[The AI Show Episode 213]: AI Answers - What AI Should Never Do, Enterprise Scaling, Governing AI & Navigating IT Roadblocks

The hardest questions about AI right now aren't technical. They're about people, policy, and judgment: when to push, when to slow down, when to walk away from a company that won't move, and when to keep something stubbornly human even though AI could do it better. Paul Roetzer and Cathy McPhillips answers 15 of them in this edition of AI Answers.

Listen or watch below and see the show notes and transcript that follow.

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What Is AI Answers?

Over the last few years, our free Intro to AI and Scaling AI classes have welcomed more than 50,000 professionals, sparking hundreds of real-world, tough, and practical questions from marketers, leaders, and learners alike.

AI Answers is a biweekly bonus series that curates and answers real questions from attendees of our live events. Each episode focuses on the key concerns, challenges, and curiosities facing professionals and teams trying to understand and apply AI in their organizations.

In this episode, we address 15 of the top questions from our April Intro to AI and Scaling AI class covering everything from tooling decisions to team training to long-term strategy. Paul answers each question in real time—unscripted and unfiltered—just like we do live.

Whether you're just getting started or scaling fast, these answers can benefit you and your team.

Timestamps

00:00:00 — Intro

00:07:01 — How do you move a company out of AI policy paralysis?

00:08:54 — How should organizations with experienced teams in highly regulated environments introduce AI?

00:12:31 — When companies are stuck with AI, what tends to get them moving?

00:15:00 — Should IT security evolve or should the business slow down rolling out new AI tools?

00:17:43 — What helps to change the minds of those skeptical of AI?

00:21:18 — How should early-career professionals prioritize what to learn about AI?

00:23:29 — When do you stop learning and start building?

00:27:29 — Where do companies get stuck scaling AI, and how do others make it work?

00:29:42 — Where is AI having the highest impact in HR?

00:33:04 — Do SMBs need a different AI playbook than enterprises?

00:35:55 — What should AI not take over, even if it's better?

00:39:43 — How important are guardrails for AI systems, and who should be setting them?

00:44:00 — If building software is commoditized, where is the real opportunity now?

00:47:48 — Could companies win by marketing themselves as AI-free and human made?

00:50:15 — As generations grow up with AI, what kinds of intelligence or capabilities do you think they’ll develop that older generations didn't?

Links Mentioned

• Intro to AI Course
• Scaling AI Course
• 2026 State of AI for Business Report Webinar
• AI for Business Bootcamp
• AI for Writers Summit
• AI Academy
• MAICON 2026

This episode is brought to you by the 2026 State of AI for Business Report webinar.

We surveyed more than 2,000 professionals on how they're actually using AI, what's working, and what's keeping them up at night. Join Paul Roetzer, Mike Kaput, and Taylor Radey on Thursday, May 14 at noon ET for a live walkthrough of the findings, plus Q&A. 

Register at smarterx.ai/webinars for live and on-demand access, and you'll also receive the report.

Read the Transcription

Disclaimer: This transcription was written by AI, thanks to Descript, and has not been edited for content.

[00:00:00] Paul Roetzer: Every day I talk to people like, oh yeah, I just gave it the login for these things. 'cause it kept getting hung up. And so now it has logins to my chrome and logins to this. And it's like, man, like you, you understand how security professionals could be pulling their hair out right now.

[00:00:14] Cathy McPhillips: Welcome to AI Answers a special q and a series from the Artificial Intelligence Show.

[00:00:20] Paul Roetzer: I’m Paul Roetzer, founder and CEO of SmarterX and Marketing AI Institute. Every time we host our live virtual events and online classes, we get dozens of great questions from business leaders and practitioners who are navigating this fast moving world of ai, but we never have enough time to get to all of them.

[00:00:37] So we created the AI Answers Series to address more of these questions and share real time. Sites into the topics and challenges professionals like you are facing, whether you're just starting your AI journey or already putting it to work in your organization. These are the practical

[00:00:53] Cathy McPhillips: insights, use cases, and strategies you need to grow smarter.

[00:00:57] Let's explore AI together.[00:01:00]

[00:01:04] Paul Roetzer: Welcome to episode 213 of the Artificial Intelligence Show. I'm your host, Paul Roetzer, along with my co-host today, Cathy McPhillips, our Chief Marketing Officer at SmarterX. Welcome Cathy to the podcast again.

[00:01:16] Cathy McPhillips: Thank you. It's been a, it's been a minute.

[00:01:17] Paul Roetzer: I it has been. And today, if you're thinking it's weird, like, where's Mike?

[00:01:22] this is a special AI answers episode, so we do these, this is our 18th edition of our AI Answers series. Where we answer questions from our monthly intro to AI and scaling AI classes, along with some of our virtual events that we run through SmarterX. So intro to AI and scaling ai. If you're not familiar, we teach these every month.

[00:01:41] They're free classes. Anyone can register for, the next scaling AI or No, this was, so what we're doing here is we're combining. Questions from these. So the way the classes work is I present for about 30 to 40 minutes, at each of these classes. We've had over 60,000 people go through these classes.

[00:01:57] So we've been doing these for a little while [00:02:00] now. and usually at the end there's dozens of questions that we don't get to. And so we curate those and then we go through and we, you know, record this episode. So. Today we are covering questions from scaling AI 16, and that was on April 23rd and then intro to AI 57.

[00:02:18] So that was the 57th time we've done that class, from April 16th. So if you attend either, either of those, hopefully we get to your question. If you have one we didn't. if you did not have a chance to attend them, you're gonna hopefully learn a bunch today. So, I will, I'll, I'll give you kind of like a little bit of background on, the episode sponsored by, our, our sponsors, which is us two, upcoming things we have going on at SmarterX.

[00:02:41] And then Cathy, I'll run you through kind of how this all works. So, the first, nearly two, three and four professionals believe AI will eliminate more jobs than it creates. That anxiety is real and it's showing up in our data, the 2026 state of AI for business report. Surveyed more than 2000 professionals on [00:03:00] how they're actually using ai, what's working and what's keeping them up at night.

[00:03:05] join me, Mike Kaput and Taylor Radey, our director of research on Thursday, may 14 at noon Eastern time for a live walkthrough of the Findings. Plus, as always, we're gonna leave plenty of time at the end for q and a. If you can go to smarterx.ai/webinars to register for live and on-demand access, and then you'll also receive the ungated report.

[00:03:26] So that's a follow up. If you've been listening to the podcast, Mike and I were talking a lot about that research, so thank you to everyone who participated. Like I said, we got more than 2000 people. there was one thing, Cathy. I thought was phenomenal. What Taylor shared with our group yesterday is like how many people took the time to answer the qualitative questions?

[00:03:44] Like they actually, right? Like there was one about like, what excites you most about ai and it's like 75 pages. I was on a plane when I saw it, but it was like, this is amazing. So out of that 2000, like 90% of people actually took the time to provide. Deeper responses, which is amazing. [00:04:00] So I'm anxious to present that data, to talk through it with all of you and to be able to share that report with everyone.

[00:04:06] And then also a new, just announced this recently. So, AI for Business. We are launching a new, event series called AI for Business. Bootcamp. So our first stop is gonna be in Columbus, Ohio on July 16, and that is at the Hilton, Columbus at Easton. So if you're in the area, 90 minute drive or so is what we were figuring.

[00:04:26] We're trying to kind of give an opportunity outside of Cleveland where our main conferences to start bringing education to other markets. So we're gonna start off there. The day kicks off. It's a one day, single track event, so it kicks off with me doing a state of AI for Business Keynote. That's about a 30 minute talk.

[00:04:40] And then we go into two workshops. So Mike Kaput, obviously my co-host on, the Artificial Intelligence Show is gonna lead an AI for, for productivity workshop that's gonna help attendees move beyond experimentation and start using ai. Systematically to transform how they work and optimize their workflows.

[00:04:59] And then in [00:05:00] the afternoon, I'm going to lead an AI for Innovation workshop that's gonna help you unlock growth opportunities for your organization and for yourself. There's also tons of time throughout the day built in for networking and getting to connect. current, current pricing ends at the end of May, and prices are even lower for our AI Mastery members.

[00:05:17] So if you are, Academy Mastery member, you get discounted pricing and seating is limited to 180 attendees, so register early. You can go to smarterx.ai/events to join me, Mike, and the SmarterX team. Cathy, I assume you're gonna be there as well. I

[00:05:33] Cathy McPhillips: will,

[00:05:34] Paul Roetzer: I hope so. Yeah. so me, Cathy, Mike, join us all in Columbus.

[00:05:38] So yeah, if you're in the area, I mean, you're welcome to fly in too, but certainly if you're, local at Columbus or driving distance from Cleveland, Cincinnati, Dayton, places like that, we'd love to see you. and yeah, if this goes well, the plan is to launch this in other markets starting this fall after Make on, so make on's October 13th to the 15th.

[00:05:55] And we're looking at different markets that we would bring this AI for Business bootcamp series to [00:06:00] starting hopefully in November. and then big plans for it in 2027. So yeah, hopefully, we'll see there SmarterX AI slash events. And with that, I'll turn it over to Cathy to give us a little more background on today's format, and we'll dive right into our questions.

[00:06:14] Cathy McPhillips: Sure. And one more thing on the business bootcamp, if you are not near interested in coming to Columbus. On the bottom of that form, on the bottom of that page. Rather, there's a form where you can put your name, email address, and the city that you would like us to come to so we can kind of crowdsource some of those and see where the interest lies.

[00:06:30] So I'm ex really excited for Columbus to get this kicked off. Okay, so I have 15, 16 questions for Paul today. Going through, like Paul said, the questions from our intro and scaling classes. Claire on our team who produces the podcast, she did a first pass at these. She has, an AI process built to. Go through those questions and curate them.

[00:06:52] And I went through them this morning and did just a quick pass myself. So we are going to get started

[00:06:57] Paul Roetzer: and I have not looked at them yet at all, so it'll be a [00:07:00] surprise to me like it is to our listeners.

[00:07:01] Question #1

[00:07:01] Cathy McPhillips: Yep. Okay. Number one, let's start with the tension. A lot of leaders are feeling right now, they know AI matters, but they're stuck in policy.

[00:07:09] What's your advice for to AI enablement leaders trying to move cautious companies from, we're still figuring out our policy to actually letting employees experiment.

[00:07:19] Paul Roetzer: I mean, this is a bigger problem for obviously large enterprises. I think a lot of small businesses, mid-size businesses are able to be more nimble and experiment while they're working on the bigger picture stuff, getting their policies in place, you know, working with legal, working with it.

[00:07:33] The big enterprises is where it can slow down significantly in this policy mode where it's still being treated largely, largely as a technology problem. And so, you know, maybe it's still sitting in the IT department or, you know, under the CIO's domain, things like that. And they're not empowering individual department leaders, business unit leaders to just push forward.

[00:07:53] So I think it, you know, you have to figure out how to experiment responsibly. Show business cases and business value with those [00:08:00] experimentations, you know, get permission to do these little things. And it really comes back to the whole idea of just education and awareness around how you can actually do this safely without having to solve the big picture thing.

[00:08:11] So we've definitely seen this with some enterprises we've worked with and advised where, you know, maybe the marketing team. Is like, let's just go, let's go get writer or Jasper or, you know, ChatGPT license, whatever it is. Like, let's just go get a thing and let's start doing newsletters and podcasts and emails and stuff.

[00:08:27] That doesn't touch any private data. There's no real risk involved. It's all publicly accessible information. and so that's how I do it. It, you know, it really just becomes education. Understand where the roadblocks live within your organization, who the gatekeepers are that are gonna allow you to kind of move forward and then present a logical, responsible plan.

[00:08:47] To experiment in a way that moves the organization forward while you're figuring out the big picture stuff.

[00:08:53] Cathy McPhillips: Yep.

[00:08:54] Question #2

[00:08:54] Cathy McPhillips: Which kind of segues nicely into question number two for organizations with experienced teams in highly regulated hands-on environments. What's the best way to introduce AI so people see it as a tool that improves decisions and execution, not just another corporate initiative.

[00:09:10] And what first use case would you pick to earn credibility? Fast.

[00:09:14] Paul Roetzer: I mean, I would start with the idea of optimization, of take your existing tasks and workflows and projects and just find ways to do those more efficiently. And, you know, start with an easy one that just shows, hey, we made a 20% improvement in efficiency.

[00:09:28] We're getting this project done this much faster. Or we were doing, you know, two episodes a month of the podcast and we're able to do four now, and actually in about the same amount of time. So we're increasing the productivity, we're actually doing more. so find something that shows tangible business value, that means something to the people who are gonna, you know, help push this forward.

[00:09:47] But again, especially in a highly regulated environment, you have to make sure that you're doing it to where it really isn't running up against the barriers to adoption that you, you know, and again, that's often gonna be touching, sensitive data, confidential [00:10:00] data, personally identifiable information if you're in like a healthcare environment, stuff like that.

[00:10:05] so yeah, that I, again, it's like you have to pick the things that are. common to what you do, like jobsGPT is an example where we built this custom GPT and you can just go in and put your job title in there and figure it out. But you could go in and copilot or Gemini or claw or whatever it is and say, Hey, my job is this and here's some of the things I do regularly.

[00:10:24] Like, help me prioritize which ones I could start with. And, you know, let's look at things that would normally take me 10 hours or less and I can prove quick value. Help me benchmark it so I can show leadership how it's helping me change. And then write me a one page strategic brief to make the business case of.

[00:10:39] You know why I should be able to do more of these things. So I don't know, like use these AI assistants as advisors. In this case they're really good at this kind of thing. Mm-hmm. Helping you figure it out, helping you build the use case, and then turn it into a strategic document. You can make the case internally with.

[00:10:56] Cathy McPhillips: Right. Yeah. That just provides so much clarity and [00:11:00] momentum. Once you get that first one under your belt and you're like, okay, now what else? Like, can I

[00:11:04] Paul Roetzer: do? Yeah, yeah,

[00:11:04] Cathy McPhillips: yeah. So,

[00:11:05] Paul Roetzer: and then you get overwhelmed like that. I live my life every day feeling overwhelmed with all the things I could be using AI for, and it's like sometimes it's hard to stay focused and just like pick the couple and just see them through,

[00:11:18] Cathy McPhillips: well, the other day you were saying something, you were, you know, we live in this all day long, you're doing all these things and there, there are, sometimes it just kind of stops you in your treks saying.

[00:11:25] I can't believe this actually is real.

[00:11:27] Paul Roetzer: Yeah, that was, that was a funny one. So I was in. Where was I? Colorado? Yeah, I was, I was having dinner by myself. I was just like sitting there. I actually told this story at the keynote the next morning, but I was just sitting by myself at dinner and I was working on a deck, like a slide deck.

[00:11:43] And so I just went into Claude and I was like, Hey, like, you know, I wanna do this. Here's our logo, here's the basic background I'm trying to do. Can you help me? And then I just sat there and watched on my phone where it's like. Going through its chain of thought and it's just building the presentation for me.

[00:11:56] and, and I did, I messaged the team. I was like, how, you know, we live in this weird [00:12:00] world, like we're surrounded by this stuff every day. And yet, like, I don't know that, that moment just caught me off guard. We're like, how bizarre is this? Like I'm sitting here eating my bread. And I'm watching this thing do the work of a senior designer.

[00:12:13] Like it, the output was incredible, like, so much better than I could do. And I build decks for a living. Like, I give a lot of presentations and I was like, it's just better than me at this. And it's so weird to watch it work. I don't know. it 's still so like, just bizarre to me.

[00:12:29] Cathy McPhillips: Right. for sure.

[00:12:31] Question #3

[00:12:31] Cathy McPhillips: So when companies are stuck, question number three.

[00:12:33] When companies are stuck, what tends to get them moving Better tools, a clearer strategy or leadership pressure.

[00:12:40] Paul Roetzer: I don't, I don't think it's better tools. I mean, the tools are really good, really. I mean, if you don't have access to them, then certainly that can be it. You know, if you're in an organization where, you know, maybe you just have copilot or you don't have anything, then yeah, I mean, starting with the right tools is definitely key.

[00:12:57] But I think a lot of times it's [00:13:00] just having a deeper understanding of what these AI platforms are capable of doing. You know, the understanding capabilities, the reasoning capabilities, the, you know, merging agentic capabilities and then being able to apply those to practical applications within your business and within your role in the company.

[00:13:18] So, I don't know. I mean, I think a lot of times that's the biggest barrier is just this lack of understanding and awareness, and then that leads to like. Lack of proper personalized training of how to use the tools. Some organizations, I don't know about leadership pressure. I don't know if that's the right term.

[00:13:32] I think leadership vision is probably a more important term where there's this mandate from the top that we are going to figure this out. Like, we're gonna become an AI forward organization. You're going to become an AI forward professional. It's expected of you. You have to be learning these tools. You have to be taking the courses we're giving you access to, like, you have to level up yourself.

[00:13:53] So I think it's more about a vision and then sharing that vision about here's where we're going as a company, here's what's expected of you. Here's how AI plays a [00:14:00] role in all of this. yeah, so I , I don't know. I think that it starts with vision. from the CEO, it ha, like, I'm a huge believer it has to come from the ceo and until it does.

[00:14:11] then that organization is likely not gonna be realizing their full potential with ai.

[00:14:16] Cathy McPhillips: Yep. Jessica Miller, our head of events or head of, learning rather, we, we are prepping for our AI for Writers summit break. Yes. Yesterday. And we got down that topic of, you know, if A CEO isn't the person, what do you do?

[00:14:30] Do you find a person? Do you just enable someone in your team to do that? So we had a nice conversation about that. I'm looking forward to doing at our summit next week.

[00:14:37] Paul Roetzer: We've definitely seen people at organizations who just took the reins as like, well, I'm doing this for the marketing team with or without the blessing, the ceo EO, and I think that's, that's good.

[00:14:47] Like that has to happen. But anyone who's been that person been the change agent knows their job becomes way easier if the CEO also correct is on board and pushing.

[00:14:58] Cathy McPhillips: Yep. [00:15:00] Okay.

[00:15:00] Question #4

[00:15:00] Cathy McPhillips: Number four. Our company's IT security stance is very conservative and it can't keep up with the pace at which leadership wants to roll out AI tools.

[00:15:08] Where should that tension resolve? Does security need to evolve or does the business need to slow down?

[00:15:14] Paul Roetzer: I wouldn't slow down. Um. You know, I think especially with agents becoming more integrated into workflows and businesses, you know, it's something we've obviously been talking a lot about on the podcast lately.

[00:15:28] The security stuff is gonna become more and more important because now we're talking about connecting this to data sources internally, giving it some level of autonomy to perform roles. I , every day I talk to people like, oh yeah, I just gave it the login for these things. 'cause it kept getting hung up.

[00:15:43] And so now it has logins to my chrome and logins to this. And it's like, man, like you, you understand how security professionals could be pulling their hair out right now. Like there's all these different areas where, you know, risk is starting to emerge. But I don't know that [00:16:00] slowing down is really the answer because what if your competitors aren't?

[00:16:03] And that's just the environment we live in today, and it's really hard to be, you know, we would call like an AI emergent company, like a legacy company that's trying to evolve and become more nimble and infuse AI versus being an AI native where it's like, Hey, we're just building from the ground up and we can take more risks and we can push the limits of these things.

[00:16:24] so yeah, it's, you know, it's hard though because those AI native companies can come up outta nowhere fast and all of a sudden that slow moving legacy company's in trouble. So, slowing down's not the answer, but, and especially go back to these highly regulated industries like banking and healthcare. I don't know how you speed up like, there, it's, I mean, it's slow for a reason mm-hmm.

[00:16:46] In those organizations. So, yeah, it's tough. Like if, if you're. You know, I think it's one of those career things, like, you know, if you're in a company that you look out and they're like, there's no way they're speeding up, and like, [00:17:00] I'm still not even allowed to use the full features of copilot. Like, what do I do?

[00:17:05] At some point, you gotta make that career decision of, am I gonna be left behind if I stay at a company like this where my peers are out there just like racing ahead and experimenting with all this stuff all day long and doing vibe coding as a sales person and like, and you're just trying to make the case to get like permission for a project and like it 's easier to change yourself and your career than it is your company sometimes.

[00:17:31] And I'm, you know. It's not, I'm, I 'm not trying to provide career advice. I'm just trying to be like realistic. Like sometimes the answer is, you just gotta go somewhere else that doesn't have that friction.

[00:17:41] Cathy McPhillips: Right. Okay.

[00:17:43] Question #5

[00:17:43] Cathy McPhillips: Number five. for employees who are skeptical or even opposed to ai, what have you actually seen change their minds if

[00:17:52] Paul Roetzer: there's a lot?

[00:17:53] I would say a lot of people actually fit into the skeptical. Bucket or just don't like it bucket. [00:18:00] Like I don't, I don't want to do it. Not, not even skeptical, like I get it that it's valuable and it's transformative, but like I don't wanna do it. So, I don't know. I mean like human psychology is a really interesting element to this and it's why change management comes into play so much.

[00:18:14] It's why HR needs to be educated better. Like, you know, your HR people should be leading the way in terms of AI literacy, and I'm not seeing a ton of that. But you need people who understand the dynamics of their employee base and you know, what the resistance may be from those employees to become AI forward themselves.

[00:18:33] One of, and Cathy, I don't know if you have anything to add to this one, but like the one thing I I've seen is peer-to-peer stuff. It's like you find those AI champions and a team or a department or within the business and you empower those people and then those people, you know, their peers see them.

[00:18:49] Doing it and maybe they function as, as mentors within the group. And it's like, Hey, come on, let me show you what I'm doing on the sales side or on the customer success side. And just seeing that very practical application from [00:19:00] someone who's their peer, who also maybe isn't technically minded. So that's the one key is.

[00:19:05] So a lot of people, if they don't understand this stuff, don't realize you need no technical background to do this. Like, it's literally just using words and talking to a machine and getting it to like help you. if you break through that technical barrier and you see someone else on your team that like, has a similar skill set to you and they're, you know, they're hitting escape velocity with their use of ai, that's motivating.

[00:19:28] It's like, all right, well show me what you're doing. Like, help me understand it. So, I dunno, I think there's like a, you can come at it from a. Macro level and like push down AI literacy capabilities and bring an AI academy into the mix and like train everybody. But there's, there's very little replacement for that peer to peer and just like that human connection, like, you know, that's why I love our bootcamp idea.

[00:19:48] It's like, let's get together, like right. Hear from your peers, share ideas, and it's not just like just sitting there listening and taking classes and stuff. It's adding an element of the human connection. I think that goes a long way with stuff like [00:20:00] this.

[00:20:01] Cathy McPhillips: Well, Ashlee, who is our head of events, she, we've, we've been working on our writer summit that is taking place the day that this podcast episode drops.

[00:20:09] And she's doing so many cool things with Claude right now. Mm-hmm. And I was like, can we have a meeting on Friday of May 8th, the day after the summit? Because I want to better understand, because I've tried to do some of the things, not the exact project she's working on, but similar things and I'm just not hitting it.

[00:20:24] Paul Roetzer: Yeah.

[00:20:24] Cathy McPhillips: And I just want, can we spend 30 minutes, can you just walk me through what you did? Because what's that little thing I'm just missing? So I'm not skeptical or opposed, obviously, I wouldn't be in this job, but there are some things like I just need a little bit of help and her showing me is going to unlock so many things for me.

[00:20:40] I'm really excited about that.

[00:20:42] Paul Roetzer: Yeah. I feel that way all the time. I mean, I, but again, like sometimes I look at it and think, yeah, but like, like I want to be able to do all the things that our studio team's doing or that, you know, Mike and Taylor are doing, or you know, some of the things I see Ashlee doing.

[00:20:53] And then, and then there's also this reality of like. I don't have time. Like I gotta be the CEO too still. Like I can't just be [00:21:00] experimenting all day long and you know, at some point you're just not keeping up on all the latest things and that's okay. But, you know, it's kind of a different story than this idea of like, people being skeptical.

[00:21:10] Right. It's like, I'm not skeptical at all. Like you said, like I'm, I'm all in, I get it, but I just don't have the time to experiment on everything.

[00:21:18] Cathy McPhillips: Okay.

[00:21:18] Question #6

[00:21:18] Cathy McPhillips: Number six, for individuals, especially those early in their careers, how do you prioritize what to learn versus what to ignore so you're not just staying current but actually driving impact?

[00:21:32] Paul Roetzer: I think focus is key here. and you know, I keep coming back to this idea of if, if you're only gonna do one thing, just get really good at one platform. and if it's whatever you have access to, Claude copilot, Gemini, Chad, GPT, whatever it is. Um. It's good to be paying attention to everything else going on.

[00:21:52] It's good to be understanding how agents are evolving and becoming more reliable and how you can integrate 'em. Like all that's great. But if you do nothing [00:22:00] else, then just get really good at using the AI assistant capabilities of your favorite platform and like understanding how to use deep research, understanding how like the more advanced models are better at helping you do planning and decision making.

[00:22:12] Like just get really good at the core platform. Um. You, you will transform your work. Like, it , that's enough for now. Like, you don't have to be doing everything and trying the latest thing all the time because, you know, depending on what bubble you're living in, sometimes it feels like I feel this way.

[00:22:33] Like I'm just like, wow, I'm not moving fast enough. I've never, I haven't installed openclaw on a Mac mini, like, oh my God. Like, I'm, I'm so far behind. It's like, no, like. Yes, there are people doing that stuff and I'd love to be able to do it, but at the same time, we are completely transforming our organization and hundreds of other organizations through our Academy and.

[00:22:52] And like that's enough. while also on the podcast talking about these things and saying, Hey, if this is your thing and you got time, like go, [00:23:00] here's the frontiers. Go out onto the frontiers and let us know what you discover out there. But for, I think for most businesses and most professionals, especially non-technical professionals, just get really, really good at gen AI and like it's enough, and then like start working in the agent stuff as it becomes more built into those platforms.

[00:23:19] Like with chat GPT, it's now. And baked into the platform. It's like, all right, find some experimentations to run with that stuff.

[00:23:26] Cathy McPhillips: Right. Okay.

[00:23:29] Question #7

[00:23:29] Cathy McPhillips: Number seven. A lot of people are stuck here. They're spending time learning new models and tools, but hesitating to scale anything because everything keeps changing.

[00:23:37] At what point do you stop learning and start building?

[00:23:40] Paul Roetzer: Never stop learning like that. There, there's no way to do that. Like, it's, it's just so everything's moving so fast. And I think being someone who's constantly learning and curious is the competitive advantage. It's the thing that keeps you from being obsoleted.

[00:23:58] Like, [00:24:00] you know, if, if, if you stand still now and you just, you aren't at least paying attention to what's coming, you could go from. The front of the line and being very valued in your company to. Being someone who isn't bringing the most value when it matters. And so I would say like always keep learning.

[00:24:21] Even if it's just like listening to our podcast once a week. Like if that's all you do, that's fine. Like at least you're keeping up. And like every once in a while you hear, you'll hear something and say, that's something I need to spend time on, or That's a threat. I'm interested. I'm gonna go like, learn more about that.

[00:24:35] So that's enough. Like I'm not saying you gotta every day be putting two hours into it. I'm just saying like, don't stop learning. But yeah, you, you gotta, you gotta figure out like a few things you can really lean into. So, you know, I talked recently about rocks, you know, as a way we run our organization similar to like an EOS model.

[00:24:53] Um. And I think about this all the time of like, what are like the five [00:25:00] things I need to do that bring the most value to the company? Because I could sit here and mess with Claude all day long, but if I'm not doing it for something that I know is gonna move the organization forward, then I'm, I'm probably just like wasting time.

[00:25:13] And so I would say always be experimenting, always be learning, but also always know what the three to five most important projects are that you need to be working on. And always think about ways to apply AI to those. and if you just do those few things, like I think you're in good shape career wise.

[00:25:32] Cathy McPhillips: Yeah. And I read that question a little bit as, okay, I built, wanna build a clawed project. Yeah. Should I just wait a few months because they're gonna come out with a new version? Should I just build it? Like, what's the risk reward of waiting? I mean, you can't wait. You can't assume that the new one's gonna come along.

[00:25:47] You know? It is, but like.

[00:25:50] Paul Roetzer: Sam Altman has said this many times, about this idea that like, if you're building something and a smarter version of the model, obsoletes [00:26:00] what you're building, then don't build it. But if a smarter model makes what you're building better every time, then like. Go in and build that thing, whether it's a startup or an app or a tool for your team or whatever it is.

[00:26:12] And so I think a lot about that with the things we're building internally. There's some, some projects I'm working on that hopefully will become public in the next couple months. And everything I'm working on, like the more intelligent these models get, the more generally capable, the more agentic, the more powerful these tools will become.

[00:26:30] And so that's a good litmus test to say. Just go and when a new model comes out, have benchmarks, have your, your own evaluations to tell you, you know, has this model gotten better at the thing I'm specifically interested in, or that I built something for? so yeah, I , I wouldn't wait. I mean, you can kind of look around the corner a little bit and know what the models are gonna be able to do, but yeah, I would just, as long as a smarter, more generally capable, more agentic version of a model.

[00:26:59] Makes what you're [00:27:00] building smarter and more valuable then build it,

[00:27:03] Cathy McPhillips: right?

[00:27:03] Paul Roetzer: If a more general version of your model obsolete, or a model obsolete what you're building, then you know, so like an example would be if you're writing a bunch of rules to set up a bunch of automations and then you're connecting a bunch of auto, like, you know, through web hooks and all this stuff, and that's your whole model, there's a pretty good chance that model's gonna be obsoleted real fast.

[00:27:26] So that's kind of like one example, I guess.

[00:27:29] Question #8

[00:27:29] Cathy McPhillips: All right. Number eight. When companies try to scale AI across departments like legal and marketing, where do they usually get stuck and what separates the ones that actually make it work?

[00:27:41] Paul Roetzer: I would, I would think people friction. It probably goes back to that earlier question around people who just don't want to do this.

[00:27:48] Um. Marketing, you know, our experience, Cathy, has been, marketing's usually the leading edge of this within most organizations we talk to because I dunno if it's 'cause the use cases are so practical [00:28:00] to marketers or a lot of the early SaaS companies that spun out in like 2023 focused on the marketing industry because, because.

[00:28:08] The tool is really good at writing and doing a lot of things the marketers did, but for whatever reason, marketing is often, you know, really pushing within organizations to do this. But once you go into HR and legal and finance and operations, this is just not, it's not normal for them to be the ones really experimenting with this stuff and super excited.

[00:28:30] And honestly, some of those professions are, are pretty prone to automation. Like some of what they do is quite. High on the exposure level, I would say, of AI doing a lot of that work. And so there's just a natural resistance from people. Like they don't, they're not in a hurry to obsolete what they do.

[00:28:51] They don't really understand the tech. So I think it just, it, everything for me just comes back to the literacy thing. If you understand what the technology is, if you're [00:29:00] experimenting with it all the time, then you become more confident in your ability to figure out how your own role is gonna evolve.

[00:29:06] How it can create value for you right now, how you can make a greater impact on the organization. And if all those things are true, then you're gonna. Be more likely to wanna adopt this stuff and wanna scale it across your department and your team. But if you don't really understand it and you're kind of worried about it taking your job, or you don't, you know, you think there's a bunch of ethical problems behind it, or whatever your reason is, but it's usually a lack of vision from leadership or human friction.

[00:29:33] Like those are the two. It's not the tech. Like, it's almost never that the tech can't do the thing. It's almost always a people problem.

[00:29:42] Question #9

[00:29:42] Cathy McPhillips: Number nine. Where are you seeing the highest impact use cases in HR right now, especially across recruiting, onboarding, and internal communications? And where should the human elements still remain?

[00:29:54] Paul Roetzer: So we have a whole AI for HR series, now, course series in AI Academy. so if you're [00:30:00] an academy member, go check that out. You know, I'll talk specifically about just like from a SmarterX perspective, how we're thinking about it. so there's definitely elements of recruiting, but a lot, honestly on, on the interview side.

[00:30:12] So we're doing it more, you know, we can assess candidates based on it. So you get inter, you know, resumes in, you can run it against like a rubric to tell you like, is this person qualified for this? but then we use it to do summarization of notes based on it, to do, to do assessments of people we've interviewed.

[00:30:29] it's being integrated into our onboarding. Process, but all of our workflows and everything within the organization ha have AI kind of increasingly in incorporated into it. but I think you're starting to see a lot of candidates using AI to prepare for interviews. So they come across as sounding amazing because AI's really good and persuasive.

[00:30:48] And so it can make a cover letter look amazing. It can make resumes look amazing and personalized. It can make the communications from the candidates look amazing. And so one of the big, [00:31:00] big things is being able to get to the human side of the process and get to know the actual person behind. What you almost have to assume is the AI facade.

[00:31:09] When you have candidates coming in, because I would say at this point, if you are not using AI to look really good in the interviewing process, you're probably falling behind. So as a, as a hiring body, you have to assume they're using AI and they have to assume you are using ai. So, I don't know. I think like that's.

[00:31:29] One of the primary ones. And then obviously when you start to get into the actual, like, assessment of people, performance reviews, professional development tracks, things like that, it can be infused into all of that. but again, like this is a great one. If, if you're curious, one take, you can take our courses.

[00:31:46] Two, just go into your favorite assistant and say, Hey, I'm, you know, trying to think about AI applications, for hr. Here's the specific areas I'm interested in. What are the ways I could be doing this better, either as a candidate or as a hiring manager? [00:32:00] how could I be using it? Gimme like five practical ways I could start tomorrow.

[00:32:03] Like things that wouldn't take me a ton of time or need new software for. So it's, you know, really way to, a good way to do it.

[00:32:10] Cathy McPhillips: It's interesting, someone in my family is currently, on the job search and what I'm seeing from them is very fascinating on automatic rejections that they're very qualified for.

[00:32:21] Paul Roetzer: Yeah.

[00:32:22] Cathy McPhillips: And just trying to figure out how to navigate that whole situation. So I would say on that side, from the human side of it. Making sure that your HR people are still doing those human check-ins to make sure that they aren't losing good candidates.

[00:32:33] Paul Roetzer: Yeah, and on the hiring side, again, like the thing, I've talked to some people who've been looking and they're just spraying, like, it's so easy to just spray personalized resumes out there now and like applications and so it's like a flood of applications.

[00:32:49] Coming in that seem really well personalized, and then yeah, it's like AI is your defense mechanism of like, oh my gosh, we're getting so many applications and so now we need AI to filter it. Right? And yes, like losing the [00:33:00] human element on both ends is, is a problem.

[00:33:02] Cathy McPhillips: Absolutely.

[00:33:04] Question #10

[00:33:04] Cathy McPhillips: Number 10, do SMBs need a different AI adoption playbook than large enterprises?

[00:33:09] And if so, what changes?

[00:33:12] Paul Roetzer: Well, the SMBs can move faster. You know, we talked about this in one of the early questions, so it's a lot easier to get approval for things. you know, if you want to try experiment, like you're probably gonna get more, you know, likely to not have a bunch of barriers for experimentation and trying new tools.

[00:33:27] so yeah, I would say like the adoption playbook, the issues become probably more around. As A SMB, you don't have maybe the security capabilities built in the IT department built out, so maybe you're not as expert in that. So in the SMB, you can move faster. Like let's say you can go try a lot of this agentic stuff, but you also now are increasing your risks and the unknowns related to it of like, well, okay, that's really cool that you did that, but like.

[00:33:55] What happens if it breaks? Like what do we do? Like you just put [00:34:00] something out into production and released it publicly and we have no idea how to manage a tool like that. So I think that's one of the things is what with the ability to innovate. Comes all these unknowns that maybe you're not prepared for as an SMB.

[00:34:16] And then on the larger enterprise side, obviously things are gonna move slower, but you have a lot of those other layers baked in that allows you to do it in a more responsible way. So there's a trade off to each of them. But the, I mean, the playbooks vary in part based on. on, on the governance I guess would probably be like one of the biggest things is just the overall governance of the tools, the uses of those tools and then how you do it in in responsible and safe ways

[00:34:44] Cathy McPhillips: for sure.

[00:34:44] And just knowing that enterprises have so many resources, people, resources in legal and IT and all those things. And SMBs may not, that that's a sound investment is to make sure you have partners that can help you navigate through all of this.

[00:34:56] Paul Roetzer: Yeah. And I hear from friends all the time who are, you know, building more [00:35:00] AI native companies who are.

[00:35:02] Very open to experimentation and there's times where I'm like, man, like you just, I can't do what you're doing. Like, as an organization, as a CEO, because I've, I mean, I've, I've been an entrepreneur for 21 years. I've seen stuff go sideways, for us, for clients. I mean, when I ran an agency we had over.

[00:35:23] What, 450 clients over 16 years, like you see things and I , I guess I'm a little bit, I would say I have a pretty high risk tolerance overall as a CEO. But there's stuff these AI native companies are doing where I'm just like, have you ever even talked to a lawyer? Like, do you, do you not have advisors?

[00:35:43] Like, what? I can introduce you to some people because you're, you're running at a very, very high risk right now, and they're just like, eh, I don't know any better.

[00:35:52] Cathy McPhillips: Right. Huh? Okay.

[00:35:55] Question #11

[00:35:55] Cathy McPhillips: Number 11, what is something that AI probably will probably be better at than humans, but we still shouldn't let it take over?

[00:36:04] Paul Roetzer: I don't, I mean, this is a personal one for me, but writing, I mean, I don't wanna offend anybody, but like.

[00:36:13] AI is a better writer than like 99% of people. Like depending on what you give it to write about now, there's no human experience underneath it. So it's surface level. But if you are given an AB test of a human versus a machine, and there was a New York Times article, I think a couple months back, Mike and I talked about where this was proven that like people can't tell the difference and they actually preferred the AI written content in that environment.

[00:36:37] And it was a pretty limited test. But um. It is very hard for the average person to know if they're reading something written by AI or not, and that's a hard thing for writers to accept. But even when I did my AI for Writers Summit keynote in 2025, this is the exact thing I addressed, was like, even if you know, you can disagree with me, that it's not [00:37:00] better and maybe, you know, your specific in experience has not been that it's better and that's fine.

[00:37:04] Like that, it's just a subjective thing. Um. My point was, even if it is, I don't want it to do my writing. So when I write my editorial newsletter for exec AI newsletter goes out on Sundays, that's a hundred percent me no AI involved. I don't even use AI to edit it. anytime I publish on LinkedIn, it's a hundred percent me, everything I say on the podcast, a hundred percent.

[00:37:29] Me, again, I don't use AI at all in those processes, and that is by design. When I give keynotes, that's me. So. Even if it is. That is like the thing about what I do that I enjoy, I find it fulfilling. I think authenticity matters, significantly otherwise, like what, what credibility do I have? If all I'm doing is regurgitating what chat GPT wrote for me to say these, these q and as.

[00:37:57] Again, I don't even look at the questions before we get on here. I [00:38:00] have zero AI help in any of this stuff. and I think that's really, really important. For me. And so I think everybody has to make a choice. Now, I will use AI to write like abstracts for my talks or things where authenticity is irrelevant.

[00:38:13] Like nobody cares that it wasn't me that wrote the abstract for the keynote I came up with. So there's a balance between when you should and shouldn't. And so the key for me is just because it can doesn't mean it should. And I think that's where everyone has to make their own decisions. And then you have to work for companies that allow those decisions to be made.

[00:38:31] So if you're like. a coder and you're at a company where they're like, you're not writing code anymore. You have to make that choice of like, okay, but I really like writing the code and I feel like that's the thing that's fulfilling to me not building the end product of it. Then you got a career choice to make.

[00:38:48] Um. I don't know too many companies that are gonna let you choose to not let the AI write the code. But for us, you know, in a business like ours where a lot of what we do is creation of [00:39:00] content, I want our humans still doing the human experience of writing when it's meant to be authentic and original.

[00:39:08] So yeah, it's, it's a balance between personal choice and then the choices that are made by the company you work for and what they allow you to still be very human.

[00:39:17] Cathy McPhillips: Right. Like I love writing our make on emails because it's such an important

[00:39:21] Paul Roetzer: mm-hmm.

[00:39:21] Cathy McPhillips: Personal event to me, but it can write my subject lines all day long.

[00:39:25] Yeah. Because I want people to open them and see them and what I think is great probably, I don't know. So I'm, I have all the, a persona I, chief PT that we have, that I use, so I definitely use AI on some of those sorts of things, but the emails themselves like, come from my heart and soul.

[00:39:40] Paul Roetzer: Yeah.

[00:39:40] Cathy McPhillips: You know?

[00:39:41] Yeah. Okay.

[00:39:43] Question #12

[00:39:43] Cathy McPhillips: Number 12. How important are guardrails for AI systems in reducing risk, and who should be setting them? Who should be sending them? The companies building the tech, or more independent public groups?

[00:39:54] Paul Roetzer: it's probably a combination. I mean, the risk reduction is just becoming more and more [00:40:00] important.

[00:40:00] Again, if you're in a highly regulated industry, you, you've been working on this since 2023, like the risk related to these things. But for a lot of people. The more agentic stuff that gets involved, the more you start connecting these core platforms off to other data sources and software products that you have access to.

[00:40:18] once you start allowing them to start making decisions and potentially even like doing complete workflows of projects with no human oversight or approval process, that's where you start to really run into the challenges and the risks start increasing. I 'll say like again, just as the CEO, there's things that we're starting to do.

[00:40:38] Every day as an organization because we've empowered everybody to go ahead and experiment, like try things, do things. There's at least once a day where I was like, Hmm, I don't know about that one. Like, I don't know if I was ready for that. Or like, you'll get a request for somebody like, can I go run these experiments?

[00:40:56] It's like, I don't know. I don't know that we have the [00:41:00] guardrails for that yet. Like I don't know that I feel comfortable allowing those things, and so part of that's on me to like. Move faster to get more governance in place so we can experiment. More. I , I guess more aggressively and safer. But, I don't know.

[00:41:20] Like I don't know that relying on outside bodies is gonna do that. I think that's more of like a company level thing. and again, just seeing my own instance, like I'm the barrier as the CEO now I don't have a CIO or a CTO or a chief I officer. Like I don't have anybody else that I could turn to and say, okay, this is your.

[00:41:40] Domain. We have IT consultants that are heavily involved in all this stuff for us now. but yeah, I think again, going back to the SMB versus enterprise conversation, I think a lot of SMBs are probably in a situation similar to ours, but a lot of the leaders of those SMBs don't know what I know about the risks of what is [00:42:00] happening right now.

[00:42:01] And so they may be blissfully unaware of the risks that are being taken by their employees. Um. So, yeah, it , it's a weird time when it comes to this stuff and obviously I've been talking a little bit more about it on the podcast recently because I'm honestly just more worried about it. And then you see these stories like we have one we'll share, on, well you and I are recording this before episode two 12, right?

[00:42:25] This is two 13, correct? Yeah. So two 12 will have come out before this one comes out. 'cause Catherine recording this on Thursday, April 30th. It's gonna come out a week later I think. Um. There's a story of a guy who had his entire production database wiped by a cursor, agent using a Claude model, and it happened in nine seconds and the company's just gone like, just wiped.

[00:42:48] And he knew what he was doing, like, right? It was. And so that you see these stories every day now. And so I am just as a CEO of an AI forward organization, like [00:43:00] infinitely aware every moment of. How risks is, risk is changing right now.

[00:43:07] Cathy McPhillips: And it is interesting because even, you know, just among our team, there have been things that we're like, can, can we do that?

[00:43:12] Should we do that? That, yes. Well, the good news is, is that we're pausing before we take that action. But if we're unsure and we are doing, we're in this every single day, there are swaths of people that just have no idea. And like you said, they're blissfully unaware of just the nurse doing things. And when are, when are people gonna realize what's actually been done?

[00:43:32] Paul Roetzer: Yeah, and then even, you know, we have admin controls of everything, but even times where I'm like, I don't even know what the admin settings are on some of this stuff. And maybe people are taking risks that they think are totally normal and not risky. That I thought was covered by some setting. We had an admin and then you find out it wasn't, and then you're like, oh, shit.

[00:43:54] Like, okay, we probably need to spend more time thinking about this.

[00:43:58] Cathy McPhillips: You're right.

[00:44:00] Question #13

[00:44:00] Cathy McPhillips: number 13, if building software is becoming commoditized, where is the real opportunity now still in SaaS or shifting towards services, automation and enablement?

[00:44:10] Paul Roetzer: Yes. I, so, I'm not sure that software is commoditized.

[00:44:17] Like I , I still think that taste matters a lot, like what to build. So when all of us can build something. What to build becomes more important. I do think that that's still somewhat unique now. It can be copycatted real fast because I can literally just build something. Someone else can send their agent, say, oh, go copy what they just did with that thing, and now they can launch like a competing thing right away.

[00:44:44] So I guess in that side it might, I maybe it's becoming a bit commoditized. But I'm still very bullish on software overall. I just think the model's changing because of the pricing. There's tons of pressure on pricing, and then the whole reality that agents [00:45:00] may be the users of the software more than humans, and that's, companies are trying to come to grips with that, figure out what that means.

[00:45:07] Now in the process, I'm very bullish on services. I think that. And even in the last couple months, I've shifted a little bit on, you know, what I think the opportunities are for agencies and consultants and advisors because there's so much opportunity right now for companies to. Adopt AI and scale it within their organization from SMBs up to big enterprises and they just don't have the people internally to do it.

[00:45:34] And I've been thinking a lot about this one personally lately because you know, I can go into Lovable or Replit or Claude, I can like vibe, code an app, I've done a bunch of 'em, and you build something in 10 minutes or a half hour and it's like, this is really impressive. Like now what the hell do I do?

[00:45:50] Like how do I get this into production? How do I put this out in the world? And I could probably do that. But then like I said earlier, like what if something [00:46:00] goes wrong or what if there was a cybersecurity issue with it that I didn't even know to be aware of? And it pops its head and like, now what do we do?

[00:46:09] And so I'm kind of more of the camp and I saw somebody tweeted this recently. I remember who it was. Um. I want to use Vibe coding to build my ideas in my brain and get like to a, a minimum bio product to turn over to a services company who's our experts in taking things into production and putting them out into the world, and then managing them when they're out in the world.

[00:46:30] And I want them to charge me less money because I know I just did 80% of the work for them, and they're able to like, get this thing live faster. So I still want those trusted partners. I just can do more. It's almost like graphic design. Or architecture, like I can do concepts in my head and say, okay, here's the concept, but like, I have no idea how to get this into final file format and like do all the other things.

[00:46:57] So can you do what you do? Like, but I'm now giving [00:47:00] you my ideas in a, in, in a pretty polished form versus. Words on a, a pap a paper previously. So I think the services industry is shifting, but I'm very bullish on the companies that figure that out and adapt their pricing model and their service mix to it.

[00:47:16] So, yeah, I I don't know that there's like a right or wrong answer here. I think people are gonna build more software than ever, like, and it's gonna be sometimes people who usually aren't developers and then people who are developers are gonna be able to build more and cooler things. But I also think services is gonna be a really interesting area where people are gonna make a lot of money if they position their services correctly and they figure out how to deal with the pricing collapsing because everything is able to be done so fast.

[00:47:46] Cathy McPhillips: Agreed.

[00:47:48] Question #14

[00:47:48] Cathy McPhillips: Number 14, could we see companies start to market themselves as human made or AI free and actually win because of it?

[00:47:56] Paul Roetzer: Definitely. Yeah. I , I would imagine it's [00:48:00] already happening. I haven't gone. Searching for this, but it's like the, was it Etsy? Was that the original model of Etsy? It was like handcrafted.

[00:48:07] It was always supposed, I don't think that's what it became over time, but like that was the idea was it was like human made. I could a hundred percent see this in, especially in the creative world, you know, artwork. Um. Writing things like that where it's just that it means more there. But I t might be a niche sell.

[00:48:26] Like I don't know how big the market is for that, because at the end of the day, a lot of people just want the best product for the cheapest price and you know, so. I don't know. Like I , I wanna believe that there is a, a very meaningful market for human made AI free. Like, I think that'll matter. I just, I don't know from an economic standpoint how big that market really is.

[00:48:53] Cathy McPhillips: And this question stemmed from, I think they alluded to Doug, so CPG, so like, does it even make [00:49:00] sense for them to say they're AI free? And how does that fit into their narrative? Right.

[00:49:06] Paul Roetzer: I mean, I guess if you're. Like, so you could do it from a perspective of like, we don't use AI in our messaging, our marketing, and our whatever.

[00:49:16] but that's, you better have some really good research data that tells you there's a large enough percentage of your potential buyers who care that you're not using AI and your product or your messaging or whatever. And I just, I don't, I've never really thought about this. I'm kind of answering this one very much off the cuff.

[00:49:35] I can't imagine that there's ever going to be a large market of those people. I think research will show people don't like ai. I think they'll show they have problems with data centers in their communities. I think it'll show they're worried about jobs and they're worried about. intellectual prop, like research will show all of these things, but at the end of the day, it's money talks and will [00:50:00] people change their buying behavior at a mass scale because a brand does or does not use ai?

[00:50:06] I don't, I don't currently think that that is a likely outcome.

[00:50:13] Cathy McPhillips: Agreed.

[00:50:15] Question #15

[00:50:15] Cathy McPhillips: Number 15. Her last question, as young, I love this question. As younger generations grow up with ai, what kinds of intelligence or capabilities do you think they'll develop that we didn't?

[00:50:27] Paul Roetzer: I don't know. I'll tell a quick side story here and then I might come up with something smart to say about this.

[00:50:33] So I was traveling this week. I was at, at an event for Acquia, doing a, a keynote for them. I got home Wednesday night, so again, we're, this is coming out a week later. Um. And my son, who's 13, he's like, yeah, I gotta show this project I work on. I was like, all right, what do you, what do you got? And they had to show something about like the evolution of cannons, like in warfare, I dunno, during the Renaissance or something like that.

[00:50:55] And so he came up with an idea to. [00:51:00] Do scenes in Minecraft, so him and a buddy, like simulated scenes in Minecraft that they screen recorded. Then he went and found ai 'cause there was like a battle scene and then like he was showing like hand to hand combat and then the creation of the cannon. And I'm just sitting there like.

[00:51:18] How did you come up with this idea for one? And he said, oh, just hold on. And then he's like showing me how he used iMovie and then he went to an AI site and he said, but I betted the site. It was totally safe. Like here's the background of like why it's safe. And I got AI voices for the crowd and the fighting, and I laid that in here and I pulled that track down there.

[00:51:33] I was like, who taught you how to use iMovie? Like, what do you, and so this thing's like a minute and a half long and I finished. I was like, I can't believe. He did this. Like I , I mean I know he is like super talented with this stuff and like has a very creative mind, but the blending of the AI in it was just so natural to him.

[00:51:54] It was just like, he didn't even think a second thought about it. It was just like, oh yeah, I grabbed AI and I knew I could do this. Da da, da. And [00:52:00] I was like, damn, dude. Like this is really impressive. And so, and then I see like with my own daughter and like the way she'll use guided learning to help her learn when she's not like she's struggling with math, it's like, okay, let me go in.

[00:52:11] I know I can't ask for the answer, but like, let me work through things. Or, you know, she's trying to write a book and so she'll go in and like ask for advice. And so I'm seeing them just work AI in, in responsible ways into the things that they're. Thinking about and working on. And to them it's just like totally second nature.

[00:52:29] And so you can start to see how this younger generation, if they're taught how to do these things responsibly and not just using it as a crutch to replace the work and the thinking, how their abilities are. Like just racing ahead. Like I've tried to do iMovie many times myself. I couldn't comprehend how he figured out how to do the things he did, and she realized like, and he probably just went in like Google and talked to like AI mode, like how do I do this thing?

[00:52:58] And like, so I think they're [00:53:00] going to just. Natively know how to integrate it into everything they do, and I think they'll be able to learn much faster because they're going to have tutors and mentors available on demand for whatever they want to learn. They can build flashcards, they can turn dense documents into podcasts.

[00:53:21] If they learn better, they're gonna be able to build virtual worlds to envision things like. I just think that if schools do their job, and if it's not schools, then parents do their job to teach responsible use. These kids are gonna be able to learn stuff so much faster.

[00:53:34] Cathy McPhillips: Yeah.

[00:53:35] Paul Roetzer: and that, that's exciting as long as they're not just using it as a crutch.

[00:53:40] Cathy McPhillips: Right. One of my favorite stories about my son, who's now 20, almost 28, is he did something and I was like, same thing. I'm like, how'd you even know how to do that? He said Google and grit, and that was, you know, that's

[00:53:52] Paul Roetzer: great.

[00:53:52] Cathy McPhillips: However many years ago. It's like, imagine what he could do now, you know?

[00:53:55] Paul Roetzer: Yeah,

[00:53:56] Cathy McPhillips: I do.

[00:53:56] I am bummed that like they were both outta school by the time. My daughter [00:54:00] graduated the spring of 23

[00:54:03] Paul Roetzer: right after,

[00:54:03] Cathy McPhillips: so they didn't get a ChatGPT education when they, when they were in school. So that's,

[00:54:08] Paul Roetzer: but they learned like the rest of us. I graduated college in 2000 and I never used email in college. So like it worked out okay.

[00:54:16] Like I missed the whole like internet chat room. Like I didn't have any of that when I was in high school and college. And here I am running an AI company. So they, they're gonna be all right. They'll figure out, they'll be fine.

[00:54:29] Cathy McPhillips: Well, thank you Paul, as always. if you're listening to us on Thursday morning, May 7th, our AI for Writer Summit is taking place today.

[00:54:35] You can go to aiwriterssummit.com and you can sign up for free. We'd love to see you there. And our next intro and scaling are coming up in May, and we will, right,

[00:54:46] Paul Roetzer: I assume we do 'em every month, so they gotta be coming up at some point.

[00:54:50] Cathy McPhillips: All the days are blending together. This point in my life. We're doing a lot.

[00:54:53] Thanks Paul.

[00:54:54] Paul Roetzer: Alright,

[00:54:54] Cathy McPhillips: thank you

[00:54:55] Paul Roetzer: Cathy. Thanks for listening to AI Answers to Keep Learning. [00:55:00] Visit smarterx.ai where you'll find on-demand courses, upcoming classes, and practical resources to guide your AI journey. And if you've got a question for a future episode, we'd love to hear it. That's it for now.

[00:55:14] Continue exploring and keep asking great questions about ai.