don't know how to do it for themselves at least a little bit,

you are going to run into enormous problems.

Paul (22:33.144)
It's very true. you any examples of companies you've successfully transition?

Mike Kaput (22:38.542)
Yeah, I can't mention names, but I can give an example of a recent very large enterprise we worked with. This is a very small but powerful example. They have for years purchased AI technology. They have done work with us, with others on forming long-term AI plans. All of this stuff was great. They've done educational workshops. They've attended events. They've bought courses. This is still all very fantastic. But one of the most impactful things we also helped them with was

taking a small team that had access to all those resources and tools and weren't getting as much value as they could out of them and sitting down and saying, we did a very small pilot with building GPTs. Well, you said, look, you have all these other resources. You have all this other AI education to do. That's great. But how about we show you how to use GPTs in your own job, how to build them for yourself.

Here's a few examples we built after talking with your leaders about what's most important to get done. And then we just turned them loose for a couple months. I gave them training on how to do it, but it was nothing super expensive. And it was night and day. Like people who previously were like, yeah, we've kind of dabbled with AI or like, we're not really doing what we should be doing with it. Night and day, we're now super excited about it. They were building their own tools. They were capturing pretty significant efficiency.

and performance gains because they knew that they know their job better than I do, better than any of us do, better than a vendor does. So we gave them the tools to be able to solve their own problems. And so that kind of ground up approach, again, it's not the only piece of it. All the other infrastructure needed to be in place. But the ground up approach had incredible results at the individual level for these people. So we actually sent out surveys about what they're using it for.

Paul (24:24.78)
How did you measure it? What were the results?

Mike Kaput (24:32.408)
how, what, if they had to, you know, it always gets a bit subjective because you have to ask, hey, can you quantify some of the benefits here? And you know, it wasn't all just hours saved though. That was a significant amount. There were more than one person saving easily a dozen hours a month, if not more on certain tasks, which was good. Well, some of them had quite a bit more. lot of the, well.

Paul (24:52.034)
So some of it's qualitative then, or perhaps ENPS data, or.

Mike Kaput (24:56.14)
I think qualitative is really important because on this survey, for instance, this was totally unprompted, simply asked like, can you share with us some of the benefits, if any, of the GPTs you built? Some of the qualitative responses I think would be really valuable for people teaching and selling AI technology to understand. They were comments like, I'm so relieved because this is work that now I don't have to do on a weekend that I typically used to have to do.

I'm, someone literally said, I am geeked out exploring what's possible here. I have like a creative spark in my work again. Like these are intangible surely, but deeply important to how to get people actually bought in to AI and like making it relevant to them, giving them the tools to help themselves, I think was key here.

Paul (25:50.254)
What did they do differently? Was it the bottom-up approach?

Mike Kaput (25:53.455)
Yeah, I think it was just simply focusing on one thing instead of this big picture. AI is going to change everything. Here's how you need to reinvent and transform your career. Again, all of that's important. We teach that type of thing. But then really drilling into saying, OK, look, here's a tool that anyone can use. Any single person, again, can build a GPT. don't even, I now even hate to use the word build. Anyone can spin up a GPT in like two minutes.

It takes a lot of iteration and effort after that to get it really right, but just giving them baseline education. Here's the tool, here's access to it, here's how to get some results out of it, here's what I would start considering using it for. Keeping them focused on that, and it took way more time than you might want it to. Keeping them focused on that and that one single outcome and then letting them experiment from there was key.

Paul (26:45.696)
Nice, because we're all adults, aren't we, at the end of the day? We're all professionals who are trusted with emails and work phones. So last thing then, what's your number one piece of advice for leaders who are perhaps feeling overwhelmed by this challenge and how to tackle it?

Mike Kaput (26:49.965)
Yes.

Right.

Mike Kaput (27:01.582)
Yeah, that's a good question because I also feel overwhelmed sometimes so you're not alone

Paul (27:05.622)
Well, you know what, when you, yeah, exactly. When you were talking then it made me think, if you think you're not keeping up with AI, everybody who uses AI tools says that.

Mike Kaput (27:18.776)
So true. So true. So that would be the first piece of advice is understand you are not alone. You may not be where you want to be. You may very well need to spend more time or a little more urgency on it. Okay, that's fine. That's like we all struggle with that. So I would just say you're not alone on that. And also,

I would really emphasize to people that as much as we do talk about urgency, the transformation we think is coming, we say all this stuff so that hopefully people act, but I would also just say, this does not have to be rocket science to start. Like again, I keep coming back to the GPTs thing because it's just a good encapsulation of this. Whether it's GPTs or something else, focus in on these like three to five things that are causing you tons of stress, tons of time, like,

eat up tons of time that get your results that dictate your performance, drill into those three to five things and hammer away at those with whatever model you want and whatever prompting strategies you want for as much time as you can afford and then tune out the rest of the noise. That will get you really far.

Paul (28:24.504)
Nice, love it. I'm gonna get you back on for some more discussions like this because you've obviously got a wealth of feedback from people out there and lots of great advice from the Institute. Thank you. That'd be ace. And you've said it on camera now, so you're definitely coming back.

Mike Kaput (28:36.919)
I'd love that.

Right, I get the strategy behind this.

Paul (28:43.352)
If you've enjoyed this as much as I have, please leave us a comment. Ask any questions on the comments. We're enjoying seeing those starting to come in on Spotify now and leave us a five-star review if that's possible where you're listening. And most importantly, really help us if you hit the follow button, but make sure you don't miss future episodes as well, especially when Mike comes back. Thanks so much.

Mike Kaput (29:02.35)
Thanks Paul, I appreciate it.