What if the technology that's keeping you up at night could actually become your biggest competitive advantage?
Here's what's happening right now: Business owners everywhere are watching AI generate content, create designs, and handle tasks that used to require human expertise. The fear is real because the question feels existential – if your clients can do this themselves, what happens to your value?
But what if you're looking at this completely backwards? What if AI doesn't replace human expertise – what if it makes the right kind of expertise absolutely indispensable?
That's exactly what our guest discovered when he conducted a fascinating experiment. Robert Capps tried to write an entire New York Times Magazine article using AI. The result was polished, engaging, and would have fooled most readers. But here's the twist – he didn't publish it. Instead, he wrote one of the most important pieces about the future of work that I've read all year, and it reveals why human judgment just became more valuable, not less.
Robert brings a unique perspective to this conversation because he's lived at the intersection of technology and creativity for over a decade. As the former Editorial Director of WIRED magazine, he guided the publication to 21 National Magazine Award nominations with eight wins. He's overseen special issues guest-edited by Christopher Nolan, Serena Williams, and Barack Obama. Now, as a writer whose work appears in The New York Times Magazine, Robert is conducting real-world experiments with AI that reveal insights every business leader needs to hear.
The AI Hat Podcast host Mike Allton asked Robert Capps about:
✨ Responsibility Advantage: AI can create content, but only humans can take responsibility for strategic decisions and client outcomes.
✨ Taste Over Tech: When everyone has access to the same AI tools, your ability to make creative choices becomes your primary competitive advantage.
✨ Integration Opportunity: Position your agency as the bridge between AI capabilities and client business needs, becoming indispensable through expert curation.
Learn more about Robert Capps
- Connect with Robert Capps on LinkedIn
Resources & Brands mentioned in this episode
- A.I. Might Take Your Job. Here Are 22 New Ones It Could Give You. by Robert Capps, NYT contributor and former editorial director of Wired
- Bill Wasik
- The H.U.M.A.N. Framework for AI Integration
- The AI Revolution: How It’s Transforming Business (and What You Need to Know)
- ChatGPT Agent
- Robert Seamans
- Sal Khan
- Rick Rubin
- AI Work Buddy Mini-Course & Community
- Ethan Mollick
- Ann Handley
- AI Primer: A Comprehensive Guide
- Explore past episodes of the The AI Hat Podcast podcast
Full Transcript
(lightly edited)
Why AI Will Make Your Agency Indispensable: The NYT Magazine Article Every Owner Must Read with Robert Capps
[00:00:00] Robert Capps: AI can guide you and help you find white space and do research for you and all this stuff, but ultimately you are making the choices for what, for producing that outcome. And I think of that as just extremely entrepreneurial. I think we're entering a very, very entrepreneurial age with AI. It's just more people within company, outside of companies, within companies.
[00:00:21] Get to stop and think about entrepreneurially, about creating something new or trying to do something new rather than just filling in the, the detail work, the execution work of what it takes to build that. And, and so I think people with really strong taste are gonna be very in demand and very needed.
[00:00:37] And I use the term designer in the article, which may or may not stay in vogue. I, when I think of designer, the, the definition of designer that I've used through my work at, at Wired and Godfrey data and some other places has been a series of creative choices leading to a desired outcome. Right? And that's what I basically think that you're do, you'd be doing with AI is you're making these choices and they are creative choices, even if you're building a business or creating an HR department or whatever it is you're doing, you are making these human choices because you have this vision of this outcome you want.
[00:01:13] Mike Allton: Mike's got The Hat, the AI kind. Unlocking power in business, you'll find. Cut through the hype, explore the tech. Every week, new ideas to check.
[00:01:47] Allton leads us on a digital quest. AI secrets he'll always invest. Tune in tight, don't miss a beat. Knowledge, groove, keep you on your feet. Listen up! To the AI flow. Business growth, here we go. Cuttin' edge insights, that's the plan. With The AI Hat you'll understand.
[00:02:22] Greetings program. Welcome back to the AI Hat Podcast, where I selfishly use this time to pick the brains of experts at harnessing the power of AI across all areas of business. From streamlining operations and boosting productivity to getting a competitive edge and driving explosive growth. Oh, and you get to learn, too.
[00:02:38] Subscribe to be shown how to prepare yourself and your brand for this AI revolution. And come out ahead. But what if the technology that's keeping you up at night could actually become your biggest competitive advantage? And here's what's happening right now. Business owners everywhere are watching AI generate content, create designs, and handle tasks that used to require human expertise.
[00:03:00] And the fear is real because the question feels existential. If your clients can do this themselves, what happens to your value? But what if you're looking at this completely backwards? What if AI doesn't replace human expertise? What if it makes the right kind of expertise absolutely indispensable? Well, that's exactly what our guest discovered when he conducted a fascinating experiment.
[00:03:22] Robert Capps tried to write an entire New York Times Magazine article. Using Ai, the result was polished, engaging, and would've fooled most readers. But here's the twist, he didn't publish it. Instead, he wrote one of the most important pieces about the future of work that I've read all year, and it reveals why human judgment just became more valuable, not less. Robert brings a unique perspective to this conversation because he's lived at the intersection of technology and creativity for over a decade. As the former editorial director of WIRED Magazine, he guided the publication to 21 National Magazine Award nominations with eight. Wins. He's overseeing special issues, guest edited by Christopher Nolan, Serena Williams, and Barack Obama.
[00:04:03] Now as a writer whose work appears in the New York Times Magazine, Robert is conducting real world experiments with AI that reveal insights every business leader needs to hear. Hey, Robert, welcome to the show.
[00:04:15] Robert Capps: Hey Mike. Thanks for having me. Glad to be here. My pleasure. I'm so good.
[00:04:21] Mike Allton: Yeah. Right. This is gonna be a great conversation, but let's, let's talk about this article.
[00:04:25] 'cause you started off by admitting you tried to ride it with AI first. Walk us through that experiment and what made you decide not to use the AI version?
[00:04:35] Robert Capps: Yeah. The, I I was ha the New York Times Magazine was doing this big AI issue, and I was hashing over the idea of doing something on, on human AI jobs with my, with my editor Bill Wassick, who has another amazing piece in the issue.
[00:04:50] And as soon as I got off the phone with him, I was, I should just, I should just have AI write this article for me. And I, and I wanted to do it as a lark. Yeah, I thought it would be, I, I mostly thought, I was thinking originally that it would be funny. To just do it and have the whole thing done in like an hour or two and then just send it to Bill and be like, there you go.
[00:05:11] All done. Where's the, here's the invoice. Which, would've been, would've made it my most profitable article I've ever written. If I could pull it off in that amount of time. But it's also like, isn't that the point, right? Like, AI is supposed to just be able to do these things and allow us to go further and faster and, and so, so I set out to try it.
[00:05:31] I think, in, in, in, in all transparency. Like I, I never thought that it would run or that I would let it run for, for issues. I'll, I'll get to, but I, I fed the assignment letter and some documents into chat GPT and put it into deep research mode and had it prepare a big report about, where, what new jobs for humans AI might create.
[00:05:55] I tried a similar thing with Claude. I don't go into the full details of the experiment in the article, but but I, but I, I worked at it pretty hard and then, I took that report and some other stuff and I said, write this article. And it, and it wrote an article. And the article had a it was very, it was a very light, lively tone.
[00:06:14] It had some really lovely turns of phrase. It had some good humor in it. It was very punchy in a way, but it, it. It, it, it had other problems, right? Like it that you might be able to predict it. It completely made up sources, it completely made up quotes. It. It, it, it's the kind of thing that if you, if you actually filed would, would get you banned from journalism for the rest of your life.
[00:06:39] Which, we have a, we have a little bit higher tolerance for AI making those mistakes now, but, but I think probably more profoundly what I found is because I hadn't done any of the actual work, right? I'd repaired this report and I'd read the report, but like I hadn't done any reporting and I hadn't really spent a lot of time reading research papers or anything, so I couldn't even really tell you where it was Right. And where it was wrong. Mm-hmm. And I couldn't tell you where it was overstating things or where it might be understating things. And I couldn't give you my sort of, stamp of approval or sort of my endorsement that what it was saying was fair and accurate, right?
[00:07:16] That like, oh, this seems like it probably will like it, it read, it read really smoothly, it read really punchy, but it just, there was no way for me to vouch for it. And that sort of opened up the first philosophical window that I wanted to think about in terms of what do we. What is our responsibility to our work product when we're engaging with Ai and AI is in incre, like has a vast store of knowledge, is incredibly confident, can really is, is, is fair, is you know, shown to be very persuasive.
[00:07:51] And can, and can make these logical arguments, but it, it's, it's just, it gets pretty slippery when you're like, okay, well this is gonna represent something that I'm vouching for. That's something that I say is fair and accurate and true. And, and and so it did, that sort of opened up the first area where thinking about, okay, AI takes off, AI is used to do more different kinds of work. Like what is the unique role of humans still need to be and like, where does AI actually need, need humans? And trust became the first, the first opening there, like right? Like how, like how, like how are we thinking about how much we trust the ai?
[00:08:31] Mike Allton: Yeah. That's the real crux of the issue. At what point? Does the AI stop and the human has to take over or lead or initiate? We have an entire framework at the AI hack, the H.U.M.A.N. Framework that helps agencies and businesses understand how to look at ai, how to integrate it. But, but you, you really, you said it so well.
[00:08:51] It's, it's incumbent upon us to understand the topic on which we're asking AI to, in this case, create a piece of content. Because if we have no knowledge of that content, we have no idea if the AI is just making it up from whole cloth, where it's falling into errors and, and again, a lot of my audience are marketing agencies, right?
[00:09:10] So they're working on behalf of clients and, and we know many of them are using AI for well reasons, good reasons. But if you're asking the AI to just write a piece of content on behalf of a client, maybe a business that you're not familiar with and you're not taking the time to vet that information, who knows what you're putting out there.
[00:09:28] And so you talk about this thing called the responsibility hurdle that AI can't cross. Can you explain what you mean by this and why it matters to professional services?
[00:09:39] Robert Capps: Yeah, AI is not, it's, it, it, it's not it's not part of our moral world, right? Like, and it's not it's, it's not, it's, it's using its algorithms and it's training and the data that it's collected to like.
[00:09:55] Assemble these things, but it's not, it, it's not able to take re it's a machine. It can't really take responsibility for the outcomes of that product. Like that has to be a human right. And that can be in small ways and in big ways, right? Like so small ways. If you, and if you're in a, I put this example in the piece.
[00:10:13] If you're an HVAC contractor, right? And you're, and you're using ai to do the parts of your job that, that you, that aren't really what you feel is like core to what you want to be doing, which is the paperwork, right? Like, contracts and estimates and all kinds of stuff and just try, try to making that part of it faster.
[00:10:30] But ultimately, like those have legal implications and the AI doesn't really, the AI is gonna do, is gonna do, it doesn't really care 'cause they can't care whether it gets it wrong or not. But you're. You're on the hook for that. So at some, at some point, there has to be a human in the loop, so to speak, to be like, I, I accept responsibility for this document, even if it's created by ai.
[00:10:53] And that goes like way, that starts at the, just the very base level. But, but the implications just grow from there, right? Like you talk about putting AI into. Into weapons in our defense system, right? Like, who is accepting responsibility if a, if an autonomous weapon kills somebody, right?
[00:11:11] Like at some point it's gonna, it's gonna track back to a human. And then there's like lots of places in between. And so I think that, a lot of sometimes. When you think about big companies and people talk about, oh, big companies move slow and big company IT departments can be a little bureaucratic.
[00:11:26] And like the reason that a lot of re, a big reason why some of that happens is because of just accountability, corporate accountability. You have to build systems that are defensible and that have to be defensible to clients, to investors, to board members, to to, to all kinds of people. So you can be like, well, why?
[00:11:45] When something goes wrong, and be like, why'd this go wrong? And be like, well, here's all the systems we had in place. And people are like, okay, that's logical. It's just an error or whatever. And, and we, and we, and we build a chain of responsibility. And I think as we integrate ai, that chain of responsibility gets more complex, right?
[00:12:01] So you start to see these roles where people have to come in and really think about that chain of responsibility. And, in, in extreme cases, they might need to go in front of a judge and jury and explain the chain of responsibility and that the, yeah, I made a mistake. And, and it has to have a logical framework that feels.
[00:12:18] Acceptable and defensible and, and part of the moral universe that a corporation or business or, or whoever exists in. And so one of the, one of the jobs I talk about. Is this the rise of AI ethicists, right? Like, and that's people who can build these chains of responsibility, these chains of logic that are defensible and know the AI strengths and know the ai we weaknesses and have properly accounted for that and have, have properly vetted things in, in, in in ways that are explainable to help make the AI explainable because AI can be quite unexplainable in.
[00:12:52] Sort of how it reaches its decision. So I think one of the ironies I like to tell people is like, like ai, AI is getting better at coding. So maybe like some of those computer science graduates are gonna struggle a little bit, but like it may produce a real boom to philosophy majors. Who come out and can, can play the role of ethicists, mm-hmm.
[00:13:13] In corporations as they start to think about, because you have to think really philosophically about like how you feel like the AI is okay, and where you need someone to accept this responsibility and where you need to have a human in the loop to step in.
[00:13:29] Mike Allton: Well, I think you're absolutely right about how we're going to see a shift.
[00:13:33] Roles and a predominance of roles. But you raised such an important point about the ethics and the responsibility. Folks listening might be thinking, ah, Rob's just being an alarmist ai. It's not gonna be able to do that. Folks we're recording this on July 17th and hours ago. Open AI released their Chat G PT Agent, which is a step above their operator machine, which means it can use a virtual.
[00:13:55] Browser and do all kinds of web-based tasks completely autonomously. And this really is just the beginning. By the end of 2025, early 2026, we're gonna have completely autonomous agents, which means you're gonna be able to ask the AI to go do something and it will just go do it on its own, maybe even without you asking it to do it.
[00:14:13] So these are the kinds of things that we need to be aware of. As business owners, as human beings, right? And just be aware that we need to have that human in loop. As you've said a couple times now, in your research, I think you identified three areas where humans actually become essential. I think you talked about trust, integration, and taste.
[00:14:33] Can you break down what each of those looks like in practice?
[00:14:38] Robert Capps: Yeah, so, so trust is what we've been talking about, and it, it has a wide range of implications that, like, there's, there's, you need a human in the loop in certain things, in certain, in, in certain systems. You just, or in certain instances, you just want a human in the loop, right?
[00:14:53] Like, and I think, like, like Klarna, which tried to go as far. Into using AI as it possibly could and, and use them. The AI for one of the big things was its customer service call centers found that at some point in, in like customer service. I could be very good at a lot of things and very good at helping people, but like at some point there would just be instances where people just wanted, the preference was just to talk to a human, right?
[00:15:22] Like so, so, because it's just, we just trust other humans in a way that, that machine's frustrated us, right? So there, there, there can be this preference issue where it's, it's, you just to show that trust you still, and, and Klarna ended up hiring more humans into the system to play that role.
[00:15:39] Alongside the AI because it's just, that's where the trust bounds were. So this, this whole world of trust.
[00:15:45] Integration was one that I talked a lot about with a guy named Robert Seamans, who's a, who's a professor at NYU, who studies a lot, who studies AI and economics and. That's really about the intersection of the technology and the business, right?
[00:16:03] So the integrators are the people who understand both. So, and these might be more temporary roles for the next 10 years or, or as AI gets onboarded, but it's the people who like really understand the models. Really understand how the AI works and, and what needs to be done, but then also really understands a given business, right?
[00:16:23] So understands the customers, understands corporate structure, understands like the different needs that it might hand and have. And so they can sit at that intersection and think deeply about like where the AI will be most useful. Where, where it, it. Might not be useful, where it might need the humans mitigating it.
[00:16:43] And so it can be things like keeping track of the models, right? So I talked to Sal Khan at Khan Academy and KT Academy the sort of learning empire. It builds tutors to help kids in, in math and science and English, and writing and, and, but the models are changing.
[00:17:01] There's, there's different models from different companies and they change every few months. And some are better at algebra and some are better at writing. And so just keeping up with those models and knowing where they're weak and knowing like where they're prone to hallucinate and might need.
[00:17:15] To be checked and, and knowing which is better at what. So like, that can be, right now, a full-time job for someone when you're building something that is a wrapper around one of these models, right? Like if you're using, if you're, if you're building as they do tutors that let's sit at the models, you, you need to keep up with that constantly.
[00:17:33] So an integrator will sit there and figure that out. Or it might be like, how is the ai, how are they, can the AI work best in a company's sales process and, and like, where can it step in and where do you still need the human to work? But it might be, as you talk about coding, an example I bring up as the software plumber where someone is, so in traditional coding you're, you're writing the software, but now more people, more people quote vibe code and they're, they're coding through prompting.
[00:18:00] Then the systems become more and more agentic and so you're sending out these agents to do the coding and build the systems and then something goes wrong and you don't know what it wrong. And it's, it's, it's not quite debugging code. 'cause literally what you're doing is you're like digging through the different.
[00:18:15] Levels of age, agentic AI to figure out like where the one thing that went wrong that cascaded the system. So it's a little bit more like, snaking the pipes as it were, like software, plumbing, and so it's really just those technical roles that really think about the AI and then the business and, and understand both.
[00:18:32] Then finally, I think the one that I found most exci, the people often find most exciting is taste. And that is that, ultimately when we're, when we're.
[00:18:42] Conducting any business like there, there, there does come down to a taste factor. And that can be a creative business or it can be a non-creative business. And, I, I open the, I start this section in the piece with the story of Rick Rubin, the famous music producer and his interview on 60 Minutes, which has gone widely viral, or Anderson Cooper is asking him very confusing.
[00:19:02] What is it you actually do, right? Like what is your role here? Like, do you know how to work a soundboard? And he is like, no, I don't work a soundboard. You know how to play instruments? No, I don't. I, I know, I know almost nothing about music. And they're like, well, what, what do you do? And, and he says, well, my, I have a really confident sense of my own taste, and that is proven helpful to artists.
[00:19:21] And like, I, I think that probably really undersells what Rick Rubin does. Like, I think like that he's he know he's a coach. He's a lot of things to the people he works with. But this idea that someone is really valued for their strong, confident taste, I think really resonates in an AI future as you think about.
[00:19:37] You know what we'll be doing when we have all these tools to do a lot of the gut work and a lot of the different things is we have to like create a vision for what we want. Right? Because A, it doesn't want anything on its own. It's not, you have to. Somebody has to be directing it. And so if you have a vision that, and you can make really bold choices and be really confident in your choices, and if those choices can lead to really economically viable or even powerful things, then that's a really important role that the human still needs to play.
[00:20:10] And that can be in, like I said, filmmaking and podcasting or other things, but it can also be in. Creating a product, right? It can be in creating a service. It's just like, what do I want this to be? How is it gonna be unique? Like, how is it, like what's the, how is it gonna be different than what's out there?
[00:20:28] How am I gonna like form it? And AI can guide you and help you find white space and do research for you and all this stuff, but ultimately, you making the choices for what, for producing that outcome. And I think of that as. Just extremely entrepreneurial. I think we're entering a very, very entrepreneurial age with ai.
[00:20:48] It's just more people within company, outside of companies, within companies get to stop and think about entrepreneurial, about creating something new or trying to do something new rather than just filling in the, the detail work, the execution work of what it takes to build that. And, and so I think people with really strong taste are gonna be very in demand and very needed.
[00:21:08] And I use the term designer in the article, which may or may not stay in vogue, but I've, when I think of designer, the, the definition of designer that I've used through a. Through my work at, at Wired and Godfrey data and some other places has been, a series of creative choices leading to a desired outcome.
[00:21:27] Right? And that's what I basically think that you're do you'd be doing with ai is you're making these choices and there are creative choices, even if you're building a business or creating an HR department or whatever it is you're doing, you are making these human choices because you have this vision of this outcome you want.
[00:21:45] And I think that like, that's where it gets exciting. And when people think about. There's a lot. There's, there's, as well, there's a ton of fear, right? About ai, right? A ton of uncertainty, a ton of fear, and it's gonna take jobs and it's, and like I'm not, and, and all of that, you, there might be serious disruption.
[00:22:04] It might cause a lot of jobs. I'm not trying to be any sort of AI ap apologist for that, but I think that there is another way to look at it more optimistically and when people are expressing that fear to me. I often talk about, well think about do what I did and think about what it is you wanna do, like what it is your.
[00:22:25] At work, whatever it is. And like, think about like your opportunity to do that with AI and, and you'll quickly see where the AI falls down, where it's not ready yet, where it can't do it. You can quickly and, and you can start us to think expansively, right? Like you can start to think like, well, if I can, if it could help me with this, that would actually be wonderful.
[00:22:45] And, and so one of the, and, and the, the thing is we're not. We're not really in an, in as, as advanced and technological as we are. We're not in this like crazy era where everything's figured out and like we're, we're sort of like, like, it, it's just like, it's just, we're just, we, we've, we've solved it all, and now it's just a matter of how efficient we can be because that's not true at all.
[00:23:08] Right. Like, it's like there's shortages of teachers and doctors and, cybersecurity specialists. There's like all kinds of shortages we have. All kinds of problem. Problems and energy and climate change and urban planning and housing and there's just, there's still so many problems. And when you think about like.
[00:23:26] Okay. It's under threat on the entertainment industry. Do like, it takes, like, what does it take to make a, like a, a like Hollywood film right now? Like a couple hundred million dollars and a few thousand people. Like what does it take to make an amazing piece of like really, really professional level software right now?
[00:23:42] Right? Like years and like, how many man hours? Like what does it take, what does it take to do these things? And you're like, oh, there's, we actually have a lot of. There's a lot of room to, to improve before we're really just like, okay, we're just, we're just losing jobs. And I think that, I think that the companies that, I think there's a certain amount of weird performativeness that the companies are going into where it's like, we're, we're just gonna, we're going all in on efficiency, right?
[00:24:10] Like, we are gonna shrink our workforce and we're gonna, and, and, and I think that, like, unfortunately, I think that people can get a little bit of a market bumped from that because they feel, because obviously the ability to grow your bottom line while shrinking your employee costs is like a, a sort of holy grail moment.
[00:24:28] But like, yeah. But I feel like that's really, really limited in thinking and I think the companies and people who think about like, what, like, like, because to me that means you just don't know how to deploy human cap, redeploy human capital. You just, you're out of ideas of like how to grow and move forward.
[00:24:43] And so you, your only idea is to get more efficient. Right. Like, 'cause you should be able to have the same amount of people and like just do new things, right? And that's the sort of, that's the sort of dream of ai. And so like I think that those companies that just focus on efficiency, I think they're gonna get run over, right?
[00:25:00] Because I think that the people who think expansively are gonna grow and expand. And I use the, the example of of robotics industry in the article where, you know, as companies. As manufacturers used robots, they tend to grow, they tend to have more employees than companies who didn't use robots.
[00:25:23] Now the sort of like, people don't really know why that is, but the best thing thing is they speaking, laugh out
[00:25:30] Mike Allton: loud. When I read that
[00:25:32] Robert Capps: is, is that but what
[00:25:33] Mike Allton: they don't know why.
[00:25:35] Robert Capps: Yeah, it's not, I mean from a, from a scientific academic, like research, like provability kind of way. They're like, well, we haven't, we haven't proved it yet.
[00:25:42] And this again, was from Rob Seamans. But like, they're probably growing because, and, and then, and they hire more people and they start more factories and they grow. And then people that don't do that sort of lose out to them. So the people that, that don't use it shrink.
[00:25:58] And this is why I think the people, and similarly, I think the people are really focused on efficiency and like, let's just have as few employees as we can. Like, they're gonna get run over by people. Like, no, I, I want more employees and I'm gonna use them AI to do more forward and I'm gonna find new things to do and I'm gonna find new avenues and I'm gonna grow.
[00:26:14] And I think that that sort of will ultimately win out. Now the question is like, how painful does it get in the meantime, which. It, it, it, it could get painful, but I think for, hopefully, hopefully we avoid that. And I think that just people should think about like, what do you want in, in your job?
[00:26:31] And whatever you do, and I'll just give you an example. Like, I, I make documentary films is one of the things I do in addition to writing and, it's, it's the ai threatens the creative industries, right? Like for, for legit reasons. But like when I think about. Like I'm making a documentary film and and let's just say it has a budget of a million dollars, right?
[00:26:52] Like, that is incredibly expensive, right? Like, it's cheap as hell for a documentary film, but like, it's, it's, it's, it's, it's expensive to me as a person. And I think like, well, like, what can I use ai? Like what, where theoretically could AI help me? Right? Like, and it, and it, I don't wanna, I don't wanna replace my editor.
[00:27:11] I don't wanna have AI edit the thing for me, right? Because the editor is like, is a key collaborator and I need his taste and I need, I need all the human things that we talked about. But like, would I like my editor to be able to do his job in 10 weeks instead of 30 weeks? Because he doesn't have to like, manually load every clip and like manually adjust every frame and like it can be a little bit faster with color and sound balancing and like all, all, all sorts of other things. Yeah. And I think he'd like that too because he would really focus on the part of his job where you'd like, which is making the edit really have an emotional punch to it. Right. And so like, like through that, I would love to get our 1 million documentary down to 500,000.
[00:27:49] Right. And then we could make. Two documentaries for that 1 million. Right? And, and like we'd still work the whole time, but like we'd produce more and it would be a little bit more risk tolerant. And, and, and so I just think there's lots of things if you start thinking about I'm using my taste and I can use these tools in some way to expand that, that you can start to think about it optimistically for yourself, which I think is useful for people to do.
[00:28:15] Mike Allton: Yeah, it's funny, I, I definitely saw myself as an AI integrator. As I was thinking through what you were sharing through the article. My wife would tell you, I have no taste whatsoever, so that's not gonna work out too well for me. But I, I really am a historian. So when I say things like, we're going through an AI revolution, I'm not being flippant.
[00:28:31] This is the fourth industrial revolution. And, and folks don't quite understand how that plays out historically. And even though it's going at a far more rapid pace than all the previous industrial revolutions, there will, as you said, be job loss. And what I give a talk which is called the AI Revolution and How It's Impacting Businesses, the last 20% or so of that talk is all about.
[00:28:52] The future of work and I share statistics from the World Economic Forum and they said, look, in the next decade, 92 million jobs are gonna be lost or impacted by ai, but we're gonna gain 170 million new jobs. Which are the kind of ones that, that you're talking about now or jobs shifting from maybe computer science to philosophies you mentioned before, which is opportunity for people to focus less on the stuff that's drudgery, that's routine, that's repetitive.
[00:29:18] The way I put it is focus on more strategic work. I loved how you put it earlier. Be more entrepreneurial. I think that's a much better turn of phrase, but folks, we're talking with Robert Capps about the future of work due to this air revolution. I've got seven more questions you aren't gonna wanna miss, but first, a quick word about how you can use AI to help with your work right now.
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[00:30:41] So Rob, let's, let's talk about some of these roles that, that you mentioned up, because I just think it's fascinating. You talked about AI personality directors and differentiation designers. Can you paint a picture of what you think like the day-to-day might actually look like for some of these roles?
[00:30:58] Robert Capps: Yeah, I'm, I'm probably gonna hit a limit there, but, yeah, it, it, what's funny is, I, I, I went out and talked to all these experts, right? Like, a lot of academics, a lot of, a lot of people who do a lot of thinking about this and who've done a lot of experiments with AI and like nobody was, like it, all the conversations got really philosophical really quick because the models are so fast moving.
[00:31:22] And it's just so hard to tell. So it was like building these frameworks. It was like, well, we think, or I came to the conclusion that it's like these trust and trust and taste and integration. There's just some things in there like the personality director, right? So when you think about, companies will be, and they already are customizing AI to their organization and there's a lot of power in doing that because the AI can use your documents and your IP in, in, in your meetings and your, transcripts and everything. To really help your organization from the internals you can be like, who said, like somebody said something in a meeting that I need to find right now, and they can, pull it up right there if it has access.
[00:32:05] So there's a lot of advantages on having a custom AI built around your company's data. But then, you gotta start to think about like, what is that, what is inner interacting with that ai like, and that's, that's a sign of company culture. What that AI is like. And so it, we've seen ais that can be cloying and flattering, right?
[00:32:24] Like, like, I, I love, I dunno if you use Chat GPTs Monday, which is like sarcastic and snide and, and I think as these ais get more integrated, like you're gonna need to think about like how and everybody across the organization is interacting with it. Not just technical people and, and not just creative people, but like, finance and HR and, and, and everybody is interacting with it. So it's a sort of symbol of your couple of your culture. So what do you want that personality to be like? And that'll become even more profound when it starts to spill over because people are talking, 'cause customers or people outside the organization are talking into it.
[00:32:59] So I think the person's role is to guide the training of the AI and try to establish. It's voice, it's probably a wrapper around one of these other things, but you want it customized to respond, certain ways to behave, certain ways to like have a certain tone to be helpful, but like, you also want it to be really honest.
[00:33:18] So I think that is, is a little bit of a, it, it's gonna take knowing that technology, but then really working with the training data to get that to get that that model. Working the way that you want it to? I think that, and that's,
[00:33:36] Mike Allton: yeah.
[00:33:37] Robert Capps: Yeah. And, and I think that that's, that's, as you train it, it's, it's a lot of working with the, the model and like adjusting the data that you're feeding it and and then, trying to get that to hold.
[00:33:49] Mike Allton: Yeah. I there's a whole section in that AI work buddy where I have people tell the ai, what kind of personality tone just in their interactions back and forth, but that's on an individual level. So you're right. There's a, there's a whole world out there for folks to spend time thinking about how are these AI systems gonna interact with the entire company or with our prospects or with our customers?
[00:34:08] 'cause those are important considerations that that could be easily overlooked. One of the things you talked about were these AI integrators, right? Who are bridging the technology capabilities with business needs. What do you think makes someone, I dunno, effective in that type of role, do you think?
[00:34:26] Robert Capps: I think really understanding the business, right?
[00:34:28] Like, understanding the technology and understanding the business, but like what their because you need to, whatever it is you need to understand. You know what the customers are like, what the sales cycle's like. Like what the salespeople are like, right? Like how are you bridging all those things?
[00:34:45] There might be an instance where you need to understand who's ready for what when, right? Like you can see like, okay, my sales team is chomping at the bit to get this ai. My HR team is completely concerned about it, right? Like I can't, like, so just belligerently, forcing the systems on people might become productive, so, okay, what do I need to do to bring the systems along so they're effective where they're not just providing my. Sales team with garbage or hallucinations or things that aren't helpful. Like what do, how do I need to adjust the systems for their needs, but then how do I need to adjust the people? How do I need to bring along my HR department to warm them up and get them to understand and, and see potential in the ai?
[00:35:24] So I'm bringing them along to get the ai. So you're working both sides of the balancing act of thinking about the people and the, and the process that already exists, but then also the AI and figuring out. What needs what to make them successful because ultimately, it's about making the, the AI successful in the context of a business.
[00:35:48] Right. And so I think that if you, I do think that if you're belligerent about it and you're just like, everybody should use ai now, here's chat, GPT licenses go, that is not really you're not really doing what you sh all you should be doing to make it successful because you can't just, you, it, it, it's a tool and people need training and you need to think about, the trust issues and all the other issues around it.
[00:36:13] And where, like, where does the human close better than the ai? Where does the AI actually do better? Like, and that could be in, in a hospital setting, like WW does a human get the better result does an AI get the better result? Does a human hybrid AI team get the better result? Like all of that needs to be solved and figured out and quantified and you need data behind it and you, so there's just a ton of work that's gonna go into like figuring that out in every organization.
[00:36:39] And because ultimately. You're trying to make the AI successful within the context of your organization. You're not just trying to force your organization AI on your organization because that's just, it's, it's either not gonna work or it's not gonna work to the, to, to the level that it could.
[00:36:58] Mike Allton: Oh yeah, I could not agree more. For my last question, Rob, I just wanna circle back to that framework of trust, integration, and taste that you talked about. Of those three, which do you think represents kinda the biggest opportunity for professionals, service providers, business owners right now?
[00:37:17] Robert Capps: Well, I think they all do, yeah. I think that the most obvious one right now is gonna be integration. I think that that's the one that people are ready for. I think all it's already been announced that all the big sort of consulting companies are trying to add integration capabilities into their, into their offerings.
[00:37:36] Right. The, the. PWCs and you, they're all, they're, they're all racing to get there. And I think a lot of companies like really need help thinking about, okay, well I'm hearing about ai, but like, how does it, how is it really effective? And I, and, and I think it really wants to be thoughtful. And it's funny, I was, I, I can't remember one of the experts I was talking to, he was like, well.
[00:37:57] You've been this, like, you've been working on this, doing these journalism experiments, including trying to write this article. Like you could be a journalism in integrator, right? Like, you, like someone who's really like, okay, well where does this really make sense and where does it not make sense?
[00:38:11] And it can just be little, like in the journalism example, and this is one Ethan Mollick talked about. This is like, I, I feel like for a long time there was people saying. Oh, it's, it's great at just creating a first draft, right? And first drafts are the hardest things to create. And so, man, to make a first draft, and then you're, you're just off to the horses.
[00:38:30] But like, I actually think that that's a terrible idea. I think that you should not use AI to do your first draft. I think that, and Ethan, as Ethan Mollick said, he is like, I don't use it to do my first drafts in academic thinking because it'll dominate my thinking, right? Like it'll. It, it, it's too much too soon.
[00:38:47] And it doesn't give me the space I need. Like I need to think, I need to think my writing. I need to write to get my, my thoughts down. And I think that's probably really the case. So it's like, I think there needs to be a lot of experimenting and understanding like where, in a specific company, like not just where it can be used, but like what, like helping people with the process that makes it most fruitful and not there, there, 'cause there is this risk that AI diminishes your capacity. If you use it wrong, right? It diminishes your think. It can diminish your organization's thinking. It can diminish like your, your your company's resilience. It can, it can have these adverse effects that you're probably not really thinking about. So you need to have, think about processes where it's making you stronger and not weaker.
[00:39:33] And I, and, and I think that that's the most immediate opportunity that a lot of companies are going to understand is that they need help. Solving that. And I think you, I, I am sure you saw that, that at the really top end, like OpenAI itself just announced that it's going, it's going to, I don't know, take on consulting gigs on the $10 million plus range.
[00:39:54] Right? Like they're, they're like, okay, well, we'll, we'll help you integrate. Like, you have to be a pretty, you have to be a pretty substantial organization to take on a $10 million consulting contract. But like, if it results in a billion dollars of value, if it results in $20 million of value, it's, it's a, it's an effort well spent.
[00:40:10] So that's the one I think that that is gonna be the most money is gonna flow and there's gonna be a lot of immediate opportunity. I also think it's probably the one that. Time's out the earliest. Right. That a lot of those jobs are, are we all, you, you used to, you, the same way that consulting companies maybe helped you with your website in the nineties, right?
[00:40:30] Like, it's just that it, it just becomes baked in at some point as the technology gets wider and wider adopted. I think that that I would think that the others might end up being longer term and more profound. And I think that taste is the, is the mental shift. I feel like I would love to see more individuals and, and, and even, companies as they think about their workforce make that like, okay, well the human taste is incredibly valuable and the human ingenuity is incredibly valuable and these are tools to that.
[00:41:02] And so how can we be really empowering that across the organization? And so, one of the complaints is that younger workers, that the bottom rungs of the corporate chain are the first to go away as we use younger workers to do the more rote tasks that AI can more easily do. Simply like, writing up the meeting minutes or, or whatever it is, and sort of like, well, your younger workers have.
[00:41:25] Really unique perspectives and they have really unique tastes. And now they have these tools that can fill in a lot of the gaps in their experience and knowledge. So how do you get access to their taste and their experience and take advantage of their young eyes on the world to help your company in a more profound way?
[00:41:43] Then having them write meeting notes. And, and I think for that reason, that's why the taste is a sort of one that like people, individuals get most excited about.
[00:41:55] Mike Allton: I was nodding my head the entire time that you were talking. This is fantastic. Particularly when you brought up Ethan Mollick. I could not agree more.
[00:42:01] I'm a huge fan of Ann Handley who's a brilliant writer in the marketing industry, and she's made the exact same point numerous times. Don't use AI to create that first draft. Use that time to really think through. What it is that you want to say, which is why I enjoy so much talking to journalists and, and authors on this show, on every podcast that I've ever hosted.
[00:42:21] 'cause they're always the ones who come with the best baked ideas. They're the most articulate. So this has been an absolute pleasure talking to you, Rob. Thank you so much For folks who wanna reach out. Maybe they got more questions for you. Where should they go?
[00:42:37] Robert Capps: They can find me on LinkedIn at Rob Capps shoot me a message and let's chat.
[00:42:43] Mike Allton: Fantastic. Well, thank you so much, Rob. Thanks all of you for listening. That is all the time we've got for today. Of course, we'll have all of Rob's links and the link to that article in the show notes below. But if this is your first foray. Into the world of AI and business. I've got the perfect resource for you in the show notes below the AI prior primer designed to quickly get you up to speed on all the terms, the tactics, and the underlying technology that's powering this AI revolution.
[00:43:06] Check it out and I'll see you in our next episode. Welcome to the Grid.
[00:43:10] That's a wrap on another episode of The AI Hat Podcast. I hope you've gained some valuable insights and actionable strategies to boost your business with ai. If you enjoyed this show, please subscribe, leave a review, and share it with your network. And don't forget to visit the ai hat.com for more resources and to connect with me.
[00:43:29] Until next time, keep innovating and remember, the future of business is human and it's powered by AI.
