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[The AI Show Episode 100]: Your Top AI Questions Answered: AI’s Impact on Business, Marketing, Jobs, Careers, Education and More

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We have a special bonus episode today, and it's all about celebrating our 100th episode! To mark this milestone, we have dedicated this episode to answering your questions.

The Artificial Intelligence Show is much more than just a place for us to share content. It's our way of making sense of the AI world and putting it all into perspective. We are lucky to be on this journey with all of you, learning and growing together every step of the way. Let’s take a look at some of those questions you sent our way.

Listen or watch below—and see below for show notes and the transcript.

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Timestamps

00:04:46 — A brief background of the podcast

00:08:57 — What is the most stand out moment of AI redefining aspects of the future of work?

00:13:40 — If you could ask Sam Altman one question, what would it be?

00:16:36 — What are the best AI tools available for small & medium-sized businesses?

00:19:55 — What are best practices in assessing AI tools?

00:22:40 — How can small and medium businesses apply AI to their customer data?

00:25:47 — What's your favorite success story of a business adopting GenAI so far?

00:28:55 — What tools does the MAII team use in their workflow?

00:32:09 — How should leaders decide whether to focus AI efforts on high-potential individuals or distribute training and resources across the organization?

00:35:53 — How do people use AI in their daily lives?

00:39:29 — In the next 5-10 years, what do you think the adoption of AI tech will look like for most businesses?

00:42:19 — How can professionals stay updated and enhance their knowledge?

00:49:40 — What are ways I can showcase my AI knowledge while looking for a job?

00:51:26 — What do you think AI’s role will be in strategy work as it evolves?

00:55:21 — What AI enabled services would you add to your client service model if you were running an agency?

00:57:53 — If you were launching a marketing agency today, how would you approach scaling with AI tools?

01:00:35 — If you were leading a college degree in marketing, what would you do to ensure that your students are prepared for the future with AI?

01:03:07 — With advances in AI and the capabilities of instant knowledge transfer to anyone at anytime, what do you think the next evolution of education will look like?

01:06:14 — What tech moment needs to happen for AI applications like ChatGPT to cross the chasm to early/late majority of users?

01:08:55 — Should we be asking more questions about privacy and security? Do we trust these companies too much?

01:11:14 — How do you see regulation affecting AI?

01:13:28 — What advancements in AI are you excited for in the next year?

Links Referenced in the Show

Today’s episode is brought to you by our AI for B2B Marketers Summit, presented by Intercept.

This virtual event takes place on June 6 from 12pm - 5pm EDT and is designed to help B2B marketers reinvent what’s possible in their companies and careers. Thanks to our presenting sponsor Intercept, there is a free registration option.

To register, go to www.b2bsummit.ai.

Today’s episode is also brought to you by Piloting AI, a collection of 18 on-demand courses designed as a step-by-step learning path for beginners at all levels, from interns to CMOs. Piloting AI includes about 9 hours of content that covers everything you need to know in order to begin piloting AI in your role or business, and includes a professional certification upon passing the final exam.

You can use the code POD100 to get $100 off when you go to www.PilotingAI.com.

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: look at the individual roles in your company and your team in certain departments and try and project out 12 to 18 months from now.

[00:00:07] Paul Roetzer: What do those roles look like? And that's the part I'm worried about that just not enough corporations are having those conversations. And

[00:00:14] Paul Roetzer: Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Roetzer. I'm the founder and CEO of Marketing AI Institute, and I'm your host. Each week, I'm joined by my co host, and Marketing AI Institute Chief Content Officer, Mike Kaput, as we break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career.

[00:00:44] Paul Roetzer: Join us as we accelerate AI literacy for all.

[00:00:51] Paul Roetzer: Welcome to episode 100 of the Artificial Intelligence Show. I'm your host, Paul Roetzer, along with my co host, as always, Mike Kaput. What's happening [00:01:00] Mike?

[00:01:00] Mike Kaput: Not much. How's it going?

[00:01:02] Paul Roetzer: Good. Well. Well. Well. Well. it's an adventure. I mean, we are, so again, timestamp this, we are recording this Wednesday, May 29th. this is our special edition 100th episode.

[00:01:14] Paul Roetzer: we've had a couple change of venues morning trying make this happen, but we are here, recording. This is going to drop on May 30th. So, uh, if you're a regular listener to the show, you know, we decided to do a special edition, uh, for you. Uh, for the hundredth episode, that is all about answering your questions.

[00:01:33] Paul Roetzer: So we had more than a hundred questions submitted by our listeners over the last two weeks,  since we that there. we

[00:01:40] Paul Roetzer: appreciate everyone who took the time to submit questions. We've got a ton to get through. We're going to try and, Mike's curated a list of about what Mike. 25 or so questions.

[00:01:50] Paul Roetzer: I think we curated it too. So we're going to try and get to all, we're going to try and answer as quick as possible, as long as I don't like detour us too much off

[00:01:57] Paul Roetzer: of one of them. We should be able to get through them [00:02:00] all. so we're going to get to as many as we can. So

[00:02:04] Paul Roetzer: episode is brought to us by the AI aI for B2B marketers summit that is presented by our presenting sponsor Intercept.

[00:02:12] Paul Roetzer: This event is an inaugural event. So it's new to our events. series. It's coming up June 6th from 12 to 5 p. m.

[00:02:21] Paul Roetzer: Eastern time. And it's designed to help B2B marketers reinvent what's possible in their companies and careers. During the event, you're going to have

[00:02:29] Paul Roetzer: chance to learn about AI and how it can be infused in creating dynamic customer experiences, how we can bridge the gap between marketing and sales.

[00:02:37] Paul Roetzer: Build an AI council. we're going to talk about real world adoption with some leading marketers, leading B2B marketers. So it should be a lot of fun. There's more than 3000 people already registered. There is a free registration option. Again, thanks to our presenting sponsor Intercept. You can go to b2bsummit.

[00:02:53] Paul Roetzer: com. ai to get registered today. There's an on demand and private registration option as well, [00:03:00] but you can get registered for that for free. Uh, it's the, if

[00:03:02] Paul Roetzer: you attended our AI for Writers Summit, same format, same general idea, and we had just amazing responses to that event. So we're hoping to, you know, really bring another phenomenal event to everybody, and again,

[00:03:14] Paul Roetzer: making it free, trying to make AI as affordable and as accessible as we can. So check out b2bsummit. ai. registered for that event again, coming up June 6th

[00:03:26] Paul Roetzer: and then, uh, again, uh, the piloting AI course series. If you're new to the show and haven't heard about this, or if you've been with

[00:03:35] Paul Roetzer: us before and haven't had a chance to look, take a look at it. Piloting AI is a collection

[00:03:38] Paul Roetzer: of 18 on demand courses that's designed as a step by step learning learning. path for beginners at all levels from interns to CMOs. More than a thousand professionals have registered for this

[00:03:50] Paul Roetzer: certification series since it first launched in December 2022. The 2024 series is fully updated. It includes more AI technology demos and [00:04:00] vendors, revised templates, a brand new generative AI 101 course, and more.

[00:04:04] Paul Roetzer: Mike and I went through and updated all the content and re recorded everything at the end of January, 2024. So it's fresh. It's about nine hours of content

[00:04:13] Paul Roetzer: covers everything you need to know in order to begin

[00:04:16] Paul Roetzer: piloting AI in your role and in your company, and it does include a professional

[00:04:20] Paul Roetzer: certificate certification upon passing the final exam, uh, not just for individual learners, you can do entire teams, there's special pricing options for, uh, team purchases.

[00:04:31] Paul Roetzer: So check that out at pilotingai. com. You can use pod 100 promo code to get a hundred dollars off. Uh, and so again, pilotingai. com. If you're looking

[00:04:41] Paul Roetzer: at team licenses, be sure to reach out to Cathy and our team through the online form.

[00:04:46] A quick background of the show

[00:04:46] Paul Roetzer: Okay. So, uh, episode 100, quick backstory. We've, we've told parts of this story before on the podcast, but we have so many new listeners every week.

[00:04:56] Paul Roetzer: Kind of a quick rewind, where did the podcast come from? [00:05:00] So the podcast formerly known as the Marketing AI Show, many of you are with us from our origins as kind of more of a marketing podcast. The premise when we first launched the podcast back in like, oh gosh, I guess MAICON 2019 was the origin, origin of the podcast.

[00:05:16] Paul Roetzer: And then what we tried to do in the initial going, like first

[00:05:19] Paul Roetzer: 10 or so episodes, was I would just interview people in the AI industry. But what became challenging over time was I wasn't very good about

[00:05:27] Paul Roetzer: consistently So it took time to, you know, find the people to interview, coordinate the interviews, prep for the interviews.

[00:05:34] Paul Roetzer: And so we just weren't getting it done. I personally wasn't getting it done. And then Around, uh, September, so 2022, I'd approached Mike and I was like, listen, man, there's so much going on. We're

[00:05:48] Paul Roetzer: sharing these links back and forth all week long, like, and we don't do anything with it. Like if Mike had time, he would turn, you know, stories into articles on our site.

[00:05:58] Paul Roetzer: But even that, we were having trouble, like, [00:06:00] staying consistent with. We were doing a lot of republishing of past, like, tips and tools and tactics and things like that, which is great. But we just, we felt like we needed more original, fresh content with a unique perspective, like to try and bring something valuable to the, to the story.

[00:06:16] Paul Roetzer: So in October, 2022, we launched our first weekly episode of the Marketing AI Show. So episode 20 of the podcast was actually the first one in that weekly format that everyone has kind of, you know, gotten used to. So. For some context, in 2022, that entire year, we had 4, 800 downloads of the podcast. Now keep in mind, when we launched this in 2022, I didn't even know what the KPI was for a

[00:06:44] Paul Roetzer: So we were not doing this as like some major marketing strategy, like let's go build this massive audience and drive traffic. growth through this channel. It was a storytelling thing for us.

[00:06:55] Paul Roetzer: Like let's tell the story each week and then let's use that to create original [00:07:00] content for the blog. And then we record the videos and we can distribute that through YouTube.

[00:07:04] Paul Roetzer: And like, basically we can, you know, start diversifying our channels. but it was really a content play for us and a storytelling play. So 2022, 4, 800 downloads, 2021, the year prior there was 1, 600. In 2023, I

[00:07:20] Paul Roetzer: I think it was over 150,000, 2024 we're on pace for 350 to 400,000 downloads. So just remarkable growth.

[00:07:29] Paul Roetzer: And over time we started realizing, wow, this is the most valuable channel we have. Like the ability every week to not only put fresh content out there, but for Mike and I to step back and actually think about what's happening. And so I've said on the podcast before and,

[00:07:46] Paul Roetzer: and Mike, I'm sure you would agree, like.

[00:07:48] Paul Roetzer: This forcing function of us doing this every week is the most valuable thing we do for ourselves. Like, I'm, I'm thrilled that you all get value out of the podcast, but the [00:08:00] reality is like, we would probably force ourselves to do this there

[00:08:02] Paul Roetzer: was still only 5, 000 downloads a year, because we actually synthesize what's happening and we try and make sense of it.

[00:08:10] Paul Roetzer: And then we develop a point of view that carries through into our online courses, the workshops we teach, the presentations that Mike and I give, the limited consulting work we do. Like this has become a really, really valuable thing for, for me, for Mike, for our organization and, and, you know, luckily for all of you as well.

[00:08:28] Paul Roetzer: So that's kind of just a quick background. I wanted to kind of touch on a little bit before we got into this, but. again, the idea for this 100th episode was, let's make this about you. Like, what is it that's on

[00:08:41] Paul Roetzer: your mind? answer your questions. And so, as I said up front, we have more than a hundred questions submitted.

[00:08:46] Paul Roetzer: Uh, we've curated it down to about 25 or so. We're going to try and get through over the next, you know, 45, 50 minutes. And with that, Mike. let's get to the questions.

[00:08:57] In your 100 episodes of the show, what is the most stand out moment for you in terms of AI beginning to redefine key aspects of people’s future of work? What are some of the key points of the journey so far as revealed through the podcast?

[00:08:57] Mike Kaput: all right, Paul. So like you [00:09:00] said, we got a bunch of questions here. Uh, we solicited these through a form that we promoted to the audience, through the podcast, on our website.

[00:09:07] Mike Kaput: Basically people just submitted whatever questions they had about AI. Didn't have to be about AI in marketing or business, though many of them were. And with each of them, we asked people if we could share their name, uh, as we read out questions. So for the ones where that's relevant, I'm going to do that.

[00:09:24] Mike Kaput: I'm going to apologize in advance. I'm going to try to pronounce your name as well as can. So please, uh, have a little understanding. but I will go ahead and introduce the person by first name and then also read question for Paul, and you take it away. So first up, we have a question from John and he said, In your hundred episodes of the show,

[00:09:50] Mike Kaput: What the most standout moment for you in terms of AI beginning to redefine key aspects of people's future work?

[00:09:59] Mike Kaput: What some of key [00:10:00] points of the journey so far as revealed through everything kind of looked at on the podcast?

[00:10:05] Paul Roetzer: Wow, that's a, that's a far reaching one to think about. I don't know. I, so I, I've had this belief for a while, probably back to the origin of, you know, October 2022 when we really started doing this, and we wrote about it in the book. I think, That it's going to be a bit messy that, that as AI is adopted, more deeply into enterprises, cause I feel like we are just at the very beginning of the AI adoption curve in enterprises.

[00:10:38] Paul Roetzer: I do think there's going to be. Disruption within a lot of industries to knowledge work. And I think that could mean some job loss. I do think it will create amazing new career opportunities for people

[00:10:54] Paul Roetzer: as well. I just don't know that that's going to happen as quickly as some of the job disruption, [00:11:00] and I would say over the last like 80 or so episodes, since we started the weekly format. We've talked about a lot of different research reports and articles and podcasts we've

[00:11:11] Paul Roetzer: listened to and videos we've watched related to the workforce and the economy. And I don't know that my position has changed much since October 2022. I still don't feel like economists largely are

[00:11:31] Paul Roetzer: preparing. People for the disruption, but I think it's because they don't necessarily understand it themselves, because I think to understand the impact on

[00:11:40] Paul Roetzer: future of work, you have to have a reasonable estimation about what these models are going to be capable of in the next one to two years. And so I just feel like we need to.

[00:11:52] Paul Roetzer: Prepare for a number of contingencies. I think if it ends up great and we don't have a job loss, a net job loss, and [00:12:00] everyone's life just gets better, then wonderful. Like I hope that is what happens. But I think there's enough of a chance that it's not that clean and amazing in the near term that we should at least prepare for the idea.

[00:12:14] Paul Roetzer: That in some industries, there's going to be disruption to knowledge work. There's just going to be fewer humans needed to do the current,

[00:12:23] Paul Roetzer: roles that are asked of them. And until we create the new career paths or until organizations figure out how to function when they can be so efficient and so productive, there's just a chance that it's not going to be Be all sunshine and rainbows when it comes to the economy and the workforce.

[00:12:42] Paul Roetzer: So yeah, I think that that's kind of where I'm still at today is that we should be preparing.

[00:12:48] Paul Roetzer: for the idea that I think we have time still to prepare in most industries. And this is why I encourage people to do these like AI impact assessments, like look at the individual roles in your company and your [00:13:00] team in certain departments and try and project out 12 to 18 months from now.

[00:13:05] Paul Roetzer: What do those roles look like? And do you have as much demand to keep as many people as you currently

[00:13:10] Paul Roetzer: have employed, or if demand's going to stay flat and you don't need as many people, what are you doing now? Can you upskill and reskill your team? do you just reduce the number of new people you hire and you, you try and find ways to adapt?

[00:13:25] Paul Roetzer: with the existing staff. Like, and that's the part I'm worried about that just not enough corporations are having those conversations. And I just feel like every company should be working on contingency planning and looking at different models when it comes to the workforce.

[00:13:40] If you could ask Sam Altman one thing and have him answer 100% honestly, what would you ask?

[00:13:40] Mike Kaput: I love this next one. This is from one of our listeners, Tilly, and they ask if you could ask OpenAI CEO, Sam Altman, one thing.

[00:13:49] Mike Kaput: And have him answer 100 percent honestly, what would you ask?

[00:13:55] Paul Roetzer: Okay, this is one

[00:13:56] Paul Roetzer: I've actually thought before.

[00:13:58] Paul Roetzer: So I was glancing these [00:14:00] questions this morning we

[00:14:01] Paul Roetzer: started, and I went and a list of questions that I have actually, about related to this exact one. So I'm gonna, I don't even know if I could pick just one.

[00:14:12] Paul Roetzer: okay. I'll do the one. I'll see if I want to throw a couple these other ones out So the first is, I would him, OpenAI has championed approach of iterative deployment and gradual transition a world AGI, so society has time

[00:14:28] Paul Roetzer: This is like fundamental to OpenAI. This is why they put ChatGPT in the world. It's why they debuted Sora. It's why they're, you showing voice Like they try and release things. that governments

[00:14:39] Paul Roetzer: and society have time prepare for what's to be possible. This is all fundamental to their, do everything. So my question be,

[00:14:47] Paul Roetzer: happens if another company or government doesn't share gets there first? So this is like One my fundamental challenges today with like open versus closed source, these [00:15:00] that to be shepherding safe AGI versus, you others. It's like, you're not doing this in isolation.

[00:15:07] Paul Roetzer: So if. let's a say Anthropic, all of a sudden claims that they're there, that they have AGI. What does OpenAI Do they throw iterative deployment out window they give us 6? Like,

[00:15:19] Paul Roetzer: I I don't know. And, and, and I don't know that, And he have like really honest that question I'm not so sure that they really think ahead. So like another question I would ask, that sort of plays this out is in, in blog post Sam published called Planning for AGI and Beyond, he wrote, the first AGI will just point along continuum of intelligence.

[00:15:45] Paul Roetzer: We think it's likely progress will continue from there. Possibly sustaining the progress we've seen the past decades for a long time. my question to him would then do you ever stop to personally process and visualize what that future would actually mean to [00:16:00] society and humanity, or is it even too abstract him contemplate?

[00:16:03] Paul Roetzer: So he's for years pushing idea of AGI is coming going to build else builds while we're at it. Has he ever stopped to think about like, that actually mean? Other than, yeah, we're going to need universal basic income and, you know, You know, going to be great.

[00:16:17] Paul Roetzer: We'll find some new roles for people. Like just don't, I've never heard an interview of these AI research lab leaders, these frontier model leaders has given a clear vision of the world looks like when we get there. I would want to know that.

[00:16:36] Paul Roetzer: right.

[00:16:36] What are some of the most effective AI tools available today for small and medium-sized businesses looking to optimize their operations?

[00:16:36] Mike Kaput: This next one comes from Anthony and they ask, what are some of the most effective AI tools available today for small or medium sized businesses looking to optimize operations?

[00:16:49] Paul Roetzer: Yeah,

[00:16:51] Paul Roetzer: and Mike, if have thoughts on this one, jump in on it as well. Like, what I always tell people is, I would at [00:17:00] industry you're in what

[00:17:01] Paul Roetzer: component of operations you're specifically thinking about. And I would go and find tools for, for those, like, for example, you may be looking at, you know, HR, finance, accounting.

[00:17:14] Paul Roetzer: Like I'm trying to find AI tools to help with performance and reporting analysis, automation of financial reports every week, where just get a narrative the CEO, like a fundamental, like here's happening, here's answers to 10 questions. I'm looking at it as that and a small business.

[00:17:31] Paul Roetzer: We have employees. so I'm, think about it from that perspective, but I honestly wouldn't, underestimate ChatGPT slash Gemini's ability to help answer this question for you. So what Mike and I continuously found is if take this kind of question and you Tailor prompt, like almost think about it as like you're talking to a, like a a top consultant in your space and And,

[00:17:57] Paul Roetzer: talk the, the AI that way and say, [00:18:00] Hey, listen, know, I need help figuring out ways as a small medium business in X industry.

[00:18:06] Paul Roetzer: To leverage AI to my operations and maximize my profit. I've given the example of how did this with a friend mine, who's a dentist. And, know, we used it a way to and out how to maximize, the organization when insurance rates were going up and cost of goods were going up and I'm not dentist, so I have no

[00:18:28] Paul Roetzer: idea, but like, I'm able to craft prompt ask right question chatGPT and get a really good response.

[00:18:34] Paul Roetzer: So that to me is. would, on your interest, I would go in there say, Hey, I'm in the accounting profession. I'm in the legal profession. I'm in retail, whatever it is. here's some of challenges I have currently in my operations. What are ways I could leverage AI? And please include example tools.

[00:18:49] Paul Roetzer: Perplexity may give you a better answer if you start asking for like specific recommendations and thing that,

[00:18:55] Paul Roetzer: I create that prompt then I would, I would test it across couple of different language models. And that's [00:19:00] high level. A takeaway for anyone listening today is like.

[00:19:04] Paul Roetzer: Don't just, because you're paying 20 bucks a month, only use ChatGPT. Like Mike and I find all the time that some prompts, you just get a better output in other models. so we'll test these things all the time. So don't Mike, do you have any other thoughts on that one, anything you've tried?

[00:19:20] Paul Roetzer: Yeah, I would just say. Somewhat related, a big bottleneck for anyone, but especially a small business is just limited bandwidth and focus on the things.

[00:19:31] Paul Roetzer: And I would say I probably wouldn't even be looking for dozens of different tool ideas unless I was very confident that me or my team already absolute rockstars prompting and getting value out of. Uh, GPT 40, Gemini, and or Claude, because those three together the right prompting and context can get you very, very, very far.

[00:19:55] What’s a good way to assess tools with so many options? Do you use an assessment framework?

[00:19:55] Mike Kaput: Okay, Katharina asks, what's a good [00:20:00] way to assess AI tools when there so many options? Do you use an assessment framework?

[00:20:07] Paul Roetzer: Yeah, and this again, Mike, might be a good one

[00:20:09] Paul Roetzer: you to in with own experience But I first at vendor. actually have, and we'll it in the notes. We have an AI tech vendor assessment that we created with the Marketing Artificial Intelligence book. it's on our site.

[00:20:23] Paul Roetzer: It's free download. a Word doc you can download. yeah. But

[00:20:27] Paul Roetzer: what we recommend there to make sure you look at, like, the vendor, that it's a legitimate AI tech company, they, know, this isn't, know, just a software company that's throwing AI into their messaging, sell some licenses, that a real company with a public product roadmap, point view on AI, It's obviously, uh, being infused into everything they're doing.

[00:20:49] Paul Roetzer: Then you start looking the technology itself and you're looking for specific value for you, making sure you're understanding the use it's going to enable, you're going to want like, if it's going to be [00:21:00] core part of your tech stack, you're to want to look at their onboarding tools, their customer support, in case you need guidance, your team's starting figure out how to use this tool.

[00:21:08] Paul Roetzer: think more than anything, it really just comes down to user stories. And what mean by that is. All We're going go find a podcasting tool. let's our podcast, is fundamental of our overall strategy. We've, we want keep doubling down on podcast, every aspect of it.

[00:21:24] Paul Roetzer: We want to improve efficiency, productivity, creativity, quality of output, like all of So what I would do is say, Okay, here's the three people working on the podcast today.

[00:21:34] Paul Roetzer: Here's the 25 tasks that they do every week to do this podcast. I'm going to go find a tool a tools us improve efficiency, productivity, creativity, quality across podcast those three people in these specific tasks.

[00:21:51] Paul Roetzer: And so if you laser in on. A very specific thing you want achieve, not just, let's just go

[00:21:56] Paul Roetzer: get a tool and let's figure out how to use later. But have a [00:22:00] specific business use case. We can define user story of what their life looks today without the tool. then once understand tool, we can define, okay, 30, days now, here's this is going to improve what they're doing.

[00:22:13] Paul Roetzer: we're going to measure it way. to me is the most important You can get into user reviews and like usual things you would look at technology, but you apply and you have a very specific idea in mind of a campaign or a workflow can benchmark that workflow and can, you can then measure improvement, the way to buy any technology you're going to get value you're going to know if it's not working and you can stop it.

[00:22:40] Please speak about how small and medium businesses can apply AI to their customer data. Should they wait until their CRM providers infuse their systems with AI assistants? Or should they use paid versions of ChatGPT to plug it into the data somehow? How safe is it in terms of data privacy?

[00:22:40] Mike Kaput: So, Jev asks, please speak about how small and medium businesses can apply AI to their customer data. Should they wait until their CRM providers infuse their systems with AI, or should they use paid versions, for instance, of ChatGPT to plug in their data? How safe is all this [00:23:00] in terms of data privacy?

[00:23:01] Paul Roetzer: So I'll work backwards terms of data privacy. All these AI companies, and specifically, you know, the frontier model companies, the the big ones, Google, Amazon, Microsoft, OpenAI, Anthropic, they understand they're not getting enterprise adoption not protecting data. So they're all building that in or have that in terms uh, of use already. Make

[00:23:25] Paul Roetzer: sure your attorneys, you know, Review that though. Just make sure fully clear confident or IT, your organization needs be involved, make that they, sign off on, on that before go putting data in. being said, under the assumption that data is safe and you can put that kind of stuff into models.

[00:23:44] Paul Roetzer: I have personally seen some, some pretty success using ChatGPT team slash plus license. With data, like it's getting really at data analysis. just introduced some new capabilities

[00:23:59] Paul Roetzer: weeks [00:24:00] around this. it used to be called what? Code Interpreter. Then it was Advanced Analysis.

[00:24:05] Paul Roetzer: Now I don't know what it's called ChatGPT anymore. but I think that the main providers Google, Microsoft, Anthropic, Amazon, OpenAI, uh, Meta, I guess, eventually, they're to build this data analysis capability right in. to these platforms. So I think six to 12 months from now, it's just going to be a common within there.

[00:24:26] Paul Roetzer: And you're going to have analysis capability that previously would have had to hire outside for, go get a PhD for.

[00:24:33] Paul Roetzer: that seems like a direction we're definitely heading. I'm starting to test those things myself. but if you have the budget, I would talk to a PhD. You know, a data analyst, a data scientist, that they understand ways to, you know, organize and structure the data, clean the data, that it has more value to you down the road and all, as you start spreading out AI applications you're looking at.

[00:24:58] Paul Roetzer: [00:25:00] certainly For all of us, if we can access the data within our CRMs use that, uh, that's a great starting point. And Salesforce is doing that, HubSpot's doing that, all the CRM companies know that that's a key feature

[00:25:11] Paul Roetzer: as well. So I would to your existing tech stack companies. would confirm with your IT.

[00:25:16] Paul Roetzer: Slash that you're, good to submit, you know, data into ChatGPT or whatever, know, Gemini, whatever license you're using. I would start experimenting use cases within those. That's Mike and I are doing that right now where we're putting data in and trying to, you know, see what it out.

[00:25:32] Paul Roetzer: But will say they, they can still hallucinate even the data side. you have to have some understanding of your own data and you have to know what to look for to make what it's telling you right. uh, because otherwise you, you could rely on

[00:25:45] Paul Roetzer: some false data.

[00:25:47] Do you have any success stories of a business adopting GenAI that wouldn't necessarily be an obvious company to do so? What's your favorite story so far?

[00:25:47] Mike Kaput: Heather asks, do you have any success stories of business adopting Gen AI that wouldn't necessarily be an obvious company to do so?

[00:25:56] Mike Kaput: What's your favorite story so far?

[00:25:59] Paul Roetzer: a [00:26:00] few episodes we talked about Moderna and OpenAI. I loved that one. So that's episode 95. If you want to go back listen

[00:26:07] Paul Roetzer: to that main topic. And then actually I'm in the midst of building our new scaling AI series, which is this eight series that we're going to be launching um,soon.

[00:26:17] Paul Roetzer: And one of the courses is called AI emergent organization. in that wanted to go companies that are doing this, that are kind of building these AI emergent versions of their company, they're infusing AI. And I asked Mike to help me with the research. he just like weeks ago went and built a database of companies that we thought based on our research, doing a job.

[00:26:41] Paul Roetzer: I'm actually gonna this one back to you, Mike. And, if there was any companies that really stood out to when you were doing that research.

[00:26:49] Mike Kaput: two stand out to me, certainly not the only examples we found, but I just think they're unique in different ways. the first is a company called Klarna, which does a bunch of like [00:27:00] e commerce and payments.

[00:27:01] Mike Kaput: And Klarna has naturally a ton of customer service chats. Now this is a pretty obvious area to start considering applying AI, given the results you can get with AI in customer service areas. But I am really impressed just the scale which they appear to have done it. They've released a bunch of information on this.

[00:27:20] Mike Kaput: According to them, They already now have an AI assistant that has had 2. 3 million conversations or two thirds of Clarna's customer service chats and doing the equivalent work of 700 full agents and has, is on par with human agents in regards to customer satisfaction scores. So it's basically estimated to a 40 million profit.

[00:27:44] Mike Kaput: uh, profit.

[00:27:46] Mike Kaput: Improvement to Klarna in 2024. Just overall, really impressive in terms of the scale at which they appear to rolled out AI for this particular use case. Now, another one is [00:28:00] Publicist Group. And I mention this just because we did cover it on the podcast. This is a early days one. I more want to highlight for the sheer Magnitude of what they're trying to do and what is required.

[00:28:13] Mike Kaput: Now, Publicis is a big agency, group of agencies, one of the leaders in the space, and they are investing 326 million in AI the next three years to basically build a centralized brain. For their company, that AI is going be a layer over all of their data and help all of their people do everything that they do in a day to help service their clients, to help earn new business, to help the agency do all creative and strategic tasks it does.

[00:28:43] Mike Kaput: So, you know, us, Paul, coming from the agency world, that one jumped out as well. They're not just applying a few little use cases here and there, they're reinventing the company from the ground up. with AI.

[00:28:54] Paul Roetzer: Those are good ones.

[00:28:55] What tools does the MAII team use in your workflow? What GPTs has your team built that you find most valuable?        

[00:28:55] Mike Kaput: All so Alec asks, what tools does the [00:29:00] Marketing AI Institute team use in your workflow?

[00:29:02] Mike Kaput: Any GPTs the team built that they find valuable?

[00:29:07] Paul Roetzer: don't you go on what tools you use? Cause I say I, I'm more an experimenter. know, I, I obviously use ChatGPT, Claude, Perplexity, uh, Gemini are of my, my main ones, but you're running content. So you could

[00:29:21] Paul Roetzer: probably get more specific on you're

[00:29:23] Mike Kaput: Yeah, sure. I'll mention a few that are really valuable for our team. So, Claude3Opus has been critical for any type of, Uh, brainstorming or first drafts of any type of content or copy, Claude, like Paul mentioned, is just a model that's comparable to ChatGPT and Gemini, but for whatever reason does writing much, much better in my opinion than some of those.

[00:29:47] Mike Kaput: Uh, Gemini 1. 5 Pro, which is the latest version Gemini available Gemini Advanced, uh, paid version, paid plan at 20 bucks a month, is super, super helpful, it's got an incredibly [00:30:00] long context window, so can dump in literally hundreds pages of material and start querying that data, using it in various ways, learning from it, that's been helpful.

[00:30:10] Mike Kaput: Absolutely essential what we do. And then there are things like another one our team loves. That's just saved an enormous amount time is OpusClip, which takes our long form video, automatically splits it up into short form video, which is a critical format that we had kind of. under invested in previously because it a really long time to create those clips manually.

[00:30:33] Mike Kaput: And I would say Descript

[00:30:34] Mike Kaput: is probably like the biggest one, so that's what use our podcasts, for our webinars, for transcription, for production, audio and video production. They've, I think, a new AI feature that does the clips thing too. So that's like absolutely core. And then there's the GPT question.

[00:30:52] Mike Kaput: So haven't personally, infused any GPTs my workflow, but will say, There's the one [00:31:00] talked numerous times that I just haven't built yet is the generative AI policy. So, you know, people through building a generative AI policy. episodes talked the idea of an AI profiler.

[00:31:10] Mike Kaput: In case, I was doing it for an a journalist where I just You know, went in and kind built a to give me everything I need to know about that journalist, but you could do the same thing for, know, sales conversations, job interviews, things like that, where you basically just build a profile on someone where you tell to go any, you know, information that's available to personality profile based on their social shares.

[00:31:32] Mike Kaput: Find anything they've written, stuff like that. So that's one we turn into a, uh, a GPT. And then the other one that was testing and building these scaling AI courses is actually a AI course assistant. And so, you know, got it as research assistant. I have editing

[00:31:47] Mike Kaput: things. I have, you know, it's ID8s with So I just a single in ChatGPT, in Gemini. Perplexity,

[00:31:57] Mike Kaput: I'm asking with [00:32:00] things. so I could easily take that and that a GPT as well. But right now I'm just as a separate chat in each of those platforms.

[00:32:09] How should leaders determine whether to concentrate AI efforts on select high-potential individuals or to broadly distribute AI training and resources across their organization?

[00:32:09] Mike Kaput: All So Will asks, uh, kind of, let me go through this question here.

[00:32:15] Mike Kaput: I've noticed varying opinions who benefits the most from AI. A high level AI consultant I know is advising CEOs to focus on a small group of employees with more ideas than time. Meanwhile, many discussions emphasize spreading AI knowledge and skills across the whole enterprise. Given these differing approaches, how should leaders determine where to concentrate AI efforts?

[00:32:38] Mike Kaput: Should it be on those select high potential individuals, or should it be more broadly distributed when you talk about AI training and resources?

[00:32:47] Paul Roetzer: I, this one, you know, I'm just of wracking my brain here, met with so many different companies, so many different sizes, industries, and I don't know that there's a right single approach to this. I don't know if there's [00:33:00] one answer to question.

[00:33:01] Paul Roetzer: I think is largely organization dependent. What I mean by that is, you know, organizations have so much red tape, like so many obstacles

[00:33:11] Paul Roetzer: to doing adoption, that getting a small group of people is their only choice, like to this as tight as possible, as controlled as possible, only way they're going to

[00:33:21] Paul Roetzer: get permission to do these things, so that might be their only option.

[00:33:26] Paul Roetzer: think that, When we look how AI should be adopted, like I think leading organizations going back to Moderna example from episode 95, decentralization. It's empowering your entire team experiment, to find the best use cases, to share the best prompts. Like. That's how companies are going really innovate,

[00:33:48] Paul Roetzer: know, this and capability in a few select people.

[00:33:51] Paul Roetzer: It'll make an impact, but it just seems to me it's probably not ideal long term. Now, from a research [00:34:00] perspective, is,

[00:34:05] Paul Roetzer: from 2023, where they benchmarked. was 700 consultants, I think. they benchmarked their performance before gave them GPT then after.

[00:34:17] Paul Roetzer: And they there was like very little training of how to use it.

[00:34:19] Paul Roetzer: Like they didn't even do full blown, you know, onboarding the way you should. what they found was the, the consultants

[00:34:28] Paul Roetzer: that performed on the benchmark. before GPT saw a much greater improvement in performance.

[00:34:37] Paul Roetzer: I it was like 41 percent improvement in their performance. The high performers pre benchmark, saw a smaller It was like 17%. Now they both improved. So like your A players A plus players, basically. Your B and C players. moved up to like A player status. So the and C [00:35:00] players are making this much larger jump.

[00:35:01] Paul Roetzer: Well, that would argue distribution of. Features and benefits across the whole team, not a small group people,

[00:35:08] Paul Roetzer: because A players are going improve and they're, they're turn going to drive productivity performance for organization. But if distribute the capabilities across everyone and teach them to use all of a sudden your entire employee base levels up and your organization rise with that.

[00:35:27] Paul Roetzer: So I think that the better play is.

[00:35:31] Paul Roetzer: Democratization of literacy and technology within the organization, but it's not going be the reality every company. They're not going to be able to that. so then I would say a small group better than nothing. Like whatever you need to do to accelerate, it.

[00:35:48] Paul Roetzer: And if you can get everyone involved, I think you should. I

[00:35:53] How do people use AI in their daily lives? Is it primarily using tools like ChatGPT or Perplexity or is there something beyond that which can help save time or solve daily problems.

[00:35:53] Mike Kaput: Sinandoh asks, how do people use AI in their daily lives? it primarily using tools like [00:36:00] ChatGPT or Perplexity, or is there something beyond that which help save time or just solve daily problems?

[00:36:05] Paul Roetzer: like. Hmm. had a, Hmm. episode. We were going to talk about something related to this, you know, I think there's this question right now around AI adoption. We're seeing, like we saw Microsoft LinkedIn study recently said.

[00:36:21] Paul Roetzer: 75 or 78 percent people are using Gen A at and 48 percent of them were in the last six months.

[00:36:26] Paul Roetzer: So you look at it's like, Oh, everybody's using it. But then you go talk real world. And I saw a data recently, it was like 7 percent people are using ChatGPT like even know what it is. And you're like, you can easily step out into the real world and like be with family or friends or.

[00:36:42] Paul Roetzer: know, your buddies who aren't in the marketing world or aren't in tech and, and they're like, yeah, I don't know. I don't really use it. Like, so I, it's, it's, there's confusing signals right now like whether or not society has it, uses it, or wants it. My argument is We've all been [00:37:00] using AI dozens times

[00:37:01] Paul Roetzer: the last 10 years.

[00:37:03] Paul Roetzer: Like if you use TikTok, you use your iPhone, if you drive in Tesla, you use Google maps or Amazon or Spotify or Netflix, like we're using AI, we just don't know it. then the question becomes, well, who going out and seeking specific AI tools like a ChatGPT or Perplexity? I think that might be fewer they're college students.

[00:37:26] Paul Roetzer: I think college students are racing to use these things. I think people on like TikTok and Instagram for reals, they're going and seeking AI tools that help them do creative stuff, but you know, in terms of world, I don't know that it's that prevalent, like a couple of examples I think about is, again, I'm in this obviously, but I use, you know, Voice all the time.

[00:37:48] Paul Roetzer: So not just talking to like, to do text message, like voice to text there, but to do to create documents, to send emails, like you speak much faster than you type. so I have [00:38:00] started using voice capabilities in all of things. other things personally used it for is kids homework. So my kids fifth and sixth grade going into sixth and seventh.

[00:38:08] Paul Roetzer: And they all, they all time. I don't know the answers to, I don't even know how to help them, but it's a coding question daughter has, or a math question or question. Like Mike, and I joked, we're writers by like to school for writing, but you asked me like technical. how to diagram a sentence or like, know,

[00:38:29] Paul Roetzer: predicate noun is like, what I was like, I don't know. It's been 20 years since I studied that. I just know how to use words. I don't how to explain to why

[00:38:36] Paul Roetzer: I did it.

[00:38:37] Paul Roetzer: And so I'll use perplexity all the time help me help them.

[00:38:42] Paul Roetzer: That's me seeking an AI to help solve something. The other one get asked questions from friends or family who own businesses industries I don't

[00:38:50] Paul Roetzer: understand. And like, I usually have to stop and do a bunch of research. Now I just create a and I go perplexity I'm like, Hey, I'm trying to advise somebody on this.

[00:38:58] Paul Roetzer: Here's business. Here's the [00:39:00] challenge they're having. What would I do? And then gives to now as a strategist, as a marketer, as an entrepreneur, I can assess that output, it's good and know whether or not to send it to my friend or family. but I think those are the kinds of things that I don't of that many people on average doing it.

[00:39:16] Paul Roetzer: I'm not family and hearing. Aunts and uncles that Oh yeah, I was using ChatGPT So, I

[00:39:24] Paul Roetzer: don't know, like would us it's not prevalent as we may think it is in bubble we all live in.

[00:39:29] Looking at the next year, five years, and 10 years, what do you think the adoption of AI Technology will be for most businesses? Do you see it coming in for more skilled labor-type jobs as well or being used to assist skilled labor jobs?

[00:39:29] Mike Kaput: So Chad asks, looking at the next year, five years, ten years, like, what do you think the adoption of AI technology will be for most businesses? you see it coming? More for skilled labor type jobs as well, or just being used assist like labor jobs.

[00:39:46] Paul Roetzer: Yeah. So I,

[00:39:48] Paul Roetzer: a thoughts here. we will put it in the show notes, the law distribution, referenced a number times. I wrote I think in early 2023, this idea that, [00:40:00] all have access to same stuff, whether you're lawyer, accountant, an engineer, HR professional, a consultant, whatever you're doing for a living, a writer, a teacher, one us can go get the same for 20 bucks month.

[00:40:13] Paul Roetzer: It's kind of like the like if you, if you 500 or 700 whatever it is, we all have access to exact same technology, whether you're billionaire or fresh out school making 30, 000 year, stuff's available to all of us. How you use that, the benefit you from it,

[00:40:29] Paul Roetzer: Will not be evenly distributed because some people don't understand it's capable of.

[00:40:35] Paul Roetzer: Some people may not have access to it's shut off company. Even though it's there, they're not allowed to use it. And some people just won't accept what they have give to get Like the privacy side or the data side just not willing to give that information to some company.

[00:40:50] Paul Roetzer: And so don't think it's going to be evenly distributed. I do some industries are going be heavily impacted than others in the near term. [00:41:00] But I, I, at end of the day, like think to years from now, I don't understand how a business functions without it infused across every department of their Like,

[00:41:09] Paul Roetzer: Like you be such a competitive disadvantage. It would like, I don't know how to relate but it would almost like if we went back to 2005 let's say like internet and email starts exploding 99, 2000 range

[00:41:25] Paul Roetzer: 2005 hits and company still doesn't have a website, isn't using email, and nobody in the company uses to search anything. That's basically what it's going to be like three to five years from now, if you haven't fully infused AI. will be at such a disadvantage

[00:41:42] Paul Roetzer: to the

[00:41:42] Paul Roetzer: companies who found ways to apply this general purpose technology marketing, sales, HR, finance, operations.

[00:41:53] Paul Roetzer: So I don't know if companies that haven't deeply infused this three five years from now exist.

[00:41:58] Paul Roetzer: Like, I, I think you're [00:42:00] just going be obsoleted basically. So, and that, you know, again, that three five years is more of an average. industries, it may take seven. I don't know. Some it's going be one, but overall average three to five years, it has to be infused into every function of the business.

[00:42:19] Given the rapid pace of AI innovation and development, how can professionals across various industries effectively stay updated and enhance their knowledge?

[00:42:19] Mike Kaput: Najam asks, given, you know, the rapid pace of AI innovation and development, this can be overwhelming even for those with extensive experience in technology and marketing and business.

[00:42:32] Paul Roetzer: Given that, how can professionals across various industries effectively stay updated and enhance their knowledge, especially Without, you know, a serious tech background.

[00:42:43] Paul Roetzer: I don't know about you, Mike, it's overwhelming for me

[00:42:48] Paul Roetzer: like, I have shared this before, but again, you're a new listener, the way Mike and I this podcast is have a, uh, Twitter thread, that I get notifications for there's probably, I know, [00:43:00] 50 people brands I get notifications I have lists, that's one but a filter beyond that is notifications, media outlets, things like that. That is 90

[00:43:11] Paul Roetzer: to 95 percent of what we talk about on this show and the things I read every week come that notification list. So the vast majority of the way I curate information consume it is through notifications on Twitter.

[00:43:25] Paul Roetzer: would, the a month I give Twitter, I would pay the 2200 or 22 just notification access. that's valuable me. So, I've created these different filters just to get down to the things think matter each week. Then, Mike takes all of those things, 30, 40 things each week, he curates those down the ones that going to actually talk about.

[00:43:52] Paul Roetzer: He picks the main topics. fire items sends to he says, this look? Are we, we to go? I maybe have few notes [00:44:00] like, yeah, move this one here. swap this or let's make the topic, whatever. generally speaking, that's it happens. And Sunday night or Monday morning, have to actually for the show.

[00:44:10] Paul Roetzer: Like now going and like deeply thinking about these things. And sometimes I do it 30 minutes, sometimes, know, an hour two hours. But. time is therapeutic, but it is like overwhelming sometimes. Like there's sometimes on that Sunday night where like, don't even how I'm going to be ready to talk about it. So

[00:44:29] Paul Roetzer: like they're so, so deep and so far reaching.

[00:44:33] Paul Roetzer: so I say all that say, you. I totally get this is crazy and overwhelming and abstract sometimes terrifying every once in a while exciting, but I think

[00:44:47] Paul Roetzer: way I advise people generally is. The fire hose Mike and I drink from each week is not advisable.

[00:44:56] Paul Roetzer: it is daunting sometimes, and you have get really [00:45:00] good compartmentalizing information so you still sleep at night.

[00:45:04] Paul Roetzer: for most people, The opportunity to pick a thread about AI that matters to your role you have now, the role you want to have in the future, or the value want create this knowledge. So if it's AI the legal industry, AI for engineers, or AI in the retail industry, or like a specific component of AI, like the impact on the workforce or impact on education, do that. Listen to our podcast once a week. Get our newsletter, maybe couple other newsletters. There's a few other that Mike I love that we subscribe to. That's enough. And like in for hour two week and try and the macro level, but spend 95 percent of your time the micro, like narrow.

[00:45:53] Paul Roetzer: With the AI expertise, cause what the world is to need lot more people who have AI expertise in a specific [00:46:00] domain. the other thing I would say here is we have the AI mastery membership. If you're familiar that, put the link in the show but we have an annual membership like a subscription program.

[00:46:10] Paul Roetzer: And Mike and I, as part of that do a quarterly report. So we'll actually a dedicated one hour with that group, each quarter to kind catch up on that. then the other thing say is like. Create an AI council be a part of an within your organization and have one of the pieces of council

[00:46:28] Paul Roetzer: be meeting once a month to talk about what's going on, what the trends and what, how do they matter to your organization?

[00:46:34] Paul Roetzer: So I, to summarize, focus on a AI like dip in once or twice a week to the macro level, unless you really, really want to go deep and, and,

[00:46:47] Paul Roetzer: and have the firehose effect.

[00:46:50] Paul Roetzer: So some more kind of career related questions here.

[00:46:53] How can I future-proof my career in AI, ensuring that my skills remain relevant as the field evolves? What are the best certifications for someone looking to gain expertise in AI and machine learning?

[00:46:53] Mike Kaput: Tyler says, I'm a 40 year old PR and communications professional. How can future proof my career in [00:47:00] AI, ensuring that my skills remain relevant as the field evolves?

[00:47:03] Paul Roetzer: What are the best certifications for someone looking to gain expertise in AI?

[00:47:10] Paul Roetzer: so again, I don't want this to sound self promotional, but like what we've built the Institute is meant to be a journey people. So we envisioned years ago, what would it take to achieve mastery of the topic of

[00:47:24] Paul Roetzer: AI? And then I've been working on building this learning journey for the last three years, basically.

[00:47:30] Paul Roetzer: So for us, intro AI, like fundamentals of AI. it's piloting AI, which is the core series I mentioned the beginning. That is okay, you understand fundamentals. figure how to apply this to your career. Go deeper like the macro of what is AI? Why it matter? the key players?

[00:47:49] Paul Roetzer: do I build, you know, support for it in my organization? Use cases, tools. do I adapt learning journey? that's piloting AI

[00:47:59] Paul Roetzer: is the next step in [00:48:00] that learning for us. How do know, do I now this knowledge figure out how to operationalize in my career and within my organization?

[00:48:08] Paul Roetzer: And then the mastery membership I mentioned is kind of the, how do I now up on everything? So that is. Truly like the

[00:48:15] Paul Roetzer: vision I had like years ago, we've, finally have brought all this life. That being said, we're just one option. We and give diverse points of We and be as objective possible

[00:48:27] Paul Roetzer: from all angles let decide what the information.

[00:48:31] Paul Roetzer: But we learn all of other. Different sources, like Coursera has a ton of great stuff. Like what's Andrew, Andrew Oong's is AI for Everyone. It's like phenomenal course from Andrew Oong. And I think it's free. Oong is the

[00:48:45] Paul Roetzer: founder, co founding member of

[00:48:47] Paul Roetzer: Google Deep Brain or Google Brain before he left and on and he Coursera and he's amazing AI leader.

[00:48:55] Paul Roetzer: There's a ton of stuff on LinkedIn learning. There's some amazing people to follow on [00:49:00] Twitter that, you know, can really curate information. So I think you got to kind of

[00:49:04] Paul Roetzer: find. again, those threads, find the who specialize in PR and communications, like

[00:49:10] Paul Roetzer: whatever you want to do, find the influencers, thought leaders who are talking about that topic there, and And then and find these other courses.

[00:49:17] Paul Roetzer: In terms of specifically around certifications, I don't know, than the ones we offer. think LinkedIn Learning both offer certificates based on completion. Google offers free AI training. They've got some very approachable AI business. IBM has some stuff, Amazon has some stuff.

[00:49:33] Paul Roetzer: So I would check with all those, know, frontier companies, cause they're AI savvy workforce.

[00:49:40] Besides sharing on LinkedIn how I’m using AI, are there other ways to showcase my AI knowledge while looking for a job?

[00:49:40] Mike Kaput: Mandy asks, besides sharing on LinkedIn how I'm using AI, are there other ways to showcase my AI knowledge while looking for a job?

[00:49:50] Paul Roetzer: A couple things come to mind. So in Cleveland, we run an AI in CLE. So CLE is [00:50:00] short Cleveland anyone not Cleveland, for anyone who

[00:50:01] Paul Roetzer: doesn't know that. we have quarterly AI and CLE events. Free

[00:50:05] Paul Roetzer: to attend they're just networking events. We'll get on average a hundred to 120 people and it's just people interested in this topic. I think yourself in those kinds of groups,

[00:50:17] Paul Roetzer: whether they're in person or virtual. Find where people like you, like minded, are congregating and start networking and building relationships with those people. The other thing, and this is like advice I would give, you back the day to college students when we doing like interviews for the agency, volunteer with non profit needs the help.

[00:50:39] Paul Roetzer: Like, Everybody needs to figure this

[00:50:41] Paul Roetzer: out. So find organization you care about, whose cause means something to you and offer to help them build an AI strategy, you know, use cases, find some free or affordable tools that they can use to, know, to drive donations or, you know,

[00:50:57] Paul Roetzer: audience or whatever it is, grow brand awareness.[00:51:00]  so apply what learning in a that benefits society. Like, I think those are, Two

[00:51:06] Paul Roetzer: great ways you do it. Uh, then, you know, that's a very fast way to also then like build a reputation as someone who knows what they're doing and build goodwill. And almost

[00:51:15] Paul Roetzer: all these nonprofits have boards that, you know, have people who are connected in, in, your community, industry. So yeah, I would think about a couple of ways to do that.

[00:51:26] What do you think AI’s role will be in strategy work as it evolves? Currently there’s a big emphasis on AI aiding with ops/content gen/repetitive work, but curious about its potential for coming up with business / marketing strategy

[00:51:26] Mike Kaput: Sevde asks, what do you think AI's role will be in strategy work as it evolves? Currently there's a big emphasis on AI aiding with, say, content generation or repetitive work, but curious about potential for coming with business and marketing strategy.

[00:51:42] Paul Roetzer: Yeah, so this is an interesting

[00:51:45] Paul Roetzer: one that's highly relevant, to this morning. So I was, I was mentioning that I was working on, Scaling AI course series. And part that series, [00:52:00] I was developing a prompt to try and help organizations and individuals figure out which tasks AI has the greatest opportunity to help with.

[00:52:08] Paul Roetzer: And strategic planning, which requires advanced reasoning capabilities, is one things that, I was specifically interested in. So What think is going happen is, the next versions of models. We know OpenAI is now in training on their next model. They disclosed that yesterday, which I think already knew, but actually saying happening now.

[00:52:34] Paul Roetzer: they're all going to continue to improve at their ability to do reasoning, to follow of a chain thought, a steps to an outcome. And the example, again, it's I haven't published this yet, but like showed to this morning, too. Gemini 1. 5, I gave it this prompt asked kind of analyze the job

[00:52:57] Paul Roetzer: of a marketing manager was the specific example [00:53:00] gave And I gave different exposure levels like the exposure that role those tasks AI assisting, replacing parts of the work. And one of the ones particular said like exposure given advanced reasoning capabilities. And it demonstrated Advanced reasoning capabilities to create the output that it gave me, and that it understands very deeply what's involved in process of strategic planning, which I was away by, the was this.

[00:53:32] Paul Roetzer: shocking to me. so I think what's going to happen is the reasoning capability is to get really good, really fast. And then people are going start infusing AI into all of strategic planning processes. would start experimenting it now. already probably better than you think it is, the end this year.

[00:53:53] Paul Roetzer: going to be like senior strategist level good. what I saw the I'm referring to [00:54:00] was senior strategist level good. Like if I, when I running my agency, and people don't Mike and I together my agency. I sold 2021.

[00:54:09] Paul Roetzer: If I would have given I gave to Gemini to a senior strategist, I'm saying 15 years experience, no offense to Mike, one of top strategists

[00:54:22] Paul Roetzer: we ever had at the I'm not

[00:54:24] Paul Roetzer: sure I've ever employed a strategist who could have done what it did.  Like, did it in 30

[00:54:31] Paul Roetzer: seconds. Like Mike and other top strategists done it, was week's worth work. It would have taken me a week to do what it output in 30 seconds. And I, checked work, I was like, geez,

[00:54:44] Paul Roetzer: like not did do it, it's really, advanced, really good. So based on what seeing I know research labs working on and the importance of reasoning to them, I don't see how AI [00:55:00] isn't extremely advanced strategy assistant by the end of in, every large language model that may use Gemini, ChatGPT, Claude, all of them.

[00:55:12] Paul Roetzer: think it's maybe the most underrated use case right now. Today's models is a strategy assistant.

[00:55:21] As a former agency owner, what new AI-enabled services (offerings not previously possible before GenAI became available) would you be adding to your client service model?

[00:55:21] Mike Kaput: So William then, kind of with that context of your background as an agency owner, Paul, he asks, what new AI enabled services would you be adding your client service model if you were, you know, running an agency?

[00:55:37] Paul Roetzer: So I'm going to answer this specific agencies, but I'm going to make it applicable to everyone listening, this needs to either outside agency or it needs to be someone internally. So if you're the person internally, I'm about to say is things could be building capabilities around and just doing it in house, which I think is a lot of are going to do.

[00:55:58] Paul Roetzer: large language models, strategy and [00:56:00] implementation. just talked about an example. If your team. if you take the leadership is unaware of Gemini 1. 5's reasoning ability and ability to help plan, they're completely missing major value creation right now without these models getting any better.

[00:56:18] Paul Roetzer: So people who deeply understand these models are not just text, but like multimodal models, what they're of that can build strategies about to use them and then train and implement team.

[00:56:32] Paul Roetzer: Across

[00:56:32] Paul Roetzer: business, all functions of the business do them. Huge. AI education and training.

[00:56:37] Paul Roetzer: You've got to have people who can teach stuff. The fundamentals, the ongoing process. that learning journey I talked about earlier, every organization needs that. And we're going to need people within these organizations or outside agencies, consultants who can help do it. tech integration.

[00:56:53] Paul Roetzer: Again, you look at the script, integrating it, like, you know, the podcast, for webinars, online courses, got to have people [00:57:00] understand deeply the tools so that they can do the integration and onboarding. Change management, massive. There's change management happening around AI in organizations

[00:57:09] Paul Roetzer: we talk to.

[00:57:10] Paul Roetzer: it is going to be required in every organization. Like today, they know what

[00:57:16] Paul Roetzer: they're doing,

[00:57:17] Paul Roetzer: but I don't see how one to two years out every single organization doesn't have some form of AI change management. being implemented. AI agents is sort of like on

[00:57:26] Paul Roetzer: the frontier

[00:57:27] Paul Roetzer: coming thing. ability to work with them, to build them, to have them trained to work together, to envision how they work together, all those things.

[00:57:36] Paul Roetzer: And then just augmented creativity, being able to enhance what

[00:57:39] Paul Roetzer: you're capable

[00:57:40] Paul Roetzer: doing, adding video capabilities, adding image capabilities if you didn't them, audio capabilities, like these the models are going to enable, people need to know how to use them. And there's just very, very low understanding of

[00:57:52] Paul Roetzer: that stuff right now.

[00:57:53] If you were launching a marketing agency today, how would you approach scaling with AI tools?

[00:57:53] Mike Kaput: A few other kind of agency related or adjacent questions here. Gabriela says, if you were [00:58:00] launching marketing agency today, how would you approach specifically that scaling, scaling up with AI tools?

[00:58:08] Paul Roetzer: yeah, so I, I, I'll answer this specific to agencies, but applicable to everyone, the, the way we teach every company, if you want to scale is five steps, education and training. So AI literacy, council, like a body of people who

[00:58:23] Paul Roetzer: have the authority to move this at least, whose opinions are respected or they can support them moving forward. Generative AI policies,

[00:58:31] Paul Roetzer: responsible AI principles, number three. AI impact assessments of team, your partners, your tech stack, your products and services, like is the impact this is going to have in the next to three years? And then fifth is build an AI roadmap. Like to, to scale, you need do all of those things.

[00:58:50] Paul Roetzer: They don't have happen all but you have to have a plan to do all them. literally just like, what is a smarter version everything we do? I think about all the time for the Institute. The Institute is [00:59:00] media, education. Those are like the three. Main arms of what do, AI research and consulting are sort of emerging areas.

[00:59:09] Paul Roetzer: day I think about what's a smarter version of this. time we're going to launch an event, a new virtual summit, we're going to doing more research. I look and I say, okay, would I have done this historically? How could I do a smarter version of this? would think about that every service I launch, every internal process we go through regularly. Every revenue model. And then if I'm from the ground up, I'm, I'm going to say, how do I do with the fewest amount of people possible,\

[00:59:34] That isn't a bad thing.

[00:59:36] Paul Roetzer: Like, so you have to, you have to separate this out. And Mike, you and I've talked about this before, like if you're an existing company.

[00:59:42] Paul Roetzer: Thinking of AI as a way to get rid of people is not the right approach. I'm not an advocate of that at all. If you're building from the ground up, building with fewer people isn't a bad thing. Like, building a more efficient, profitable business that creates more fulfilling careers for the people that are there,

[00:59:59] Paul Roetzer: It just [01:00:00] means you have to hire fewer people to get to where you want to go.

[01:00:02] Paul Roetzer: So when you're running an agency, maybe your revenue per employee annually is 150, 200, 000, maybe 250, if you're kind of a leading agency, that's how much money each employee generates.

[01:00:14] Paul Roetzer: don't see any reason why an agency starting today, that number shouldn't be a half a million to 750, 000 per employee. So if you can build a business where you're generating 2 to 3x revenue per employee, and that person's still only working 40 hour weeks, that's, that's great for everyone. And I think that's what people should be thinking about.

[01:00:35] If you were leading a college degree in marketing, what would you do to ensure that your students are prepared for the future with AI?

[01:00:35] Mike Kaput: Okay. So kind of switching the topic area here, Rob asks, if you were leading a college degree in marketing, what would you do to ensure that your students are prepared for future?

[01:00:53] Paul Roetzer: So about seven years ago, made an argument to a major university that intro to AI should be a [01:01:00] required class for every freshman.

[01:01:02] Paul Roetzer: this is long before ChatGPT. my belief at the time, my belief still today is everyone in every profession, every major should take intro to AI and should understand the fundamentals so that they can connect the dots about the impact

[01:01:16] Paul Roetzer: it'll have on their career.

[01:01:18] Paul Roetzer: their career path, the, the industry that they go into. So I would start with that fundamentals within a marketing degree, for sure. I would focus on deep integration of AI into every aspect of the curriculum, specifically around the experiences that are created. I would bring in tech demos, either by outside experts or by students.

[01:01:37] Paul Roetzer: I would enable students to share best prompts. I would think of it as an aid to critical thinking. We

[01:01:43] Paul Roetzer: still have to develop critical thinking, strategic thinking, Reasoning capabilities, but I would have AI help accelerate the development of those things. I would try and figure out how to do personalized learning around it. But going back to like

[01:01:58] Paul Roetzer: the infusion and everything, I would [01:02:00] just think about every assignment you're giving and say, how can AI be an assistant in this assignment? And then I would have that be part of the process. Like, okay, I'm giving you this assignment

[01:02:11] Paul Roetzer: to go do a total addressable market study. I want you to use Google Gemini 1.

[01:02:18] Paul Roetzer: 5 in the process. As part of your deliverable, I want you to walk me through the prompts that you provided,

[01:02:27] Paul Roetzer: how you, you know, had a conversation with AI, the follow on prompts you had, what you learned from like, I would teach them how to infuse into

[01:02:35] Paul Roetzer: what they're doing, but make sure they're thinking critically about the outputs they're getting, and that they're getting better and better at, Knowing how to prompt the system to get what they're looking for and then how to verify sources, vet those citations, like things like that.

[01:02:51] Paul Roetzer: It's what's going to be asked of them in the real world. And I think that the sooner in, in high school and college, and even into like primary school, the [01:03:00] sooner we teach them how to work with the tools, um,

[01:03:03] Paul Roetzer: more capable they're going to be when they get into the professional world.

[01:03:07] With the advances in AI and the capabilities of instant knowledge transfer to anyone at anytime, do you think we're approaching the end of the need for the education system? At least the way that is is currently constructed. If so, what do you think the next evolution of education will look like?

[01:03:07] Mike Kaput: Okay, so Brian then kind asks a great follow on related to education, like, given the advances of, in AI and the capabilities of essentially instant knowledge transfer to anyone at any time, like, are we approaching the end the need for the education system?

[01:03:25] Mike Kaput: At least the way it's currently constructed, like, what do you think next evolution of education looks like?

[01:03:32] Paul Roetzer: I want to believe that. There's

[01:03:35] Paul Roetzer: going to be a place for higher education. Like, I think that look back on my time at university,

[01:03:42] Paul Roetzer: so much more to college experience than, than just, you know, the classes. it's just such a valuable experience, in so many ways, and it teaches you a diversity of thinking.

[01:03:57] Paul Roetzer: Like, it, it teaches you how to work in groups. It teaches [01:04:00] you, how to build relationships and, you know, work with mentors and like, I don't, I don't know. Like, so at a high level, I think there's just so much value to higher education. that being said, it has its deficiencies and it's really expensive.

[01:04:18] Paul Roetzer: And as a parent of someone who's going to have, you know, college aged kids in five, six years, you do start to wonder, like, is it worth it? that costs, don't even know,

[01:04:29] Paul Roetzer: 50, 000, 100, 000, like whatever a college education costs these days, if I, if I don't think that they really need what they're going to learn there.

[01:04:37] Paul Roetzer: So, I don't know, like I'm not deep in higher ed, uh, but I've spent a lot of time with higher ed leaders, and what I know about it is change is really hard in higher education, you know, to, to progress a university, you need professors who Welcome the change. My experience has been there are [01:05:00] amazing, innovative, forward thinking professors in every university.

[01:05:03] Paul Roetzer: And then there are a bunch of them who don't want to learn the new thing and don't want to teach the new thing. And so they're going to be resistant to AI and it's just straight plagiarism to them and I don't care what you say to me, like there's going to be those people too, and if I was a parent paying 50, 000 a year for a higher education and half of my, my kids.

[01:05:26] Paul Roetzer: Teachers didn't want to teach AI, I would have a serious problem.

[01:05:32] Paul Roetzer: so I think that as it becomes a more integral part of corporate life, as more business leaders who are parents, who have kids college age, Start asking around like, well, what are you learning? Are they teaching you how to use Perplexity?

[01:05:45] Paul Roetzer: Are you learning how to use Gemini? Do you have Microsoft Copilot? Cause that's what I'm using at work now. And if the answer is no, you're going to start getting a lot of backlash from parents who are unhappy about the lack of AI literacy being infused into higher

[01:05:59] Paul Roetzer: education. [01:06:00] SoI don't think this is like flip a switch next year.

[01:06:02] Paul Roetzer: Higher ed's got an AI problem, but I do think that. In the years ahead, we're going to start running into some major problems if universities haven't adapted to infuse it more deeply into what they're doing.

[01:06:14] What technological moment needs to happen to allow AI applications like ChatGPT to cross the chasm to early/late majority of users? Within the tech community there is very heavy use, but if you look around other industries (even outside of Marketing within companies), there is still very limited use outside of curiosity.  Is it a matter of it being embedded into iOS or some other event?

[01:06:14] Mike Kaput: Anuj asks, what technological moment needs to happen allow AI like ChatGPT to cross chasm to the early slash late majority of users? So, you know, within the tech community, there's very heavy use, but if you look at other industries, It seems like there's still very limited use outside of Curiosity.

[01:06:35] Mike Kaput: Is it a matter of being embedded into iOS or some other event?

[01:06:39] Paul Roetzer: could be a mix of being embedded into the platforms, but right now, Like Copilot, Gemini, um,

[01:06:50] Paul Roetzer: like someone's got to buy those licenses. I, you know, it's usually, know, the IT side coordinating it, CIO's office. somebody's got to get [01:07:00] the licenses for the 20, 30 bucks a month. is not insignificant when you're about of licenses.

[01:07:06] Paul Roetzer: And then somebody has got to teach them how to use the tools. So the procurement part is easier because you can go get the budget to get 500 licenses start

[01:07:18] Paul Roetzer: testing them. Where we're seeing the disconnect is the teaching of the people of how to use them. So if, if we go grab a thousand copilot licenses today and we get, you know, approval for 12 months.

[01:07:32] Paul Roetzer: And six months from now, only 200 of those licenses have even been distributed to the team and no one did any benchmarking of performance before or after, and nobody did proper onboarding of how to use

[01:07:44] Paul Roetzer: them and taught them, here's the top 10 use cases for you, accountant, for you, marketing manager, for you, uh, engineer.

[01:07:52] Paul Roetzer: If no one's done that part, then what's, what's the value going be?

[01:07:56] Paul Roetzer: And now we're going to be, you know, at the end of the license saying, did we get the value for the thousand [01:08:00] licenses and be like, nah, like utilization rates are like 10%. So my argument is we have a literacy problem until we solve AI literacy, until we solve.

[01:08:10] Paul Roetzer: a understanding across organizations of what is possible, then we're going to have disappointment with these tools and we're going to have a, uh, a bit of a mirage. We're going to think

[01:08:22] Paul Roetzer: that they're not as good as they're, they're said to be. They're not as valuable as they're said to be, but it's actually user error, not the fault of Google. And so I've seen that time and time again, meeting with big enterprises that they're going and getting licenses for things, and then they're just not properly onboarding people and teaching

[01:08:41] Paul Roetzer: them what they are. And you got a bunch of people who are like afraid these things are going to put them out of jobs.

[01:08:44] Paul Roetzer: Like not in a big hurry to like figure out how to use them. So AI literacy and change management, without those, we will continue to not

[01:08:53] Paul Roetzer: have, you know, deep adoption.

[01:08:55] As people give AI agents like GPT-4o and Astra access to their cameras and show it their homes, offices, desktops and documents, shouldn’t we be asking questions about privacy and security? Do we trust these companies so much? Is there a risk of increased government surveillance here?

[01:08:56] Mike Kaput: Diego asks, as people give AI like GPT 4. [01:09:00] 0 access to their cameras and show them things like their homes, offices, desktops, documents, shouldn't we be asking questions about privacy and security? Do we trust these companies so much?

[01:09:12] Paul Roetzer: So this goes to the law uneven AI distribution and the acceptance variable. Do we accept what we have to give up to get

[01:09:19] Paul Roetzer: benefit?

[01:09:19] Paul Roetzer: This is 100 percent problem in enterprises, our personal lives. I've said on the podcast for better, worse, Apple probably the company I trust the most. episode 101,

[01:09:32] Paul Roetzer: we're actually going to talk about a new, uh, report from the information that came out today about Apple's efforts to keep

[01:09:39] Paul Roetzer: your data Private on the iPhone when they introduced their new language model capabilities in June. Yeah. So this is why like HumanePin and Rabbit and like all these startups, whether they're device companies or software companies are going to have major adoption problems

[01:09:59] Paul Roetzer: the savvy [01:10:00] consumer is like, I don't know who this company is, like, I'm not trusting them with my data.

[01:10:06] Paul Roetzer: You know, we heard about this with like Roomba and stuff, like

[01:10:09] Paul Roetzer: like robots in your home that were able to map like your house and where things are, like, that's kind of weird or like cameras that, you know, you put in your house, some people choose to put them in their like baby's rooms. Those cameras have computer vision, employees at those companies have access to that data.

[01:10:26] Paul Roetzer: it's a problem, like, and so people are going to have choices if they're educated on how these tools work and where that data resides.

[01:10:37] Paul Roetzer: then they're, they may make the choice not to do it.

[01:10:41] Paul Roetzer: problem most people have no clue how computer vision works, how it recognizes people and objects through those cameras.

[01:10:50] Paul Roetzer: And so the same thing is going to, you know, kind of follow on over. A lot of people are just like, I don't care, like, whatever, it's got, my iPhone's always listening to me anyway. Like I'm just [01:11:00] going to do it. so it, it's just. Yeah, but the short answer,

[01:11:05] Paul Roetzer: privacy, security, major problems, it is going be a recurring theme you're going to hear about as AI,  you know, diffuses throughout society.

[01:11:14] How do you see regulation affecting AI? In particular, how it will benefit (or hinder) some economies more than others. For context, we are seeing a lot of different regulations being put into place by different governments, trading blocs and corporations, which could impact development and productivity. As an example, in Europe, we only just got access to Claude and the Gemini mobile app is not yet available, so we are technically behind everyone else when it comes to understanding and using those models.

[01:11:15] Mike Kaput: All right, Paul, last question. Made it. This comes from Guy. How do you see regulation affecting AI? In particular, how will it benefit or hinder some more than others? For context, we're seeing a lot different regulations being put into place by different governments, which could impact development and productivity.

[01:11:36] Mike Kaput: In Europe, we only just got access to Claude, and the Gemini mobile app not yet available. So we're technically behind everyone else when comes to understanding the world. and using those models.

[01:11:48] Paul Roetzer: So this definitely goes to the LLAMA on even AI distribution. This is the accessibility variable. Company may not allow it. Country not allow it. State shut it down. If you're in California, they got [01:12:00] kinds of stuff going on there. in the U S I think, you know, we've talked about, there's like 700 pieces of AI legislation and varying, know, degrees being pushed forward.

[01:12:09] Paul Roetzer: Regulations going to be part of this story.

[01:12:12] Paul Roetzer: You know, how it affects it and where it goes and, you know, whether it slows things down, we just don't know. certainly different countries, know, already seeing that EU AI Act is absolutely gonna play a role. Like, there's probably really good aspects of it.

[01:12:28] Paul Roetzer: There's probably parts that gonna, know, slow down some progress as well. So

[01:12:35] Paul Roetzer: and this again goes back to that, idea find your thread. Like, if this something you're really interested in, go deep on it. be, be an expert in AI and regulation. Like a fascinating area of study.

[01:12:44] Paul Roetzer: Like I don't, I don't have a ton of time to on it, but could spend

[01:12:48] Paul Roetzer: a day a week just Processing what's going on in this space. So, yeah, part of the story. And Mike, I'm going to throw a curve ball here.

[01:12:56] Paul Roetzer: I'm going to with like a really of upbeat thing. [01:13:00] Um, go first, but like when we think about all this, like there's a lot of daunting things.

[01:13:05] Paul Roetzer: There's regulation, there's privacy and security, there's lack of adoption. There's being frustrated in their corporation because not moving fast enough. there's all this amazing potential. And so I want to end with, are we most excited about? So Mike, knowing everything we know, all

[01:13:21] Paul Roetzer: the stuff we talk we see and do, what are you most excited about with, say, the next  year AI?

[01:13:28] What advancements in AI are you excited for in the next year?

[01:13:28] Mike Kaput: I think you alluded to mine, uh, in, when you were talking about AI being underrated for strategy. What I'm most excited about is the idea people

[01:13:37] Mike Kaput: still really underrate the idea of AI as intelligence on demand. Like, I'm not kidding when I say it's, It's super exciting to me has actually happened that through use of these tools I've easily gotten functionally a 20 point IQ bump, which would have been impossible any other means and is only going to grow.

[01:13:57] Mike Kaput: So with all the doom and gloom, which I very [01:14:00] much feel, it's amazing to be to go have this incredible new affordable tool to go really solve interesting intellectual knowledge work problems. And I think we're just scratching the surface.

[01:14:13] Paul Roetzer: Yeah, I love, I love that one. Um, so

[01:14:16] Paul Roetzer: for me, I I'm going to cheat going to do two. So at a high level scientific discovery, I've said this think it's going to be a golden age of scientific discovery, know,

[01:14:27] Paul Roetzer: for diseases, solutions some of the biggest we faced humanity. Like I, think we're just knocking on door

[01:14:33] Paul Roetzer: of amazing breakthroughs, know, in the next to 10 years. on business side though, I think

[01:14:42] Paul Roetzer: find the idea building like an native or AI company. Amazingly, invigorating. Like, when think about our own business, how do I build a smarter version a media company?

[01:14:54] Paul Roetzer: How do I build a smarter version of an event company? How

[01:14:56] Paul Roetzer: do build a smarter version of an online education business, a [01:15:00] research firm, like as someone who's been, mean, I've been in this, 25 years. I in 2000. I feel like as excited as day one, because anything's possible now. Like I can just look it and but there's no rules.

[01:15:14] Paul Roetzer: Like there's nothing saying can't build company 10X what are today with like more people. And those people have amazing lives and amazing careers. And we can create financial independence for and their Like, and we can help thousands of figure this like can do all that.

[01:15:32] Paul Roetzer: we don't need a hundred people or thousand people

[01:15:35] Paul Roetzer: it. That's kind of the Moderna one. Like back, going back case

[01:15:38] Paul Roetzer: studies, like we're going to accelerate drug discovery. We're going to launch like whatever, 10 new in five years, whatever it was. You used to need a hundred thousand people.

[01:15:46] Paul Roetzer: Now we can do it with a thousand. I feel that way for any business right now, where you can build smarter from the ground

[01:15:53] Paul Roetzer: entirely new ways where you're going to like a first principles approach, like, what I do if, if I didn't have [01:16:00] all like our existing financial model, I didn't have, I was in Asia, didn't Bill Blauer's to worry about, or if I didn't have this, what I do if I higher education didn't have this legacy stuff us what would I build?

[01:16:12] Paul Roetzer: I just think the, the, the fact we can ask that question, what would I build if anything was possible? What it is Hmm. that that's, it's so inspiring as an entrepreneur to be able to look out and see a smarter version. Of businesses being built in industry. And because have the knowledge we have able to help people bring those to life.

[01:16:34] Paul Roetzer: Like that's awesome. And I when I get asked, I asked this yesterday, like, how do you sleep at night? Like people were asking me all these like hard, big picture questions.

[01:16:42] Paul Roetzer: And I think part of the way I do is I balance it with these thoughts that it doesn't have to be doom and gloom. It It can be abundant.

[01:16:50] Paul Roetzer: It can be amazing. It can be inspiring. We can reinvent and reimagine everything. And I the people who choose to latch on to that mentality [01:17:00] have tremendous opportunity to build incredible things forward.

[01:17:04] Mike Kaput: That is an awesome note to end this on. I am also excited for the next hundred episodes of the podcast.

[01:17:12] Paul Roetzer: It's been 100So yeah, thank you everyone for listening. Thanks to everyone who submitted questions for this.

[01:17:19] Paul Roetzer: Mike, thanks always for the work you do to all this in an order. We can talk about it every week and showing up every week with me to do this. It is, it's a lot show up every week, but I wouldn't have it any other way right I think it's, it's such an amazing time to be living through what may end up being the biggest transformation in business and human history. And like get row seat to it. We get to talk it every week. So we're glad and grateful that you all listen.

[01:17:47] Mike Kaput: Awesome. Well, thanks Paul. And thanks everyone for sticking with us for however many episodes you've been with us, here's the next hundred and we'll see you again next week.

[01:17:57] Paul Roetzer: Thanks for listening to The AI [01:18:00] Show. Visit MarketingAIInstitute. com to continue your AI learning journey. And join more than 60, 000 professionals and business leaders who have subscribed to the weekly newsletter, downloaded the AI blueprints, attended virtual and in person events, taken our online AI courses, and engaged in the Slack community.

[01:18:20] Paul Roetzer: Until next time, stay curious and explore AI.

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