It’s our last episode of the year!
Join our hosts, Mike Kaput and Paul Roetzer, for a special year-end episode of The Artificial Intelligence Show! In this audience-focused finale, they address your most pressing questions about AI, tackling the top 25 questions submitted directly from our audience. We're grateful for your thoughtful questions and continued support in 2025.
Listen or watch below—and see below for show notes and the transcript.
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To learn more about the membership, go to www.smarterx.ai/ai-mastery.
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Listen Now
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Show Notes
- Marketing AI Institute
- SmarterX
- Intro to AI for Marketers [Live Class]
- Piloting AI 2024
- Scaling AI Course Series
- AI Mastery Membership
- Intro to Large Language Models
- My Last Five Years of Work
- Situational Awareness
- How AI Helped Us Hit 100,000 Podcast Downloads in 2023
- [The AI Show Episode 124]: Has AI Hit a Wall?, What Is An AI Agent?, Dario Amodei Interview, OpenAI’s New Agent, Greg Brockman Returns & Microsoft Copilot’s Woes
Timestamps
[00:07:01] AI Education
00:07:01 — Question 1: In many places, AI skills aren't taught in schools, leaving parents searching for ways to help their kids build a strong career future. What are some tips to guide them?
00:10:08 — Question 2: What should universities be doing in 2025 to better prepare college students for AI?
[00:11:34] AI Trends
00:11:34 — Question 3: What has AI not changed? Or what will AI not change?
00:14:49 — Question 4: Is the race for AI companies to be first to market with new models, new features, and new solutions (whether they're ready or not) setting a dangerous precedent?
[00:17:41] AI Careers and Business Advice
00:17:41 — Question 5: What are your thoughts on learning coding in the age of AI? What are the most valuable education tools I should work towards achieving to help further a career in AI?
00:19:49 — Question 6: A lot of the value AI brings isn't easily measured. How can we gather ROI of the AI tech stack next year?
00:21:14 — Question 7: What unintended consequences of widespread AI adoption should we be watching for and preparing to address?
00:23:42 — Question 8: What is the most impactful piece of advice and/or literature you came across regarding AI in 2024?
00:25:34 — Question 9: In your view, which uniquely human traits are most critical for marketers to upskill and focus on alongside building their AI skills and capabilities?
00:29:11 — Question 10: It already feels impossible to keep up with the pace of AI changes. How can our company make decisions about the use of AI tools so we're emergent, but while avoiding waste?
00:34:03 — Question 11: What is your advice for AI enthusiasts who work in industries that are slower to adopt new technology and where leadership doesn't recognize the urgency we should be placing on AI adoption?
[00:36:52] AI Tools and Use Cases
00:36:52 — Question 12: What is your favorite AI tool for work and why?
00:38:33 — Question 13: Can you share an automation or workflow that has been the most effective one you’ve implemented for the team?
00:39:49 — Question 14: What would you consider to be the most impactful or beneficial AI use case that you've seen or heard of?
[00:41:15] Agents
00:41:15 — Question 15: With the rise of AI agents that can autonomously execute complex tasks and strategies, how do you see the role of marketers evolving in the next few years?
00:44:24 — Question 16: How do you build agents? Is there a platform or app that you recommend?
[00:45:43] AI and Agencies/Professional Services
00:45:43 — Question 17: With AI potentially reducing the time spent on content creation and strategy, how should agencies reinvest that time to drive greater value for clients?
00:46:56 — Question 18: Any specific recommendations for language that agencies can use (or should use) in their client contracts re: the use of AI?
00:48:08 — Question 19: We suspect AI will replace junior associates (who eventually become partners) at almost any professional services firm. So where will professional service firms get partners in an AI world?
00:51:10 — Question 20: Do you think AI will change the typical agency pricing model, particularly in areas like project-based work or retainers? If so, how should agencies adapt?
[00:52:30] What 2025 (and the Future) Holds
00:52:30 — Question 21: What AI opportunities and challenges excite you the most or fill you with dread, and why?
00:54:08 — Question 22: How do you stay optimistic about the future of humanity (especially the world of work) with the potential near-term advent of AGI?
00:55:18 — Question 23: What's an industry where you think AI is currently underutilized—one where you're personally most excited to see it adopted in earnest?
00:56:36 — Question 24: If you could have one wish granted for the future of AI in 2025—whether it's a breakthrough, a trend, or a shift in how AI is used—what would it be, and why?
00:59:08 — Question 25: What is the one, most urgent piece of AI advice you’d give to any business professional as they enter the new year?
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: So I choose to be optimistic. I choose to believe that the future can be abundant. It can be incredible. We can get time back. We can invent new career paths. We can go through a renaissance in creativity and entrepreneurship. Like. I think all of those things are possible. Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable.
[00:00:24] Paul Roetzer: 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
[00:00:52] Paul Roetzer: Welcome to episode 128 of the Artificial Intelligence Show. I'm your host, Paul Roetzer, along with my co [00:01:00] host, as always, Mike Kaput. This is a special episode, special edition of the Artificial Intelligence Show podcast. It is our final episode of 2024. But what we're doing here is it's not our normal weekly format where we go through main topics and rapid fire items.
[00:01:18] Paul Roetzer: Instead, we are going to be answering 25 user submitted AI questions for 2025. And so that is the focus here for your regular listener, for a few weeks in, what month are we in? So November, we talked about the fact that we were going to do this episode, we had an online for from Google people could fill out.
[00:01:41] Paul Roetzer: And, that's where the questions are going to come from. So, Mike's actually going to walk us through a little bit of the methodology before we dive into the first question. We're going to move pretty quick through these, some of these, I mean, they're honestly like incredible questions. I scanned through them this morning before we started recording.
[00:01:55] Paul Roetzer: We're recording on December 17th. [00:02:00] And they're, they're, they're amazing questions that we could easily spend five to 10 minutes or more on each of them, but we're going to move like one to two minutes is the goal for each of these. So we'll try and get through as many as we can, hopefully in under an hour.
[00:02:12] Paul Roetzer: Okay. So this episode is brought to us by, the AI, AI Mastery Membership Program. So this is, I've been talking about this recently on the podcast. This is our annual membership program that gives people access to exclusive educational opportunities, insights, and experiences. It's, Mike and I largely run the programming, so we do, a trends briefing every quarter, kind of the 10 key things you need to know about that quarter.
[00:02:39] Paul Roetzer: we do a quarterly Gen AI Mastery Series, we do demonstrations of AI technology, and we do a quarterly Ask Me Anything session. So every month, there's at least one unique, programming opportunity for members. In addition to, un gated access to the on demand webinars, un gated access to blueprints, and then we're actually working on a bunch [00:03:00] of plans for 2025 to add even more value.
[00:03:03] Paul Roetzer: to this membership program, including new courses, new certifications, new experiences. So as you're thinking about 2025, this is a great chance to get in. And we always think about everything in like a learning journey. And I think about intro, piloting, scaling is kind of like the main steps. But throughout that process and beyond, you always want to be pursuing this idea of mastery in, in your education and capabilities.
[00:03:28] Paul Roetzer: And so that's our goal here is like this ongoing program in addition to the podcast Kind of a more deeper dive into helping people really drive their own AI transformation in their careers and in their companies. So you can go to smarterx. ai and click on education and it's under there or smarterx. ai slash AI dash mastery and we will put that link in the show notes.
[00:03:51] Paul Roetzer: You can use pod 150 and that will get you 150 off of the membership. So again, that's pod P O D 1 [00:04:00] 5 0, 1 5 Okay, Mike, we've got a lot of, like I said, incredible questions, very thoughtful questions. We appreciate everybody who took the time to submit these questions. So I will turn it over to you. You can kind of explain to us the process we went through.
[00:04:16] Paul Roetzer: I used a little bit of AI in the process and we'll jump into the questions from there.
[00:04:21] Mike Kaput: Sounds great, Paul. first up, I just want to, I'm not even saying this to be nice to everybody, our audience just deserves, like, a gold medal for the quality of these questions. Like, I was just blown away. It was really hard to curate them.
[00:04:33] Mike Kaput: They're very thoughtful questions. They're incredible. Yeah. And I, you'll hear in a second just how in depth some of these are. So what we did is over the last few weeks on the podcast, we solicited questions through just a quick Google form, had people submit anything on their mind related to AI. We got dozens and dozens of questions.
[00:04:54] Mike Kaput: So I went through and kind of manually reviewed them all. Basically curated from, [00:05:00] in my opinion, kind of the top 25 questions and organize them thematically. You know, people have a lot of the same types of themes on their mind. So I wanted to also be sure, you know, we pick a question that's also representative of several others that people ask, try to cover as much ground as possible.
[00:05:16] Mike Kaput: What was cool is it was really helpful to use Notebook LM during the prep for this because we have, what, 127 other podcast episodes at this point. So most of those are in a notebook now in NotebookLM via YouTube video links. And I was able to quickly like query for many of these questions, what we've talked about in the past, kind of just pull some interesting threads that we've been hitting on, which I found to be really helpful in terms of prep.
[00:05:44] Mike Kaput: And then we kind of synthesized our answers and kind of talking to what we want to discuss. And also just like kind of off the cuff conversation. Related to all of these questions. So that's kind of how we got to where we are. So Paul, if it's good with you, I'm just going to kind of dive in [00:06:00] and start reading out some questions for you.
[00:06:02] Paul Roetzer: Yeah, and for context, so, I mean, Mike sent me this link a few days ago, and honestly, I looked at it this morning before the Co CEO webinar. So, I just kind of went through, and the way I actually approach this, because generally speaking, when I do Q& A, whether it's a podcast or intro, I actually don't prep for it.
[00:06:19] Paul Roetzer: Like, I prefer to not even know what the questions are going to be. But for this one, knowing we were doing these 25, I thought, well, I'll at least go through and like read through these things. So I actually haven't read through, Mike, your notes on what we previously talked about. I just went through and jotted a couple of bullet points.
[00:06:35] Paul Roetzer: And I thought that I would actually almost prefer to take like this fresh perspective on these things. So what I'm going to do, Mike, is that when you asked me the question, I'm going to kind of give this more off the cuff, fresh answer. And then if there's things we've previously said about it on an episode, yeah.
[00:06:51] Paul Roetzer: You know, feel free to add that stuff in. It's good context.
[00:06:56] Mike Kaput: All right. Yeah. I feel like you're in the hot seat now. You ready? [00:07:00] Okay. Yeah. All right.
[00:07:01] Question 1
[00:07:01] Mike Kaput: So, question number one. I live somewhere where AI skills will not be taught in schools. I want to prepare my kids and also help guide them to the best possible future employment.
[00:07:13] Mike Kaput: Do you have any thoughts or tips?
[00:07:17] Paul Roetzer: So the couple of thoughts I have here is I've obviously talked on the show numerous times about my own kids. I have a 12 year old and an 11 year old. And they go to a wonderful school, and I wouldn't say that school is proactively teaching them about AI. Like, they're, they're open to it.
[00:07:34] Paul Roetzer: Like, it's not outlawed for use in the school. and I think I've, I've seen that in a lot of schools where they're allowing it, within the confines of how individual teachers often determine that they're going to use it. And so, even though, you know, this person's saying they live in a place where it's not going to be taught, even people like me who live in a place where you would assume it's going to be taught, it's still, you can't [00:08:00] rely on the schools for this.
[00:08:01] Paul Roetzer: And so I guess my point here is I'm trying to be very proactive with my kids to, to make them very aware of AI technology and very savvy with AI technology. Cause the way I think about this is whatever their career path is. So they're in sixth and seventh grade as they move into high school, as they move into college, like I've got a little time, they've got time, but I know some of these listeners may have kids who are in college, or, you know, very soon going to be, and so you're starting to think about like career paths and things like that.
[00:08:34] Paul Roetzer: And so. My feeling is that they're going to be at an advantage because if I look forward to the future of work, I am very confident that AI is going to be infused into every profession. And so I want them to be confident with the technology that they will use in their career. And so I'm trying to experiment with them in fun ways, like storytelling, image generation.
[00:08:58] Paul Roetzer: We'll definitely play with like the video [00:09:00] generation, play around with voice mode on the way to school in the mornings. We'll use it when they ask me a question about stuff I don't really know. I'll pull up advanced voice mode and we'll have a conversation about it. I'll let them ask follow on questions.
[00:09:14] Paul Roetzer: So like, I'm just trying to let it be a part of their life without allowing them to use it as a crutch to avoid learning. so I'm trying to teach responsible use and then Depending on how old they are would dictate how proactive I would be about their future and education career choices. So like, you know, if they were seniors in high school and they were making a college decision today, I might be a little bit more proactive about how I would guide them than I am when they're in sixth and seventh grade because I feel like It's not time yet to make any changes or anything like that or say, Oh, you're not, that job's not going to exist when you grow up.
[00:09:53] Paul Roetzer: Like you should, so I'm not doing that. So I guess my, my short answer to this would be. Just be proactive, bring the knowledge [00:10:00] to them, take the responsibility yourself to, try and engage them in the technology in a responsible way.
[00:10:08] Question 2
[00:10:08] Mike Kaput: So question number two, somewhat related, what should universities be doing in 2025 to better prepare college students for AI?
[00:10:17] Mike Kaput: Or, what do you see as the future for higher ed as it relates to emerging AI capabilities?
[00:10:22] Paul Roetzer: Yeah, this one I'm very adamant about. We have to teach the teachers. You know, you can put whatever policy guidelines you want in place in a university or even in a high school. But until the teachers themselves are enabled, you know, until they have a strong confidence level and understanding the technology themselves, what it's capable of, how students could be using it already, how the students could benefit from it, we have to teach the teachers.
[00:10:50] Paul Roetzer: And I, the other thing that I think about here is like, you know, Mike, you and I both have done a ton of workshops and speaking. We've spent a lot of time with, you know, brands, enterprise leaders. [00:11:00] And the organizations who are racing ahead have CEOs who are bought in. when the CEO and the C suite are present, presenting roadblocks to this or not encouraging responsible adoption, then those are the organizations that are falling behind.
[00:11:18] Paul Roetzer: And so I just feel like the same is going to be true on education. We need the leaders, the provost, the deans, the directors, they've got to be involved in doing this. And not trying to shy away from it or ignore it, they've got to embrace it.
[00:11:34] Question 3
[00:11:34] Mike Kaput: Alright, so question number three. People always ask about what will change about AI or what are the biggest changes from AI.
[00:11:43] Mike Kaput: But, and I think we've cited this interview before, Jeff Bezos once said in an interview, The most important question I'm never asked is what hasn't changed. And he says, in the context of Amazon, you know, people are always concerned about price and delivery, no matter how much everything else changes. [00:12:00] So, this listener wants to use the same logic on AI.
[00:12:04] Mike Kaput: What has AI not changed, or what will AI not change?
[00:12:09] Paul Roetzer: Yeah, this is a, this is a challenging one. So, I often think about, you know, what remains uniquely human, and what isn't that AI going to be able to do or to simulate. honestly, that list keeps getting shorter. You know, the things I thought a year ago were pretty uniquely human, I'm not so sure anymore.
[00:12:30] Paul Roetzer: So, when I think about this question, like, the first thing that comes to mind is human connection. Like, that's not changing. Like, we still want to be around other people. We want to interact with them. I want to see people in the office. I want to meet our, you know, customers. I want to hear their stories.
[00:12:45] Paul Roetzer: Like, that doesn't change. When I think about the customer side, and I, again, I come back to like our specific business just for context, people want to feel needed, valued, and fulfilled in their careers and they need [00:13:00] education and training to do that. So like when I think about the future for us, I think about that's not going to change.
[00:13:08] Paul Roetzer: It actually might become more important and harder to figure out like what is fulfilling for the human when the AI is doing more and more of the work. so, but how we deliver that information, how we, you know, help and delight people in providing that education and training, that changes, because AI enables whole new ways to do that, and I'm constantly thinking about how can we improve the way we deliver this, but those fundamental needs aren't.
[00:13:37] Paul Roetzer: And so that's, I don't know, like, I don't know how, like, universal that is to different industries, different business models, but human connection and the human need to feel needed, valued, fulfilled, like, those don't change, the tech just enables whole new ways to deliver that, I guess, you. But yeah, it's hard when you look at human traits and skills to, [00:14:00] to know what doesn't the AI, you know, at least be able to simulate.
[00:14:05] Mike Kaput: One trend that came out of some of our past episodes is, if I had put it in one word broadly, this idea of curiosity. Because like right now, at least if we had to bet, I would say we're still always going to have questions. We're still going to be asking questions and maybe we can actually ask better ones.
[00:14:24] Mike Kaput: Or more complicated ones that AI can help us answer. Now, obviously, I don't know if that's like a skill you're putting on your resume, but I suspect we'll still need to be asking really smart questions moving forward.
[00:14:36] Paul Roetzer: Definitely. Yeah. the machine itself is not curious by nature. It just solves things you ask it to do.
[00:14:43] Paul Roetzer: It does things you ask it to do, but it doesn't seek out things to do or to learn.
[00:14:49] Question 4
[00:14:49] Mike Kaput: Alright, question number four. Is this race with all these AI companies to be first to market with new models, new features, new solutions, whether these things are ready or [00:15:00] not, is this all setting a dangerous precedent?
[00:15:03] Paul Roetzer: Well, great timing on this question. Coming off of episode 127, when we talked about the craziest week of AI updates I can recall, yes, it is. Like, there's no real way around this. It's, we are in uncharted territory. And none of the companies know where they're taking this. Like that is indisputable. Like they don't understand the ramifications of what they're doing.
[00:15:30] Paul Roetzer: nor the potential, like, long term implications if they succeed in building the AGI or the superintelligence they intend to build. So yeah, I mean, we don't, it's not clear, like, just last week we had our new research report on scheming and how these models are able to scheme to manipulate humans. We know that they're highly persuasive.
[00:15:49] Paul Roetzer: They're likely superhuman at persuasion, but we also know that these frontier model companies, extract that capability. They try and keep them from being overly [00:16:00] persuasive. we don't know what happens if, and maybe when, I don't know who you talk to, these things become aware of their own thoughts, like metacognition, like they're like a human, like I'm, I'm aware I'm thinking right now.
[00:16:13] Paul Roetzer: machines we don't think are aware that they're thinking. But when they do, then they become self aware and that's a really weird thing to start considering the ramifications of. I think Ilya Sutskever talked about that concept in his recent talk that we covered on episode 127. And then there's this whole idea of Once we build agents that can really do things and plan on their own and take actions, they likely become self improving.
[00:16:42] Paul Roetzer: They, they, they develop the ability to just replicate themselves or to improve themselves at a very rapid pace. And we don't know what that means. So, yeah, the reality is, is like we're racing really, really fast to build and release smarter models for competitive reasons, for financial reasons, for [00:17:00] egotistical reasons.
[00:17:00] Paul Roetzer: Like there's probably a lot of reasons why different companies are doing this. but safety and alignment is not moving as fast and we are basically depending upon these companies to, to halt or slow down when they think it's gotten too dangerous. But I'm not convinced that will happen because Anthropic is supposed to be, at least, you know, from a PR perspective, they position themselves as being the ones who are supposed to be championing this and yet they're putting out computer use for anybody else, which is as dangerous as anything right now.
[00:17:31] Paul Roetzer: So Yeah, it's a, it's a big area of concern and I hope more people moving into 2025 spend some brainpower on, on that topic.
[00:17:41] Question 5
[00:17:41] Mike Kaput: Alright, we have a bunch of questions that would fall kind of under the banner of AI career and business advice. And first up, question number five in our 25 questions is, what are your thoughts on learning code in the age of AI?
[00:17:55] Mike Kaput: If I'm trying to further my career in AI, what are the most valuable? [00:18:00] education or tools that I should work towards achieving or figuring out.
[00:18:06] Paul Roetzer: So I'll go back to the, context of like, if one of my kids was a senior in high school and they wanted to go into computer science, would I guide them not to?
[00:18:18] Paul Roetzer: I, at this moment I would not steer them away from that. So if my daughter or son said, I'm going to go wherever and I'm going to, you know, I'm going to do coding or build software. I think in the near term. People who can code are going to tend to 100x their capacity, their capability to build things.
[00:18:38] Paul Roetzer: It's just going to become that much better. And the people who know how to build will get more value from these tools than people who don't. That being said, there is definitely a clear direction among these companies to make coding, the language of code, human language. Like, you don't [00:19:00] need code. You, you will just say what you want.
[00:19:03] Paul Roetzer: Like imagine how we build GPTs. Like you just give it instructions and you build it. You'll be able to go into places like Repl. it and Microsoft and Google, and you're just as a non developer, a non technical person, you're going to just be able to build apps and websites and products and companies. with your words and that's not far off in my opinion.
[00:19:24] Paul Roetzer: So I think coders are still going to matter. I think they're going to be way, they're going to have superpowers. But I also think the average person is going to be able to do what coders, you used to need coders to do. And I'm not sure what that means to the future of that profession. But again, I would not currently steer someone away from pursuing that profession if that's what they chose.
[00:19:48] Paul Roetzer: Thanks.
[00:19:49] Question 6
[00:19:49] Mike Kaput: Question number six, a lot of the value that AI brings is not always easily measured. How can we gather the ROI of the AI [00:20:00] tech stack as we go into 2025? Like how can we get better at measuring ROI?
[00:20:05] Paul Roetzer: I don't think this is very different than just traditional software, tools you would buy, things like that.
[00:20:12] Paul Roetzer: I think anytime you're going to make an investment, you have a goal in mind of what we're going to achieve with this investment, this project, this campaign. You benchmark prior performance and then you measure whether or not it's improving. So, you know, we always talk, Mike, about like these pilot projects where we're gonna, let's just say podcasting.
[00:20:31] Paul Roetzer: We're gonna go get an AI product for podcasting. It's gonna do these three things. Okay, our goal is to increase, say, 30 percent efficiency. You know, let's just pick a number. then we're going to take time and benchmark it. If we have existing time data, we'll, we'll use that. If not, we'll do it the way we've been doing it for, you know, a week or two, benchmark it.
[00:20:52] Paul Roetzer: And then we will measure whether or not these tools improve over a 90 day period. If they, if they don't achieve what we wanted them to do, create the value we wanted, we move [00:21:00] on. If they do, we double down or we, you know, buy that annual license at that point. So, I think you just have to approach these things with goals in mind and then know what the metrics are you're going to measure to tell you whether or not it's working.
[00:21:14] Question 7
[00:21:14] Mike Kaput: Alright, question number 7. What unintended consequences of widespread AI adoption should we be watching for and preparing to address?
[00:21:23] Paul Roetzer: I'm really glad we didn't make this one the last question because this is like, it's like, just shove it in the middle. I
[00:21:29] Mike Kaput: structured the mood of these questions and on a positive note, let's just say
[00:21:33] Paul Roetzer: that.
[00:21:34] Paul Roetzer: So I'll, this is definitely one that we could spend the whole time talking about, so I'll be brief here. Near term, it's jobs. Jobs, jobs, jobs. Like, that is like the main thing I'm worried about. I know that concern is not widely shared among economists and government leaders, at least they're not saying it publicly if it is.
[00:21:52] Paul Roetzer: I think they are misguided. I hope I'm wrong on this. I really do. I hope two years from now we look back and [00:22:00] say, yeah, you were, you know, overstating it. It really wasn't that big of a deal. Increasingly signs are pointing to it's going to become a problem in the next one to three years that we are going to need fewer people doing the work we currently do.
[00:22:14] Paul Roetzer: Now, there are always a bunch of industries who can't hire enough people. It's not going to be universal. I'm not saying like everywhere across the economy, this is going to be the case. Some industries need AI to fill gaps. I get it. But there's a lot of knowledge workers and a lot of them are going to be directly impacted by AI's capabilities in the next one to three years.
[00:22:34] Paul Roetzer: Mid term, you know, we're starting to look at, What happens with this next generation when they're raised having AI assistants on demand? When they can just ask questions of Surrey or, you know, Google Voice or OpenAI, ChatGPT, Voice. And three to seven years from now, like, what if they forget how to learn?
[00:22:55] Paul Roetzer: Like, what if we don't teach this the right way and kids, it does become a crutch and they [00:23:00] never learned the fundamentals that we all had to learn coming up in our professions that enabled us to become. You know, domain experts, or gain that experience, gain that knowledge and understanding. I worry that if we don't do this right, they, they won't learn those things.
[00:23:14] Paul Roetzer: And then, seven to ten years out, now we're looking at societal change, government, unstability, instability, educational, massive educational, system shifts, massive impacts on the economy, which I think can be mostly positive, but they're going to be an impact nonetheless. And so that's kind of near term jobs, mid term, you know, impact on students as they grow.
[00:23:36] Paul Roetzer: And then long term macro, like everything, that's the stuff I think about.
[00:23:42] Question 8
[00:23:42] Mike Kaput: Alright, number eight. What is the most impactful piece of advice or literature that you came across on AI in 2024?
[00:23:52] Paul Roetzer: This is an interesting one, Mike. I'll be interested to see if you have any that don't make my list. I know it said just anything.
[00:23:57] Paul Roetzer: A piece I had trouble really picking, and [00:24:00] I could explain why each one of these was so impactful, but first was Intro to Large Language Models, or LLMs, by Andrej Karpathy. So that YouTube video from January, it had a profound impact on me because he laid out what all the major AI research labs were working on.
[00:24:16] Paul Roetzer: And that validated a lot of what I thought was happening, but to hear him say it was like, okay, good. Like, I definitely feel, and that worked into like every keynote I gave after that and eventually informed part of the exposure key I built for JobsGPT. the, you know, the custom GPT we created.
[00:24:33] Paul Roetzer: the other two that I would mention is My Last Five Years of Work by Avital Balwit, who's the chief of staff at Anthropic for the CEO. And then Situational Awareness by Leopold Aschenbrenner. We'll put links to all these in, but we, we talked about all of these on the podcast and in many cases, multiple times, we referenced all three of those.
[00:24:51] Paul Roetzer: Is there any that jump out to you, Mike, as something that was impactful for us?
[00:24:56] Mike Kaput: Well, all of those would definitely be on my list. I would just add to that in [00:25:00] aggregate, the work of Ethan Mollick, just because I think the biggest. piece of advice he has that recurs through his posts and, you know, his engagement online is this idea of like, look, even the labs themselves don't know how to apply this stuff to your job.
[00:25:16] Mike Kaput: And it's very, positive in a lot of ways. Cause it's really easy to sit here and say, someone I'm sure knows more about this than I do, but he, Kind of says, look, you're supposed to go play, experiment. It's messy. Go figure it out for your own job, your own work, which is something we talk about all the time as well.
[00:25:34] Question 9
[00:25:34] Mike Kaput: All right, number nine. So, you know, we talked about this past year, Sam Altman's kind of quote about AI automating 95 percent of like marketing work, creative advertising agency work. So, as I think about this as a marketer, someone asked, and remaining indispensable, like in your view, which uniquely human traits are most critical for marketers to [00:26:00] upskill while they focus on building their AI skills and capabilities?
[00:26:06] Paul Roetzer: Yeah, so I kind of alluded to this one earlier. I do struggle with this, what remains uniquely human, which traits should we really be pushing. I don't know that the 95 percent by 2027 is anything I would put any money on, like the probability of us getting to that by 2027 is probably pretty low. It's not zero, but it's, it's low.
[00:26:28] Paul Roetzer: at least across like the general populace, maybe in some industries it could be. So, that being said, like, some of the things I've highlighted in talks, I know at my opening keynote at MAICON I talked about this, is common sense is uniquely human. And that one I'm, I'm fairly confident probably stays.
[00:26:47] Paul Roetzer: Curiosity, you had called out earlier. Experience, that's an interesting one because can that be simulated through just a bunch of training or simulations, probably, so I'm not sure. [00:27:00] Imagination, so thinking of creative things to solve, creative problems to solve, creative approaches. That's, I mentioned on episode 127, I'm not so sure that the AI lab, specifically Google, don't think they have a way to do that.
[00:27:17] Paul Roetzer: Like I, I think they think. That they are unlocking the ability to give these machines imagination, create original ideas and thoughts. That's to be determined. Instinct, which comes from experience a lot of times, intuition, love, like actually caring about the people you're creating solutions for is uniquely human.
[00:27:40] Paul Roetzer: I don't think machines are going to have that. And then self awareness we sort of talked about. so I mean, at the end of the day, like what I think the future of work is going to be is telling the AI what to predict, what to create, what to plan, and then knowing what to do with it. So an example here is like the O1 reasoning model from OpenAI.
[00:27:59] Paul Roetzer: It's [00:28:00] now able to go through chain of thought and do this reasoning, but it doesn't do anything. It sits there as a blank screen until you think of what to ask it to solve. And so the human has to come up with the things to solve and, you know, develop a creative plan around that. and then once you get the output, you, you have to decide if it's any good.
[00:28:22] Paul Roetzer: And so those are the things I would really focus on is like logic, like logical thinking, strategic planning. again, there's like common sense intuition. Like, I don't know how you teach those traits per se, other than going through experience and trial and error in a lot of, a lot of ways. But for us to judge the output of the machine, we, we have to have those things.
[00:28:44] Paul Roetzer: So, I don't know. I mean, the people I think who excel in those areas stand to do really well. If, if all you do in your career is like the repetitive tasks that they could take someone tomorrow and plug them in, they could do the same thing you're doing. That's, that's [00:29:00] not going to bode well. you have to have these unique abilities that isn't going to be easily replaced with some smarter version of ChatGPT.
[00:29:11] Question 10
[00:29:11] Mike Kaput: Alright, question number 10. It already feels impossible to keep up with the pace of AI changes. No matter how much the technology improves, but the number of AI tools and companies, all the options, all this constant leapfrogging, it's impossible to keep up with. This person asked, as general counsel, I'm on the board with AI for my company, so is our president.
[00:29:33] Mike Kaput: But the pace it progresses at does not align with what seems like a reasonable pace to scale the company and to get the employees to embrace this. For example, just when the president agrees to get an enterprise account for a handful of employees, ChatGPT announces an expensive pro plan, where a competing AI tool announces an advancement.
[00:29:54] Mike Kaput: That makes it seem like that tool is better for our company. How does a company like ours, that [00:30:00] he says they're a construction company, make decisions about the use of AI tools so that we're emergent but we avoid all this waste? We don't want to sit back and wait. But we also don't want to start down the wrong path.
[00:30:11] Paul Roetzer: Yeah. I will just say, first of all, no, you are not alone that as you're reading this question, I would imagine a lot of our listeners might be thinking to themselves, well, I could have sent that question. Like that's the same problem. Mike and I feel that and we monitor this space for a living. Like just this past week as I felt like I should have tested the video generation model more.
[00:30:34] Paul Roetzer: I should have had a chance to go in and do this. And like, I just feel like. AI world just like moved past me in the last three days because I had other stuff I had to do. so a lot of people feel that same bit of overwhelm and helplessness in some ways. So the first thing I would say is have trusted voices, hopefully Mike and I function in that role for many of you, you know, just knowing once a week we're going to try and unpack the things you should really care about.
[00:30:58] Paul Roetzer: And if you miss the news on your own for [00:31:00] a week, hopefully, you know, you feel like we can catch you up. And so that's, you know, whether it's us or somebody else, like have the people you trust as your filters who actually are living and breathing this stuff every day. And can, you know, help you see it through.
[00:31:13] Paul Roetzer: The other thing I would say is like, don't worry about trying to solve all this. Don't worry about always having the latest thing. Honestly, like if people just took ChatGPT 4. 0 or Gemini 1. 5 or whatever it may be, and you just went hard on that platform and you've just maximized the value and personalized the use cases and taught people how to do it and enabled them with these tools and you ignored.
[00:31:39] Paul Roetzer: AI updates for the next 12 months, you're going to come out ahead of most of your peers. Like I think just picking a platform and going and training people on it and building, you know, custom GPTs or whatever it is that just enables people to get value, get them, you know, one, two, three use cases they use every day, that's going to be [00:32:00] enough.
[00:32:00] Paul Roetzer: Like it's going to get you ahead. And then if you can, depending on your structure or company, create a little AI lab or a center of excellence or whatever, and have like two or three or five people who want to be a part of being out on the frontier. Let them test this stuff. You know, join our AI Mastery Membership Program and like, just follow along with what we're experimenting with.
[00:32:19] Paul Roetzer: However you want to do it, let them worry about that. But until they've built a business case and they can pilot this with a small group of people. Don't even think about the new stuff, just like let them handle that and then they'll bring it to you when they think they have a proven business case. So I don't know, Mike, you, you obviously deal with this all the time too.
[00:32:38] Paul Roetzer: Do you have, do you have any other thoughts on that?
[00:32:39] Mike Kaput: Yeah. I liked what you said about just go hard on one platform because I can guarantee you if you actually do that. And you get to the end of whatever that pilot looks like or that experimentation period and you say, Shoot, we're using the old technology.
[00:32:54] Mike Kaput: We're ready to advance. You've probably saved so much time and money already that it will not be hard [00:33:00] to get a little extra money for the next tool or for a few tools. So that's the key.
[00:33:04] Paul Roetzer: Yeah, and I think the other thing that comes to mind is like Sam Altman talking to startup founders and saying like, Don't build something we're going to just.
[00:33:13] Paul Roetzer: like obsolete with our next model, if you build around today's capabilities and adopt it within your company, it's only going to get better when they improve the model. That's what I'm saying. Like, if you just bet on Gemini or ChatGPT or Copilot or AgentForce or like whatever your platform of choice is, whatever your company of choice is, and you just invest in maximizing the value you can extract from that.
[00:33:40] Paul Roetzer: And then if someone introduces a new model that then is put into Salesforce or ChatGem or whatever. And it gets better at reasoning, it gets better at, you know, content creation, creative writing, whatever, it's not going to change your plan in adoption, it just may, like, level it up a bit, so I don't think you can go wrong with making a bet on a [00:34:00] platform that you're confident in.
[00:34:03] Question 11
[00:34:03] Mike Kaput: Alright, number 11. What is your advice for AI enthusiasts who work in industries that are traditionally slower to adopt new technology? And where leadership doesn't recognize the urgency we should be placing on AI adoption.
[00:34:17] Paul Roetzer: So I'm, I'm just going to hit this one fast with like three things, each one of them, again, we could unpack, you know, another time, but, if your company isn't embracing it, or even worse, isn't allowing it, like you cannot use ChatGPT within your company, you can't test custom GPTs on your job, so you have no idea what we're talking about, then invest in your own personal life.
[00:34:38] Paul Roetzer: Go get a paid 20 a month account. Go build a GPT to help you plan a trip, to help you talk to your kids, and Gen Z slang, like whatever, whatever it is, like Just go in your personal life and experiment. the second thing is, push for change internally. Like, with actionable and achievable plans and viable pilot [00:35:00] projects.
[00:35:00] Paul Roetzer: Like, bring ideas to the table that solve business problems. Not, hey, I want to try some AI, let's go get Sora. It's like, no, nobody needs Sora right now in the company. Like, what do you actually need? We need to like, figure out churn, or we need to generate more leads, or we need to be more efficient.
[00:35:15] Paul Roetzer: Whatever it is, push for change. Push for that change. And if all else fails and nobody wants your voice involved and nobody wants to listen to the opportunities here, then go find another job. Look in your industry and say, who is moving forward? Like, cause I will tell you this is hard. And I trust me, like I am.
[00:35:33] Paul Roetzer: I am very lucky in my life that I run companies and I have for the last 20 years and I've never had to go look for a job, but I know plenty of friends and family and peers in my industry who have, and I understand how hard that process is. All I'm going to say here is like, If you're in a company and they're not going to do this, and three years from now you're going to be doing the same thing you're doing, using the same tech you're [00:36:00] doing, you will have been obsoleted in your profession.
[00:36:04] Paul Roetzer: So I just don't feel like people should be okay sitting still. If they personally feel that they have to do this, then you have to find a company that is embracing this and go be a part of that. The payback for you, if you spend the next three years figuring this out versus the next three years sitting still, it's going to be tremendous.
[00:36:27] Paul Roetzer: and I think that eventually it's going to start to feel very, very helpless for people who are in companies that aren't adopting AI. You're going to feel like you are now being left behind. That is not the case yet. You have not been left behind. If you're in that kind of role, it's still early. We still have time.
[00:36:47] Paul Roetzer: But three years from now, I don't think we'll be saying the same thing.
[00:36:52] Question 12
[00:36:52] Mike Kaput: Okay, we have a bunch of, questions here about AI tools and use cases. Number 12, what is your favorite AI tool [00:37:00] for work and why?
[00:37:01] Paul Roetzer: Alright, so I'm definitely going to let you throw in on this one, Mike. I have a hard time with this one, but I have to say ChatGPT because it is the thing I dominantly use.
[00:37:09] Paul Roetzer: Like if If I stacked all my AI uses up, I would say like 80 percent of them is ChatGPT. Specifically, the co CEO personal custom GPT I built. You can go check that out on SmarterX. ai. We just launched that GPT in a webinar around it. I am, though, very, very intrigued by the voice and video capabilities that are now in ChatGPT as well.
[00:37:30] Paul Roetzer: Perplexity, I'm a huge fan of. I do not use it nearly as much as I did earlier this year. I use ChatGPT more than I am using Perplexity. And then the new ones, Google Deep Research and Notebook LM, I'm very bullish on those. So, ChatGPT, if I have to pick one, is my answer, but I'm a big fan of the others.
[00:37:48] Mike Kaput: Yeah, I mean, ChatGPT obviously just has to be top of the list for me. I would just drill down even further into if you are not trying to push advanced voice mode as far as it [00:38:00] can go in areas of your life, I'd recommend it can be kind of a hack to do so. It's been the biggest thing for me lately. Maybe it's just how I prefer to work sometimes, but honestly, like on a long drive or have like Dead time, you know, where otherwise I'd be just like listening to a podcast.
[00:38:16] Mike Kaput: I have gotten incredible amounts of work done, of problems solved, just using advanced voice mode.
[00:38:23] Paul Roetzer: Agreed. Yeah, I don't use it enough, but when I have, it is awesome, and long drives are a great example of that. And I think even just like the quick drives into the office, I'm starting to do it more and more.
[00:38:33] Question 13
[00:38:33] Mike Kaput: Alright, number 13. Can you share an automation or workflow that's been the most effective one that you've implemented for the team, for yourself?
[00:38:42] Paul Roetzer: Yeah, the one I always come back to just because it's relevant to everyone listening to this is our podcast. That is probably like the campaign that we have done the best job of continually optimizing the use of AI within it.
[00:38:55] Paul Roetzer: Our main platform is Descript. That is the predominant tool we [00:39:00] use to do it. on episode 55, which we'll put in the show notes, Mike and I actually walked through that workflow. It's definitely evolved since then, but the same steps are there. The tools we're using have probably changed a little bit. But you can go hear a lot about that.
[00:39:15] Paul Roetzer: So podcasts would be the number one for me. Do you have one, Mike, different from the podcast?
[00:39:20] Mike Kaput: Mine would just broadly be custom GPTs for everything. For your role, for different domain areas, just building these almost mini workflows with custom GPTs has been transformative.
[00:39:31] Paul Roetzer: Yeah, and if you're not a ChatGPT user, you can do a similar thing with Google Gems.
[00:39:36] Paul Roetzer: Hopefully they're going to keep improving Gems next year and offer more capabilities within them. And then Anthropx, Claude, Projects, I believe. I haven't built one there, but I think that functions in a similar way as well.
[00:39:49] Question 14
[00:39:49] Mike Kaput: Alright, question 14. What would you consider to be the most impactful or beneficial AI use case that you've seen or heard of, in and out, in or out of marketing?[00:40:00]
[00:40:00] Paul Roetzer: Yeah, I'm actually going to piggyback off of your previous answer. Custom GPTs. Yeah. are hands down, like, you know, I think Notebook LM took off for a lot of people because they saw practical use case. I think a mass market or heading toward mass market, actually just this morning or yesterday, I saw that Google actually put Notebook LM on the home search page, which is holy ground at Google.
[00:40:24] Paul Roetzer: So like to inject a project there, you know, that they, they believe deeply and they're seeing strong metrics. So I think the key is. To make something so tangible and simple to understand the value. And so I think that's what Notebook LM did. And I think that's what custom GPTs do. It's like if you say, Oh, you're an email marketer or you're an accountant or you're an HR professional, or you're a CEO, let me build a custom GPT that, that helps you do the things you do every day.
[00:40:54] Paul Roetzer: And they open it up and it just helps and it just works. That is how you create [00:41:00] value. That is how you get adoption within enterprises. Learn So to me, I agree, like if you personalize GPTs for people in their role, that is the fastest way to have success when you're looking at adopting AI in any company.
[00:41:15] Question 15
[00:41:15] Mike Kaput: All right, question number 15. We've got several questions here about our favorite topic of the day, AI agents. With the rise of AI agents that might be able to autonomously execute complex tasks and strategies, how do you see the role of marketers evolving in the next few years? What skills will become indispensable?
[00:41:35] Mike Kaput: How can organizations or employees prepare for this shift?
[00:41:39] Paul Roetzer: So, yeah, I know we have like a couple questions about agents, so I think it's good to just You know, I'll give it specific to, you know, marketers as an example here, but we'll talk more, more broadly as well. So just for context, AI agent, we're currently defining as an AI system that can take actions to achieve a goal.
[00:41:59] Paul Roetzer: So [00:42:00] ChatGPT doesn't take actions, ChatGPT outputs something. It does, it creates a plan, it writes an email, whatever. It doesn't go do something. It doesn't fill out forms, it doesn't complete workflows, it doesn't do those things. So what we're talking about is systems that can take actions. agents are early.
[00:42:16] Paul Roetzer: they are not autonomous, despite what you may hear. we talk about this in episode 124, I think it was, Mike, kind of what is an AI agent. I went through this so you can go back and listen for some more context. But if we think about what goes into an agent, there's five fundamental steps I like to think about.
[00:42:35] Paul Roetzer: So there's goal setting, telling it what it's going to do. What is it supposed to achieve? there is planning. So there's going through setting up of this, the integration of the data, things like that. there is the executing part of doing the actions, going through the 10 steps, 20 steps. That is the part that can be autonomous in, in a way.
[00:42:56] Paul Roetzer: Not necessarily fully, but that, that executing is the part that we're hearing about being [00:43:00] autonomous. Then there's the improving the agent and then there's the analyzing the agent, the performance. So to, to like, don't just listen to me. I'll do Jensen Wong, the CEO of NVIDIA. This is what he said in a presentation in November.
[00:43:15] Paul Roetzer: He likes to think of them as AI workers, like digital workers. These AI workers can understand, they can plan, and they can take action. We call them AI agents, he said. And just like digital employees, you have to train them. You have to create the data to welcome them to your company. You have to teach them about your company.
[00:43:33] Paul Roetzer: You train them for particular skills, you evaluate them after you're done training, you guardrail them to make sure that they perform the job they asked, they're asked to do, and of course, you operate them, you deploy them. So whether it's a marketer, or any other profession, I don't care what you do, the humans are needed to set the goals, plan and design the agents, connect the data sources, integrate the supporting applications and tools, Over C execution, provide the [00:44:00] inputs and iterate and improve them and analyze the performance.
[00:44:03] Paul Roetzer: So that, like if you say, what is a marker going to do? What is anybody going to do? All of those things, like the agents we're going to have in 2025 aren't doing those things for themselves. They, they execute the actions in the middle part. They'll increasingly do some of the other things, but right now, Every profession is going to still need to do all that work.
[00:44:24] Question 16
[00:44:24] Mike Kaput: All right. So this other question about agents kind of piggybacks on that. Like my question is how, this is number 16, how do you build agents? Like do you do it directly in ChatGPT? Is there a particular platform or app that we would recommend or think about?
[00:44:39] Paul Roetzer: Yeah. So this is a great follow on question because again, This perception exists that these things just magically show up and start doing these things.
[00:44:47] Paul Roetzer: That is not what happens. So if you're in Salesforce, you would use their AgentsForce platform. You would go through and define the role, set up the data, do all those things I just walked through. If you're in Microsoft, they have a Copilot Studio where you go [00:45:00] through and build agents. If you're a Google user, they have Vertex AI, where if you're a more advanced person, you can go build AI agents in there.
[00:45:07] Paul Roetzer: It's not, Google Vertex is not for the non technical audience quite yet. They might go there, but you can go do it. Agent. ai is another example where people, right now it's Dharmesh Shah and his team that are building the agents for you, but they're going to enable people to build them. so there's, there are platforms that are starting to allow you to build agents and set the rules for them.
[00:45:31] Paul Roetzer: But, that's, that's, it's kind of like a platform by platform thing. And then I would imagine you could probably do like hugging face. Like if, if you're more technical, if you're a developer, there's probably a lot of other places you could do this.
[00:45:43] Question 17
[00:45:43] Mike Kaput: Alright, we have quite a few questions about AI and its impact on things like agencies or professional services.
[00:45:52] Mike Kaput: Question number 17. With AI potentially reducing the time spent on content creation and strategy, how should [00:46:00] agencies think about reinvesting the time they spend on those things to drive greater value for clients?
[00:46:06] Paul Roetzer: Yeah, so if you have the opportunity, I think in the agency setting, professional services, Education, training, and change management are going to be, you know, a big part of where it's at.
[00:46:16] Paul Roetzer: You know, you have to think about where is this going, so you might expand your services to be things like building agents. Like, that's a very logical thing that people would turn to an agency for if they trust them already. And if, like, let's say you're helping manage Salesforce or HubSpot for somebody.
[00:46:31] Paul Roetzer: It would be a very natural extension of that to offer agent building. Now it's going to obsolete some of your services, but who cares? Like the idea is that you're going to keep having new capabilities emerge because of these AI models that you're going to be able to build services on top of. So that's, that's kind of a look.
[00:46:49] Paul Roetzer: I would look at these immediate service areas like agent building, but I would also think deeply about education, training, and workshops.
[00:46:56] Question 18
[00:46:56] Mike Kaput: Number 18. Any specific recommendations for [00:47:00] language that agencies can use or should use in their client contracts regarding the use of AI?
[00:47:07] Paul Roetzer: you can play around with ChatGPT or Gemini or whatever and draft this stuff.
[00:47:12] Paul Roetzer: I've had some success building policies and guidelines within those tools. I'm not a lawyer though, so I would always turn that over to my lawyer and have them review it. which is really my main thing, is talk to your attorneys. also, you know, again, I ran an agency for 16 years. Sometimes we signed our contracts, sometimes we signed theirs.
[00:47:32] Paul Roetzer: more often than not, it was probably theirs that we were signing. And what I have seen from the brand side is language not allowing agencies to use Gen AI. Where it's explicitly saying, unless you get our permission, you are not to create anything with Gen AI. so that you need to consider. And then the other thing I would just think about from an agency perspective is, you know, pricing and fee models because, you know, those are going to have to [00:48:00] change.
[00:48:01] Mike Kaput: I'm glad you mentioned that because in a couple questions, you're going to get to answer that question too.
[00:48:07] Paul Roetzer: It's a very popular question.
[00:48:08] Question 19
[00:48:08] Mike Kaput: It really is. But 19. So this person says that they're suspecting AI tools will basically, you know, kind of come for what junior associates at their firm. Or any firm are doing, so think agencies, consulting, legal firms, etc.
[00:48:25] Mike Kaput: But we used to live in a reality when junior associates became senior associates, then managers, then principals, then partners. Where are professional service firms going to be getting their partners in an AI world?
[00:48:39] Paul Roetzer: So I actually got this exact question from a law firm. I was, you know, meeting with a bunch of partners and when I explained, you know, went through like state of AI, where it's going, somebody said, oh, so we're not even going to need to hire associates.
[00:48:52] Paul Roetzer: And I said, well. That's one way to think about it, but who are your future partners? And they just stared at me and I was like, [00:49:00] that's on you. Like, I don't know. You probably all want to retire at some point and nobody's going to be left. So, the answer is like, we don't know, like. If I think about professional service firms and again, having run an agency for 16 years before I sold it, I just think there's gonna be fewer humans needed to do it.
[00:49:19] Paul Roetzer: And that doesn't mean that we won't still hire people. It just means we won't need to hire as many people. So if I was like, if I was gonna be done doing what we're doing and I was gonna go start an agency right now, I would do it under the assumption that with 2025's models, this isn't even really looking into 2026 and beyond yet.
[00:49:39] Paul Roetzer: We would need one employee for every three to four hires of what we would usually have done. So if I go back to like 2015 and I'm thinking about our production and the client demand and things like that, I think you could seriously build an agency of 20 people. That does the work of what previously would have been a 60 to 80 person [00:50:00] firm.
[00:50:00] Paul Roetzer: And I honestly don't even think that's an exaggeration. That might actually be a conservative estimate. And you could apply that to client side as well. Like when you're thinking about your marketing team, your sales team, your customer support team. I think we're very quickly in the next one to two years entering a phase where one human can do the work of three to four humans depending on what the profession is.
[00:50:25] Paul Roetzer: And that's a very weird environment. And if, if, so if there's increased demand for your product and services, you're going to just keep hiring people and you're going to do more. Great. Like that company doesn't need to lose people. But if there isn't increasing demand or, or even worse, there is shrinking demand for your services, that company will reduce their workforce.
[00:50:47] Paul Roetzer: And I don't, I've said this on the podcast before, I don't understand the argument against that. Assumption, like I really don't comprehend how that isn't what happens. So, yeah, [00:51:00] I think that's how I would, I would look at the service firm side of it is I think fewer people are going to do the work and hopefully there's demand.
[00:51:06] Paul Roetzer: You, you can still hire, but I don't know you're going to need as many people.
[00:51:10] Question 20
[00:51:10] Mike Kaput: All right. Last question on agencies. Question 20. Do you think AI will change the typical agency pricing model? If so, how should agencies adapt?
[00:51:21] Paul Roetzer: Okay. So I have, I've said this before. My first book in 2011, The Marketing Agency Blueprint, chapter one was eliminate billable hours.
[00:51:31] Paul Roetzer: If you are a firm that is still charging billable hours 13 years later, yes, your model is cooked. Like you cannot charge, unless it's just straight up advisory consulting work, where they're just paying for your knowledge and you say it's going to cost X per hour for you to talk to me. That's a different story probably.
[00:51:50] Paul Roetzer: But if we're charging to produce an output. And you're charging by the hour, and they know you're using GenAI to do it. There is no way you're going to be able to [00:52:00] make the same amount of money doing what you're doing. So you're going to need a lot more work in the pipeline, because you're going to have to be doing it for less.
[00:52:06] Paul Roetzer: Unless you're on a value based model. Whatever that looks like to you, some project fee, a set fee, or, you know, out, out, output, or performance driven, however it is, You need to do it. I would go listen to the episode 127 combo we just had, Mike, yesterday, I guess this, whenever it was this morning, about SaaS pricing, and I think the same principles are going to apply.
[00:52:30] Question 21
[00:52:30] Mike Kaput: All right. Our last handful of questions here are broadly under the category I'm calling what 2025 and or the future holds. Question number 21. As you consider the growth of AI and its impact on business and society. And you think about the opportunities and challenges that 2025 may bring, what one opportunity and one challenge excite you the most or fill you with dread and why?
[00:52:57] Paul Roetzer: So the dread would be already said, it's jobs. I [00:53:00] am obviously have concerns about jobs, in the economy. thing I'm hopeful for the opportunity is that explosion of entrepreneurship. It's getting time back in our lives and it's to see what career paths people create, because I do think like one to two years out, we're going to have this impact on jobs, but we're also going to have these really cool new careers people are creating around AI, like things you and I probably can't even sit here and conceive of yet.
[00:53:27] Paul Roetzer: And so I think that's exciting, but on the entrepreneurship side, like there's never been a better time. to build a business from the start because you just don't need as many people. AI is going to help you do a lot of things. You won't need as much advisory work outside. You're not going to pay all the legal fees and accounting fees and things like that because you're going to be able to do a lot of that for yourself.
[00:53:46] Paul Roetzer: You're still going to need those experts, just not as much. So I think building a business from the start with fewer people is an amazing opportunity. I think having to transform an existing business is going to be painful, like I, [00:54:00] for the reasons I already outlined. If you need fewer people, you're going to have to go through a bit of pain to get there.
[00:54:08] Question 22
[00:54:08] Mike Kaput: Alright, question 22 is a bit related. How do you stay optimistic about the future of humanity, especially the world of work, when the potential near term, potentially advent of artificial general intelligence threatens to disrupt work like never before?
[00:54:24] Paul Roetzer: It's definitely a choice. Like, it's a mindset. Like, if I was dreading it every day, and I was negative about it, and I listened to all the negative voices in the AI industry who were, like, trying to, like, counter the optimism.
[00:54:38] Paul Roetzer: Then I would just, I wouldn't even do what we're doing, Mike. Like if we, if we had to think about this every day and I just assumed it was going to go wrong, I would like, what, what good would it do? So I choose to be optimistic. I choose to believe that the future can be abundant. It can be incredible. We can get time back.
[00:54:54] Paul Roetzer: We can invent new career paths. We can go through a Renaissance in creativity and [00:55:00] entrepreneurship. Like. I think all of those things are possible. I am very much a realist, though. I know there's gonna be bumps in the road. I know it's gonna be hard at times. I know there's gonna be pain in different sectors and different industries more than others.
[00:55:13] Paul Roetzer: but I think net it's gonna be a positive for society and humanity.
[00:55:18] Question 23
[00:55:18] Mike Kaput: Question number 23, what's an industry where you think AI is currently underutilized and an industry where you as a business owner and or as a dad. are personally the most excited to see AI adopted in earnest.
[00:55:33] Paul Roetzer: Yeah, so every industry that's underutilized, let's just be straight on that.
[00:55:36] Paul Roetzer: that is the whole purpose of Smarter X. The X stands for like, pick an industry, pick a business model, whatever. You can build a smarter version of X, anything. And so take your business, you know, whatever it is, manufacturing, retail, e commerce, law firm, accounting firm, whatever. You can build a smarter version of that business.
[00:55:55] Paul Roetzer: And so I'm excited to see what people create in different industries. But if I had [00:56:00] to pick like personally, it's education. Like that's. You know, I'm balanced. I'm fearful of what it looks like. I don't know what college looks like when my kids are going to be there in five and six years. Like, I really don't know that it's going to be able to look like it currently does.
[00:56:15] Paul Roetzer: So I worry about that. But I also think the ability to personalize learning, you know, bring learning to people who otherwise wouldn't have access to it, democratize educations and give everyone like a personalized learning assistant. Like, it could be incredible. You know, we gotta be intentional about getting there.
[00:56:36] Question 24
[00:56:36] Mike Kaput: Question number 24. If you could have one wish granted for the future of AI in 2025, whether that's a breakthrough, a trend, a shift in how AI is used, What would it be and why?
[00:56:49] Paul Roetzer: So I'm going to steer out of the technology side of this one, for a moment and say what I, what I really want is, you know, in our Scaling AI course series, I [00:57:00] taught a course on how to do AI impact assessments.
[00:57:03] Paul Roetzer: And I think those are really, really important. Like, I think that leaders in, in different companies, different industries need to proactively, Look out at the models one to two years out because we can reasonably project the things they're going to be capable of doing one to two years out and say, how does that change the jobs in our company?
[00:57:23] Paul Roetzer: How does that change our industry? How does it change our partner ecosystem? And be proactive in planning for that change. Nobody's doing that yet. Like, I don't know of a company that is doing that. And so that's what I want is like proactively looking at the impact and proactively planning to do this responsibly.
[00:57:41] Paul Roetzer: on the technology side, the things, I don't know if I'm like looking forward to them. I'm just going to tell you what's coming. reasoning is going to get a lot better. So we'll go from 01 to 02 or whatever, 01. 5 or whatever OpenAI is going to call it. Gemini 2. 0 is gonna have [00:58:00] reasoning baked in.
[00:58:00] Paul Roetzer: They're all gonna have reasoning. Memory is gonna become much more significant, and that's gonna be impactful. Vision, as we've talked about, built in, Apple Intelligence has some elements of vision now. You're going to, you know, Project Astra from Google has this vision, like, to be able to see and understand the world around you.
[00:58:17] Paul Roetzer: And you can test it right now in voice mode in OpenAI and ChatGPT. You can go play with this ability to see the world around you. Voice interface is going to be huge and AI agents are keep, going to keep getting better. So like those five areas. Reasoning, memory, vision, voice, action, that's going to happen next year in all these models and a lot of cool things are going to come as a result of that and a lot of more uncertainty is going to come.
[00:58:40] Mike Kaput: Yeah, just piggybacking on that, I would love to just see truly useful, almost unlimited context windows plus memory and we've talked about how those factors can come together because if I could just have an always on assistant that knew truly Everything I chose to [00:59:00] reveal about myself and all the content and context and books and information I've ever read, that would be pretty incredible.
[00:59:07] Paul Roetzer: Yep. Agreed.
[00:59:08] Question 25
[00:59:08] Mike Kaput: All right, our last question here, number 25. What is the one most urgent piece of AI advice you would give to any business professional as they are entering the new year?
[00:59:22] Paul Roetzer: Get through the fear and uncertainty and anxiety and just get started. Like, it is, again, you can feel like it's passing you by, it's not.
[00:59:31] Paul Roetzer: It is early, most enterprises haven't solved for this yet, most educational institutions haven't fully solved for this yet. You have an opportunity to lead, regardless of your age or experience level, and you have an opportunity to reimagine your career. And for anybody who's like early on, you know, that's an amazing thing.
[00:59:52] Paul Roetzer: I think I told this story maybe on the podcast once before, but I gave a talk. I think it was [01:00:00] last year at Ohio university to a bunch of the professors and a professor who was, you know, in his like late seventies, early eighties came up to me after the talk and he said, I'm so envious of you. And I said, why?
[01:00:11] Paul Roetzer: He goes, I would give anything to be in my forties again. Like the stuff you're going to get to see and build and experience. With what you just showed us, it's like, incredible. And It weighed on me, like I thought about that deeply on my ride home that day. because I do think it is like this incredible opportunity we have and this like amazing runway ahead of us to just like reinvent everything.
[01:00:35] Paul Roetzer: And that's, that's very exciting. So, get started and be a part of that.
[01:00:40] Mike Kaput: Well, that's an amazingly uplifting note to end on as we get to the end of the questions. Well, I guess you're right, Brett, but I don't know that. I mean, I'm going into like Christmas and now I'm like, no, no, I'm super excited. I know this is
[01:00:54] Paul Roetzer: like, this is the last thing, like last major thing I do, this week again, we're on December [01:01:00] 17th here and I have like some big planning and vision things I got to do, but like.
[01:01:05] Paul Roetzer: I am looking forward to the holidays to actually step back and just like experiment with some stuff and like get started myself in some ways and try and think about how to like really transform stuff next year in a very positive way. And like, whether it's with my kids, with my own professional life and with the businesses, like, I do just think there's such cool things ahead and, you know, I'm inspired by our community, you know.
[01:01:29] Paul Roetzer: Like 9, 000 people or something in the Slack community now and thousands of people come to events. And it's just like, I love hearing those stories and just seeing what people are doing. So yeah, I mean, as we said in episode 127, Michael, I'm just grateful that we have a voice that matters to people and is helping people.
[01:01:46] Paul Roetzer: And I'm, I'm appreciative of being able to be part of the AI journeys of all of our listeners and viewers, and we're all figuring this out together. So it's, it's going to be, you know, fun and overwhelming and exciting and [01:02:00] terrifying. All those things in one, so we'll go through it together, though.
[01:02:04] Mike Kaput: Well, Paul, as always, thanks for sharing all your insights and thanks for answering all these questions.
[01:02:09] Mike Kaput: I think the audience is going to get a ton of value out of this.
[01:02:12] Paul Roetzer: Yeah, thanks for pulling it all together, Mike, and thank you again to everyone who's listening and who submitted all these incredible questions. We appreciate it. Thanks for listening to The AI 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.
[01:02:43] Paul Roetzer: Until next time, stay curious and explore AI.
Claire Prudhomme
Claire Prudhomme is the Marketing Manager of Media and Content at the Marketing AI Institute. With a background in content marketing, video production and a deep interest in AI public policy, Claire brings a broad skill set to her role. Claire combines her skills, passion for storytelling, and dedication to lifelong learning to drive the Marketing AI Institute's mission forward.