Ever feel like you're barely scratching the surface with AI in your business? Sure, you've got ChatGPT churning out blog posts, but what if I told you that's like using your smartphone just to make calls? What if you're missing out on 90% of AI's true potential to transform your business and marketing operations?
Here's the thing - while everyone's focused on content creation, the real AI revolution is happening behind the scenes. Business teams are drowning in data, struggling with campaign coordination, and racing against impossible deadlines. And the solution isn't just working harder - it's working smarter with AI.
That's why I'm thrilled to welcome Peter Benei to the show today. As the driving force behind Intercept Scale and a veteran CMO/COO who's been leading remote business and marketing teams since 2014, Peter has been at the forefront of operations optimization. He's helped countless B2B tech companies scale their business operations using AI, and his recent study on AI applications in marketing has unveiled game-changing insights that most marketers are completely missing. Based in beautiful Tuscany, Italy, Peter brings a unique global perspective on how AI is reshaping the future of business operations and team productivity.
AI in Marketing: Unpacked host Mike Allton asked Peter Benei about:
✨Beyond The Content Bubble - AI's true power lies in operational optimization, not just content creation.
✨Data-Driven Transformation - AI enables real-time decision making and predictive analytics for better marketing outcomes.
✨Operational Excellence - Implementation of AI across marketing operations leads to faster scaling and better resource utilization.
Learn more about Peter Benei
- Connect with Peter Benei on LinkedIn
Resources & Brands mentioned in this episode
- Intercept Scale
- EXERCISE: “What does ChatGPT Know About Me?”
- Intercept Study: “CMO’s Perspectives on AI-Powered Marketing”
- The AI Librarian: How RAG Can Revolutionize Your Business
- AI Marketing Primer: A Comprehensive Guide for Marketers
- Explore past episodes of the AI in Marketing: Unpacked podcast
Full Transcript
(lightly edited)
AI for Business Toolbox - Applications of AI You're Not Using (But Should Be) with Peter Benei
[00:00:00] Peter Benei: 85 percent of the, the CMOs are using some sort of AI within their team. Almost the same amount generally across all the applications felt that their outputs or the results from AI tools that they are using were inefficient or not concise or some mixed bag, something must happen there. And I feel that it's because they are not treating AI as it should be treated.
They are treated as a tool. They don't give context. They don't give some briefing and background to the tool. They don't set up the tool properly. For example, ChatGPT, everyone knows ChatGPT. Do you use ChatGPT as a customized ChatGPT? Do you customize it to your brand and, and marketing and your audience?
That you can create like almost like really easy to create, sorry, a custom built ChatGPT for you. And most of them say that, no, we didn't, we didn't do that. We just use the free or normal pro version tool. We don't have an AI policy, for example. Right. That's also a thing. We don't have any kind of like plan how we are using the tools.
So obviously there is some wild west there and storming, but that has to settle in time. Uh, you have to figure out how to use those tools, have a plan, policy, and the right mindset.
[00:01:28] 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.
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Greetings program. Welcome back to The AI Hat Podcast where I selfishly use this time to pick the brains of experts at keeping up with and integrating or layering artificial intelligence into social media, business , advertising, search, and other areas. Oh, and you get to learn to subscribe to be shown how to prepare yourself and your brand for this AI revolution and come out ahead.
Now, you ever feel like you're barely scratching the surface with AI in your marketing? Sure. You've got Chat GPT, churning out blog posts or emails. But what if I told you that's like using your smartphone just to make phone calls. What if you're missing out a 90 percent of AI is true potential to transform your marketing operations.
And here's the thing. Well, everyone's focused on content creation. The real marketing revolution is happening behind the scenes. Marketing teams are drowning in data, struggling with campaign coordination and racing against impossible deadlines. And the solution isn't just working harder. It's working smarter with AI.
And that's why I'm thrilled to welcome Peter Benei to the show today. That's the driving force behind Intercept Scale and a veteran CMO and COO. Who's been leading remote marketing teams since 2014. Peter's been at the forefront of marketing operations optimization. He's helped countless B2B tech companies scale their marketing operations using AI.
In his recent study on AI applications in marketing has unveiled game changing insights that most marketers are completely missing based in. Beautiful Tuscany, Italy. Peter brings a unique global perspective on how AI is reshaping the future of marketing operations and team productivity. Hey, Peter, welcome to the show.
[00:04:16] Peter Benei: Happy to be here. I have to say that this was an amazing intro. Thank you for that.
[00:04:22] Mike Allton: My pleasure. You have the honor. Seriously earned it, but before we dive into some of those applications, I'd love to know, and just literally pick your brain, what do you think the biggest misconception that you're seeing about AI and marketing is right now?
[00:04:37] Peter Benei: I think you said it in the intro as well. It's using only for content and only for content creation because there is so much more to that. I understand by the way, why marketers use it for content creation as their first step. Not just marketers, by the way, anyone who is using chat GPT or any other AI tool.
It's obvious it's immediately delivers you a tangible result. You have the text or video or whatever that you are using for immediately shortens most of the cycles that you already have on content, but there are so much more. You mentioned data. That's one point I would mention data in a more refined manner in, in a sense, for example, sales data, sales or lead generation data, because, companies usually have two problems.
They either have too few leads or they have too many and they don't know what to do with them. So they either need some help sourcing new ones or filter out and target those who are really valuable for the time. Now, previously before AI, this kind of data segmentation was all manual. Now with AI, it can be, I wouldn't say automated, but at least, enhanced a little bit.
And the other last misconception, I think which you haven't touched on, I think on the intro was that treating AI as a tool, that's like a mindset shift, I think that everyone should be more familiar with at least what now as well, but within one or two years, definitely. Because you cannot just use it for one or two solutions as one or two tools.
You have to use it everywhere within your business, because if you combine those elements into together, you use it for operations, you use it for content creation, use it for data, enrichment, data generation, analytics, decision making, we will touch a lot of that. During this show, if you combine those, then you have a compound effect with the tool while with the AI, sorry.
And that's how you get a lot of sense.
[00:06:36] Mike Allton: Yeah. Yeah. Cause I'm seeing that even just in normal conversation that I might be having, with ChatGPT or Claude, one day I'm talking about this aspect of my business. Tomorrow I'm talking about something else that I want to accomplish.
And of course it builds up that memory, that context, if I'm keeping it within the same chat and by combining those conversations, it's learning more and more about me. There was a, there was a great little I don't want to say it's a meme, but there was a post, an idea going around the internet just this past week, the suggestion that people should just go to Chat GPT and ask it based on all our previous conversations.
What do you know about me that I don't know? It was so insightful. Some of the people's responses. Certainly mine was very insightful and, and illuminating. And it just goes to show how much the AI is learning and being able to connect the dots for us. If to your point, we're using that in multiple ways and not just, let's just keep writing, let's just keep writing.
Email subject lines over and over and over again. Let's get out of that. And to your point, so many people are stuck in that AI content creation mode. So, from your experience, what, what kind of made you realize that there was just so much more potential for AI beyond content creation?
[00:07:52] Peter Benei: Oh my God, it might be controversial, but but the, the last meetings.
And more time on on things that matter. So we haven't touched my back. You, you touched my background a little bit, but I've worked for for mid scale companies a lot as a CMO for 10 years. And one of the, one of the, one of the biggest issues what challenges that I had is that how figuring out, for example, go to market, right.
Or we had, we already figured out go to market. We have a product, but that product has a new feature and that feature has to be. marketed in a way with a marketing strategy or sort. Now, what happened before AI? We had countless of meetings, gathered all the data before the meeting, if we were efficient, by the way, because usually that wasn't the case.
Again, startup and mid scale work, can be chaotic. And we spent so much time On strategizing, discussing, investigating. We, we paid external consultants. Lot of money to figure, help us figure out how we are standing with our brand, how can we improve here and there. And so now we AI now if you obviously configured your tools in the right way, conversed with the, with the, with the AI model a lot, again, your example, by the way those insights were amazing.
And only if that. That person conversed a lot and the AI had a lot of memory to get some insights from, right? Same with, same with business. So configure the tool properly and you can actually save a lot of meetings. Now, if we need to launch a new initiative, especially by the way, and within scale, within our, within our company, we don't really have a, like a strategic meeting.
Around it, or maybe just a short one. Because AI actually brings us a, almost like a fully engaged, fully customized, proper plan on what to do. Even with the new ideas, supporting all the decisions. It saves insane amount of time. Insane amount of slack insane about chatting and whatever kills your focus by the way at the end That's the main win so we can actually focus on stuff that actually matter.
[00:10:18] Mike Allton: Yeah. Yeah, that makes a lot of sense to me now I know You talked about some of the applications you just briefly covered them Moment ago. I'd love if you could step through them a little bit more and talk to us about the study that, that reveal these applications, tell me about what that was and how that worked and what you found and then get into some of those applications that marketers you think today are overlooking.
Yeah,
[00:10:41] Peter Benei: yeah, sure. So, so we had this study since you mentioned it we did it this year as the hundreds of CMOs and, and marketing leaders mainly because that's, I think it's important for the context mainly around, uh, 200 or more people headcount companies, so like mid scale and enterprise.
level marketer. So not just solopreneurs and startup founders or stuff, stuff. So we asked them how they use AI in 2024 within their teams. And we had some really interesting insights. Obviously, content creation is leading the way as AI application. Video, audio is getting, gaining traction, although it's still a little bit laggy and buggy.
We all know because the applications and the tools are still new a little bit. But that's fine. It will refine so that's fine within within one or two years but was more but but that was which was more interesting was the analytics and the decision making part and the conversational element that the that people are using these kind of tools.
So around 30, 40 percent of of all the, all the answers said that they are using for decision making support and and data analytics, a lot these tools. So when I'm saying you can actually save a lot of time and be more, a little bit more efficient, not just a little bit, a lot more efficient within your operations that's actually happening right now.
So people are actually using it, doing it, implementing the, I wouldn't say the right way because that's the second most important insight that we had from the, from the study that everyone is using AI a lot, but I feel that it's more like curiosity and testing things out because what we saw is that like 80, 85 percent of the CMOs are using some sort of AI within their teams, almost the same amount, generally across all the applications felt that their outputs or the results from AI tools that they are using were inefficient or not concise or, some mixed bag. Something has happened there. And I feel that it's because they are not treating AI as it should be treated. They are treated as a tool more like a image shall we say I know it might be controversial to say that they don't give context they don't give Some briefing and background to the tool.
They don't set up the tool properly So when I say for example, most of our I mean, we have lots of discovery calls with others and clients and But it was also in the study that do use For example, ChatGPT, everyone knows ChatGPT. Do you use ChatGPT as a customized ChatGPT? Do you customize it to your brand and, and marketing and your audience?
You can create like, it's almost like really easy to create, sorry a custom built ChatGPT for you. And most of them say, no, we didn't, we didn't do that. We just, Use the free or, normal pro version tool. We don't have an AI policy, for example, right? That's also a thing. We don't have any kind of like plan how we are using the tools.
We're just experimenting on those. Some of our colleagues using a free plan. Others are using the pro plan. I know that that that guy actually customized it, but I don't know So it's like it's really weird and and almost like chaotic which is again Fine because this is a whole new territory. It's just you know, one or two years old So obviously there is some wild west there and storming but that has to settle in time and you have to figure out how to use those tools Have a plan, policy and the right mindset.
[00:14:48] Mike Allton: So if I'm extrapolating from what you're saying for the Yeah, sorry, I said too much. No, no, you said, it was great. I just, I just want to make sure I'm clear about it so that everybody else listening is clear. The majority of CMOs that were surveyed said, yes, we're using AI, which is cool.
[00:15:02] Peter Benei: But they had a mixed bag.
[00:15:04] Mike Allton: But then a mixed bag and many of them are finding that they're not seeing the results that they would expect or hope for in the issue isn't AI. The issue is a lack of AI literacy on behalf of the brands. They don't know how to use it. They don't know how to do custom GPTs. They don't know the pre work that needs to go in.
They don't have an AI policy. They're not all on consistent plans. Some people are using Chat GPT free, some are pro, some might be using Claude or Perplexity. So there's no consistency across the board. So, right.
[00:15:35] Peter Benei: Yeah. And also not just that so yes, that like skill literacy, that's a thing. But you have to never forget that these tools that you are using right now as AI tools, they have a.
I wouldn't say like super steep learning curve, but they are a new tool and we all know how marketers work. We are flawed. We don't have too much time. We are either in meetings or watching huge charts with numbers and stuff or writing content or I don't know. So Everyone is super flooded. You don't have time to learn new tools like this.
You have to dedicate some time, right? To bootcamps, to courses, to whatever is your thing to learn that tool. So obviously, because you don't do that. That leads to inconsistent results with the tools that you're using but that's just one thing The other thing is that they don't have the strategy behind the whole thing they don't have the vision.
They don't have the policy. They haven't figured it out Why it is important for them usually what happens and that's like Sorry for overgeneralizing everything a little, but usually what happens is that they sign up for a tool, they try to test it. They use it for something. Someone becomes a little bit proficient on that and they use those results to improve their, usually the marketing content, but in, in order to have better results, you have to take a step back, find the use case first.
Okay. Right. Where is your current bottleneck with, without or without ai? It doesn't matter. Where are your pain points? Where are you struggling? What AI can help you There is to improve efficiency and get you point A to point B faster in most cases. Right? But first you need to find a use case. Now that you found, found the use case, you can have a plan or strategy or something around it.
And you implement the tool with the right mindset that yes, I will use that tool. Whatever tool is it is that it doesn't I wouldn't say it doesn't matter, the tool itself matters less than the strategy behind it. So you would know why you are using that tool. What is the outcome that you are seeking from that tool?
And you implement that tool with that right mindset. We are marketers. We add some performance metrics behind it before, after and you just see what happened after you did the implementation with the tool. So you do the audit first, then the strategy and all the rest later instead, immediately jumping in without any.
Any any discussion around strategy and audit, to use a tool because you obviously you will have mixed bag of results Because you don't know what you are doing and why you are doing it
[00:18:50] Mike Allton: That makes a lot of sense and I think that's a really winning strategy because if you tackle one specific use case to your point, and you are able to achieve some efficiency.
That means you've been able to save some time, which you can then reinvest into exploring other use cases and learning more about how you could use that one tool, or maybe go on to the next tool, depending on what we're talking about. And that's a common refrain in this show, we've talked about AI literacy quite a bit.
And in fact this is a good point for me to mention folks, if you're listening and you're feeling like you're new to AI, you don't know the difference between Chat GPT and Claude or large language models and those kinds of things. There's, there's a free AI marking primer. I'll link to it in the show notes below.
It's just a quick ebook that'll just quickly get you up to speed on what all of these things are. So then you can start to dive into some of these more interesting applications. But one thing I want to come back to Peter, cause you mentioned before, that one of the more interesting applications in your mind was how these CMOs and businesses were using AI for analytics and decision making processes and coming up with strategies.
What was that role actually that AI was playing in that? How were they using AI to come up with these kinds of processes?
[00:20:03] Peter Benei: So it's different for every company, obviously. Right. So, but there is a, I would say, I would say there is a certain flow that you need to follow or process you need to follow in order to make this work at all because just like, I need a go to market plan for this product.
Give me a plan, a technical plan on how to attack said market. With this and that that result that you will get will be obviously a mixed bag again So it will be generic. It will be non creative and so on and so on and so So again the flow is the same with all AI implementation set up the tool with, with the right criteria.
Brief it. We, for example, we do internally, we do have a separate custom models for content creation, separate custom models for a strategy, separate custom model for sales and, and so on and so on and so on, every model is briefed. On the company. Like generic stuff, which you probably already figured out anyway.
And every tool as, as really specific, not just how it digest the information that I plant in, but also how it, uh, creates and provides the output just an example for the content. For example, obviously in, in today's digital world environment or whatever. Generic. Crap that the the tool usually spits out, right?
Yeah, you have to filter that out. From the setup, of the tool that's easy and that now you won't have this generic sounding. Sorry bs it will be a much cleaner content same with strategy. So you actually need to provide some Information in advance, a briefing, a context, by the way, you would do the same for a strategic consultant that you hired for your go to market creation plan before AI for a lot of fee.
You do the same with AI. You treat it as your, I don't want to say teammate, but like as a, as a, as a colleague that you would brief accordingly to a task. Once the good news, once you briefed that AI model, you don't need to brief it again. You don't need to do it again. And that's where the time saving comes in because it can exponentially grow.
And again, with the proper setup, it learns later on from that. Original strategy set up that you created. And once you did that, that whatever input that you give to that tool, it probably will provide you a little bit of better result in terms of data, in terms of analytics, in terms of strategy decisions that you.
That you, that you want to uncover and here where, where the agents can come in, by the way, that's an extra because they can actually hunt information down and do work for you strategic work for you Always on and on demand and instantly they're not a hundred percent there yet, by the way. So yeah
[00:23:19] Mike Allton: Yeah, exactly what I was going to say.
We haven't talked about Ai agents a lot on this show because I tend to try to avoid Ai news and developments and that sort of thing. Because well for starters, it's not evergreen stuff News that I might break on this show by the time I release the podcast. It's literally old news But we also try to stay in, what, what, what can marketers actually do today?
But it's come up particularly when I ask folks, like, I'll probably ask you in a few minutes, where do you see things going? We'll talk a little bit about agents, but to your point, yeah, there's so much you can do to. In terms of pre work that will help the AI, whatever large language model you're using understand what you want to accomplish, who you are as a business, who you're talking to as an audience.
So much great effort can and should be put in there that marketers just You need to do it. So folks, we're talking with Peter Benei about some of the ways marketers can be using AI, but aren't. I've got several more questions that you're not gonna want to miss, but first a quick word from our sponsor. This episode of AI for Business Leaders: The AI Hat Podcast is brought to you by Magai. Tired of juggling multiple AI subscriptions and. Trying to figure out which tool to use, and when? Magai simplifies AI for businesses by offering access to all the leading language models and image and video generators for one low price. With Magai, you can create custom instructions to personalize AI for every business need and use them across all LLMs, including Chat GPT, Gemini, Claude, and even Deep Seek.
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And now, back to the rest of today's episode.
So Peter, with some of the businesses that you're working with, what are some of the implementation challenges that those kinds of marketing teams should prepare for?
[00:25:30] Peter Benei: Good question. I'm trying to rank it. I think the data is the first one.
So I think everyone should learn a little bit, even though you're not a developer or a marketer. I'm not, I'm not, I'm not a developer. You still need to learn a little bit about how these AI models technically work just like the basic bare bones, nothing fancy, nothing complex, but they obviously consume data and interpret it to you as some sort of like an output.
Now, because of this, the data is one of the challenges. Do you have enough information in the proper format in the right way that we can insert it and feed it to the AI? Most people think that AI anyway eats up everything, anything. Yes. And generally you can say yes, but for example, if you create Just one of the examples that we, that we do for others content sorry, a product chat bot.
So it's product bot, which you can talk to if you have a product based business. I'm sure every marketers can relate to that when there is a sales agent or SDR or BDR on a conference. They don't know the exact. Up to date, like what's in on that given day is fixed on the product, which is marketable and sellable to a prospect that they are in on the field are talking right now.
So they have like a meeting and a call and something to figure out, or they just hunting down documentation publicly on the Internet. That's not the case anymore. You just talk to the product bot because it actually has all the information That is relevant and updated about the product that you have and it not just tells you the product version of it but it Tells you in a sales and marketing way that you can actually use and grab and and and work with it so To make that work.
You need a proper documentation proper data You And, and and proper information. So that's one. So if you are considering AI adoption, have a clean data set or, document everything written form because it can be used later on. Second is, we touched on this, so I don't want to waste too much time on it, but skills, of course knowledge gap it's huge, it's huge.
I tend to think sometimes that, that we are like, I don't know for, sorry. I'm from, I'm from Europe. So football, like soccer in the U S like everyone, everyone knows it. Everyone understands it. And everyone has a opinion about it. Same with AI, right? You think that you have an opinion and you have a knowledge.
There, there is, no wonder why we have coaches on in football or soccer. They actually know it. You are just you know, watcher or viewer. So there's a huge difference between knowing the actual knowledge and the skill, learning it using that skill and knowledge, create and configure AI.
And work with it a totally different level. So obviously you need the training and and and every kind of learning material that you can grab. And the third one is the ethics, privacy, policy, everything around that. They usually don't have a policy and it means that they they know that they have tools they use some tools but they are not data compliant security compliant operation wise it's a madness or chaos sometimes again I mentioned it some of them using the free platform some of them using the pro platform within within one team So not just per company so that's, that's a big thing which you can ignore at a certain size.
So, like, if you're a startup or, 50 people or so, you can, I wouldn't say get by because you duct tape everything together anyway. Sorry. But after, after you grew up and and you have entered the scale up territory, get some funding, get some revenue, get some proper CFO actually looks so after your data and numbers and stuff.
You can't ignore the policy piece because it just make, it makes everything streamlined and, and clear, transparent and risk free. So that those are the three, I think.
[00:30:11] Mike Allton: That makes a lot of sense. I loved your first one about data. I just finished leading a team at Agorapulse where we implemented that for our sales and customer facing teams.
We built a system that interfaced with Slack. And we fed it our blog, our support materials, other sources of data. So now to your point, our sales team can go to that Slack channel and say, do we have any stories about a customer switching from X competitor to us, or, what's the product's capability?
How many, images can we share in a post or whatever that, that question might be. But to your point, we are discovering in that process issues with. Some of the documentation, some of the data that's out of date, right? Where there's an old blog post that says we don't support this, that, or the next thing, or a release note that's just no longer valid.
So you have to be mindful of the data that you put in and then you have to continue to monitor and make sure that there are no errors, there are no hallucinations or anything like that that can be involved. But I love these examples of both things to be mindful of and things to avoid. How do you see these kinds of AI applications affecting our marketing team structures, or maybe even the roles within marketing teams?
[00:31:24] Peter Benei: Are we losing our jobs?
Yeah, no, no, no, don't worry. Don't worry. Well, at least not yet. .
Worry. Okay. So, on a serious note I think we, we started with a misconception. Right. About AI. It's not an automation tool or not just an automation tool and it won't replace You as a team member, it will augment the team.
And that's like the short term when I say short term, like five to 10 years. Or maybe even shorter. I don't know about AI development now. Can anything can happen really? Yeah. So like, Short term, it will augment the teams. You will still have the same amount of people, you probably won't need desktop researchers and stuff later on for marketer, marketing teams, because agents and AI will do that for you immediately.
But you still have the same creatives. You still have the same copywriter, the basic structure of the marketing team will stay intact. But you, because you added AI as a teammate with, specific use cases, you are able to with a 10 percent person, 10 people, strong team, you are able to produce and create and manage marketing campaigns that are not.
Usually managed by just 10 people but managed by 100 people So the scale is exponential and it's all because of ai because you save time you scale with it and you use it for more and more and more manners so it will augment you on the long term though I'm, not sure and I don't want to go fully into futurology and stuff.
I do believe that human creativity Like our input as creative human beings will be still required. Because it's not just rationale. It's not just the output. It's, it's also intuition. It's also emotion that we are dealing with, especially marketing. And AI cannot emulate that. So we still need it, but.
I'm pretty sure that less people will be needed to do the same amount of work on the long term. So like 10 plus years. Because the AI will evolve into a space that will probably impact hardly not just marketers, everyone, but on short term, it's fine. So it will exponentially scale everything five to 10 years, maybe.
[00:34:07] Mike Allton: It's, it's a really interesting thought exercise, I think, to try to envision what a future with AI is going to look like in five to 10 years. Cause first of all, pretty much everything that we imagine is going to be wrong. It'll be, it'll be different and unprecedented. I I'd harken it back to, if you were an advertising agency in the 1970s.
The idea of managing digital advertising was not even an inkling in your mind back then. And yet, just fast forward a couple of decades. Now you've got agencies that have completely transitioned how they're doing business and the kind of business they're doing. And even the kind of clients that they're working with.
The company that I work full time for is a social media management tool that could not have existed. Two decades ago, just there was no need for it. And so that means that with artificial intelligence, there will be new roles and new applications that we couldn't even conceive of in the next five to 10 years.
But the other really interesting thing that's hard for most Because it's not part of their normal day to day thing is the fact that it's a society we are changing and evolving and as a society we are aging and our populations are decreasing. So people are concerned today about the sheer number of jobs that are available today.
Probably don't need to be quite so concerned because in five to 10 years, we'll have less people, less need for jobs, which means that if there is more freedom to be more creative, to work less and still have the same lifestyle or a better lifestyle than we have today, that's an amazing thing. We don't need to be quite so worried about that.
Yes. I think, and that's based on what I'm, one other thing.
[00:35:43] Peter Benei: Yeah. One other thing that I would add to here, sorry to interrupt you. Is that Yeah, please. Yeah. You're right. I think less people will, like, need a job, I think that's like over generalization, but say that, but also I don't think that we will have new kind of jobs.
And I don't think that the social media manager is so utterly different from a 60s copywriter. I would say we are doing the very same things over and over from hundreds of years, but with different transformations, different angles, how technology is able to Impact our lives. So we need to change and adapt Um, I don't think That we can change that fast.
By the way, that's also one thing and we should change that fast We need to try to find a way and that's like the optimistic way. I I view the thing this whole how marketing teams will be impacted by AI. You need to find a way where you can still create You value with AI on the long term, how can you transcribe your creative output and feed it to AI so you together, you and the bots can create something exponential or scalable.
And when I say, for example, 10 people will manage campaigns that are Previously before AI, we're only able to manage by a hundred people. That's true for one person as well. So your personal one person output will be insane. Before AI, I, I was like a hype consider myself a high performer, but now I'm like, almost like on steroids.
Seriously, it's insane how much, how much I, I am able to achieve and produce as output or results or whatever. We didn't just like, like days. Like, or just like hours sometimes it's, it's hilarious. Seriously, just like one example, like we're also creating a course, for example. It's not public yet.
And so I'm publicly committing to creating and make it live here now. Yeah. Before like AI. It would have took us like, I don't know, a month or two to create a course like this. Write the materials, consume everything that you have, read ebooks and books and whatever, watch other courses and stuff.
No, now it's, I wouldn't say like days, but It's insanely short compared to, to what I did before pre AI. So I wouldn't worry too much how it will impact in a negative way. I would worry about that only on the very long term as a marketer, 20 plus years. But the world will be totally different in 20 plus years anyway, as you just highlighted.
So I'm not sure that anyone should need to do any kind of predictions, especially nowadays. We can't even predict what happens like next month. So it's really hard. Short term, it's full on scale and you can achieve so much more with AI and super optimistic. The picture is super optimistic and bright
[00:39:10] Mike Allton: Could not agree more.
What a terrific way to end this conversation. Peter, you've been so insightful. I hope people have been inspired. For folks who want to reach out to you. Maybe they want to learn more about you and the kind of work that you're doing and how you can work with them. Where should they go?
[00:39:28] Peter Benei: Yeah, so I'm pretty easy to find on LinkedIn.
I think I'm the only one with this name or not many others. Peter B E N E I. Hit me up there. My DMs are open. I'm also very active, like posting daily and stuff. Or visit our site interceptscale. com.
[00:39:49] Mike Allton: Fantastic. We'll have all of Peter's links and everything we talked about in the show notes below as usual, but that is all the time we've got for today, friends.
And like I mentioned before, if this is your first foray into the world of AI marketing, I do have that perfect resource below for you in the show notes that AI marketing Primer designed to quickly get you to speed on all those terms and tactics and the things that we're talking about in this show and all the others.
Check it out and I'll see you in our next episode. Welcome to the grid.
That's a wrap on another episode of the AI hat podcast. I hope you gained some valuable insights and actionable strategies to boost your business with AI. If you enjoyed the show, please subscribe, leave a review and share it with your network. And don't forget to visit theaihat. com for more resources and to connect with me.
Until next time, keep innovating and remember the future of business is human and it's powered by AI.
