
AI Made Content Free. Here’s What It Made Priceless (Digital Reset Episode 492)
The cost of producing a 1,500-word article has collapsed to somewhere near zero. That’s the supply shock, one my friend Mark Schaefer has talked about for years. The more interesting question today — the one most marketing leaders haven’t priced correctly yet — is what that collapse does to everything else.
When a factor of production goes free and infinite, value doesn’t disappear. It shifts. And in marketing today, it’s shifted somewhere most content strategies aren’t looking.
Academic evidence has seen this coming. A National Bureau of Economic Research paper using Pixiv data shows that generative AI is crowding out human creators. Ahrefs data shows that 86.5% of top-ranking pages now contain some amount of AI-generated content. And Graphite.io found that the total quantity of AI-generated articles probably surpassed the quantity of human-written articles published on the web within the last couple of of years.
Additionally, research published in Nature on "model collapse" — the degraded outputs that occur when AI trains on AI output — singal a related, and more problematic reality for marketers: a "collapse to uniformity.” That’s the steady, unrelenting increase in “textual similarity” across the web since AI started publishing in the 2010s. Those similar, AI-generated outputs have accelerated ever since ChatGPT’s earliest models, and are projected to reach 90% saturation around 2035.
If that forecast holds, we’re adding roughly 10 points of uniformity — bland, boring, blah content — every year. And that means the window for you to differentiate is not some theory. It’s real. And it’s closing on you right now.
The result is two things happening simultaneously:
- AI-generated content is increasingly good enough that it saturates every channel.
- And human beings — who are, as I say, "pretty good bullshit detectors" — are beginning to flag content they don’t like as "AI slop.”
That second reality isn’t happening just when content was generated by a machine. It’s also happening when it doesn’t sound human enough, when it’s too corporate, too polished… too fake.
It’s fairly likely that at least 25% to 30% of your customers will actively demand authenticity within the next two to three years… if they aren’t demeaning it already. My two-to-three year forecast isn’t pulled out of thin air — it’s the sheer math of 10 points of AI detection per year building off a base of roughly 10% today.
This episode of Digital Reset with Tim Peter identifies the three specific assets AI cannot reproduce:
- Proprietary data
- Original examples
- Your expert voice
We also share a three-question framework for auditing whether your content strategy is actually building any of them.
The closing argument is my own practice of writing our podcast scripts by hand, despite having AI tools running in the background: not because I can write faster than a machine. We all know that’s not true.
Instead, it’s my experience, my beliefs, my humanity are the scarcest resource our content can put to work. That the distinction that matters — separating what is abundant from what is actually scarce. It’s the core claim I’m making this time. And it’s the one that will determine which brands still get seen in three years time… and which will have blended into the background.
Key Insights for Marketing and Business Leaders Navigating AI Content in 2026
In this episode, we break down:
- AI didn’t kill content marketing — it repriced it. The cheap parts (generic explainers, commodity how-tos, undifferentiated articles) are now worth close to nothing, because anyone using AI can produce them in seconds. The expensive parts — your proprietary data, lived experiences, and genuine expert voice — have become more valuable, not less. Using AI won’t make you fail. But spending your content budget on the wrong side of that line will.
- "AI slop" is the uncanny valley of content — and your customers’ bullshit detectors are already activating. People flag content as AI-generated not just when it actually is, but when it fails to sound human enough. As customers get increasingly sensitive to “AI slop” — probably by 10 points or so per year — the brands relying too heavily on overly templated, indistinct, and impersonal content will find themselves on the wrong side of a widening credibility gap. Somewhere between 25 to 30% of customers will demand clear authenticity in the next two to three years… if they’re not already.
- "Collapse to uniformity" is the structural threat underneath "AI slop." The Nature paper on model collapse gets most of the attention, but the follow-on research on “textual similarity” is the more immediately relevant fact. Content on the web keeps getting steadily more similar, and has only gotten worse ChatGPT emerged on the scene.. Researchers project 90% saturation by 2035 — roughly nine years away. That means the differentiation window is not just some theoretical abstract. It is measurable, and it is closing.
- The three assets AI cannot fake are proprietary data, original examples, and expert voice. Data that only you have about your customers, your market, and your industry is yours alone to report. Original examples from real customers carry the credibility of lived experience that no AI can generate. And an expert voice means being willing to make a specific, named predictions and opinions — ones you’re willing to be wrong about — because taking that risk is exactly what makes you worth listening to. Generic best practices and how-to content is dead. Your truth, your actual opinions, that you’re willing to own, is rare.
- Three questions will tell you where your content strategy actually stands. What is your ratio of proprietary to commodity content in the last 90 days? When a prospect asks ChatGPT, Gemini, Claude, or Perplexity about your category, what specifically about your brand shows up — and is it something only you could have said? Who on your team is your named voice, and are you amplifying their signal or burying it it in generic content calendar outputs? The answers to those three questions are the most useful content audit you can conduct.
- The answer is not to publish less — it’s to publish more of what’s scarce. This episode is not about cutting volume. It’s about redirecting where you put your efforts. Publishing more of the content only you can produce — and less of the content that any AI could produce — is the allocation of time and resources that matters most. The brands that figure this out in the next two to three years are the ones customers will ask for by name. The ones that don’t will blend into the background.
Whether you’re a CMO deciding where to concentrate your content budget in 2026, a marketing leader who keeps being asked about AI, or a brand that’s already noticed its content working less well than it did a year ago, this episode gives you the framework to understand why… and what you can do about it.
AI Made Content Free. Here’s What It Made Priceless. (Digital Reset Episode 492) — Headlines and Show Notes
Show Notes and Links
- The Single Biggest Myth in Digital: Content is Expensive (Thinks Out Loud Episode 275)
- Does Generative AI Crowd Out Human Creators? Evidence from Pixiv by Sueyoul Kim, Ginger Zhe Jin, Eungik Lee :: SSRN and Does Generative AI Crowd Out Human Creators? Evidence from Pixiv | NBER
- w34733.pdf
- 74% of New Webpages Include AI Content (Study of 900k Pages)
- More Articles Are Now Created by AI Than Humans
- AI models collapse when trained on recursively generated data | Nature
- [2404.01413] Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data and 2404.01413
- Future of AI Models: A Computational perspective on Model collapse
- Three reasons why brand is more important in the AI Era – Schaefer Marketing Solutions: We Help Businesses {grow}
- Mark Schaefer and The Most Human Company Wins – Schaefer Marketing Solutions: We Help Businesses {grow}
- The most human company wins: A case study – Schaefer Marketing Solutions: We Help Businesses {grow}
- Win No Matter What: The Hub and Spoke Strategy (Digital Reset Foundations 491)
- The Foundation: From Card Catalogs to Concierges — Your SEO + GEO Blueprint (Digital Reset Podcast) – Tim Peter & Associates
- The Long Game: What 15 Years of Digital Marketing Teaches Us About AI (Digital Reset Episode 489)
- Why AI Gives Your Customer Different Answers… Every Time
- The AI Value Gap: Why 82% of Companies are Failing to Gain from AI (Digital Reset Episode 486) – Tim Peter & Associates
- Why AI Won’t Kill Search—It’s Doing Something Much Bigger (Episode 483)
- The House Always Wins: Lessons from Google’s 2025 Earnings (Podcast Episode 484)
- What Brand Tattoos Tell Us in the Age of AI (Podcast 482)
- AI Is Changing How Customers Choose — Here’s How Brands Win in 2026 (Best of the Show: Revisiting Episode 478)
- What Taylor Swift Can Teach You About Bypassing Gatekeepers (Thinks Out Loud Episode 393)
Buy the Book — Digital Reset: Driving Marketing and Customer Acquisition Beyond Big Tech
Tim Peter has written a new book called Digital Reset: Driving Marketing Beyond Big Tech. You can learn more about it here on the site. Or buy your copy on Amazon.com today.
Past Appearances
Rutgers Business School MSDM Speaker Series: a Conversation with Tim Peter, Author of "Digital Reset"
Free Downloads
We have some free downloads for you to help you navigate the current situation, which you can find right here:
- A Modern Content Marketing Checklist. Want to ensure that each piece of content works for your business? Download our latest checklist to help put your content marketing to work for you.
- Digital & E-commerce Maturity Matrix. As a bonus, here’s a PDF that can help you assess your company’s digital maturity. You can use this to better understand where your company excels and where its opportunities lie. And, of course, we’re here to help if you need it. The Digital & E-commerce Maturity Matrix rates your company’s effectiveness — Ad Hoc, Aware, Striving, Driving — in 6 key areas in digital today, including:
- Customer Focus
- Strategy
- Technology
- Operations
- Culture
- Data
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Transcript: AI Made Content Free. Here’s What It Made Priceless.
Welcome back to the show.
A few years ago, I made the claim that content wasn’t expensive. Instead, I said that content that doesn’t convert was expensive.
Today, that’s not really true either. Not because you want content that doesn’t convert. I mean, really.
But AI has essentially driven the cost of producing content to zero. You need a 1,500-word article or a 15-second video? A quick prompt, and you’ll have what you need within minutes, if not seconds.
Sure, there’s some nominal cost to you for the AI platform you’re using. And crafting a solid prompt might take you a few minutes, assuming you don’t already have an effective process or a library of prompts to work from. Both of those are still orders of magnitude cheaper than what content creation used to cost.
Hell, according to Ahrefs, 74-plus percent of all newly created web pages contained AI-generated content.
I mean, I know I use AI all the time as part of my workflow, and I’m pretty sure if you’re watching or listening to this episode, you do too. That’s part of the point.
When everyone has access to the same tools, when the tools become part of our ambient reality, the outputs of those tools become ambient reality too. We are all contributing to the flood every day, all by ourselves.
Now, before we get started, I want to be clear. Today’s episode is not anti-AI. I use AI. Clearly I’m in favor of it. Instead, it’s about the costs of marketing and where we want to and need to invest our budget and time.
For example, I had Gemini and Claude and ChatGPT doing work in the background while I was writing this script. And they took less time to complete their tasks than even writing this introduction did.
So why did I bother writing the intro at all? Why not just let AI do it?
And that gets to the core of what we need to talk about today. Because the volume of effectively free content that’s flooding the internet has driven up costs somewhere else. As content has become free and abundant, something else — something more critical — has become expensive and scarce.
And that something else, when done well, is what will differentiate your brand and it will help you stand apart in the marketplace.
That something else is what AI can’t reproduce. It can’t generate. It can’t hallucinate. It can’t fake.
Your lived experiences, your real-world relationships, your personal touches with your customers, and a genuine voice all your own are what actually are worth cultivating. When content becomes a commodity, your human connection to your customers becomes the most scarce asset of all.
Building that asset, growing it, and nurturing it is what is going to set you apart in a flood of free, fake content. In fact, I’m going to argue in this episode that you’ve got no more than two to three years to get this right. And getting it right is what will make your brand one customers will ask for by name today and in the future.
This is episode 492 of Digital Reset. I’m Tim Peter. Let’s dive in.
It’s abundantly clear that AI-generated content is here and that it’s absolutely flooding digital spaces every single day. You do not need me to tell you that. You see it every single day.
If you’re interested in some of the economic underpinnings though, there’s a National Bureau of Economic Research paper from Kim, Jin, and Lee, published earlier this year, that used Pixiv data and shows that generative AI crowded out human creators. I’ll link to it in the show notes.
Similarly, research last year from Ahrefs said that "86.5% of top-ranking pages contained some amount of AI-generated content." That’s a quote. While I have a few quibbles with their methodology, I’m relatively convinced that a fairly healthy chunk of content on the web involves AI in its production somewhere along the way, just as their research found. And again, I’ll link to their research in the show notes.
Finally, some research from Graphite.io claims that, and this is a quote, "The quantity of AI-generated articles has surpassed the quantity of human-written articles being published on the web." They claim, contra Ahrefs’ findings, that these articles "largely do not appear in Google and ChatGPT." They also ignore "AI-generated/human-edited articles," while noting that "they may be even more prevalent." Ya think?
And yes, I’ll link to their research in the show notes too.
The point is that AI-generated content is everywhere online. It’s a core part of how content comes into being today. Most of that content is, at minimum, pretty okay, and some of it is actually quite good. I’m willing to bet that you are seeing that same reality.
At the same time, AI-generated materials are so common now that we’re starting to see a bit of a backlash lately, with lots of folks talking about "AI slop" showing up in search and on their social media timelines.
That slop critique hints at the problem. It kind of gets at the core of the problem. It’s a flashing red light that says, "we need to start doing something different." And I’m going to come back to that in just a minute.
Before I do though, there’s one other signal that I have to address that shows why we need to think beyond AI content. It’s called model collapse, and it points to a likely reality your "free" content faces longer term. In fact, it’s something you might even be dealing with today.
The basic principle behind model collapse came from a paper published in Nature by Shumailov and his team — all the way back, way, way back in July of 2024 — so less than two years ago. It found that, and this is a quote, "indiscriminate use of model-generated content in training causes irreversible defects in the resulting models."
In simple English, what their research showed was that training artificial intelligence on AI-generated content generally leads to increasingly bad outputs over time, much the same way that making a photocopy of a photocopy of a photocopy will get blurrier and blurrier until eventually the output is unusable. Shumailov’s team rightly worries that as large language models get trained on the increasing amounts of AI-generated content on the web, those LLMs will produce worse results over time. That concern seems 100% valid if we agree about the photocopy example, right?
It’s also apparently not likely to happen in practice. Because follow-up research from Gerstgrasser, Schaeffer, Day, and Rafailov shows that as long as there’s at least some original human data in the model — you know, like all the web content produced before ChatGPT emerged — we’re probably fine.
But — and this is a key point — there is a related term we do need to think about. It’s called "collapse to uniformity." A group of researchers, while testing the idea of model collapse, discovered that, and again, this is a quote, "textual similarity has been steadily increasing since 2013, with a significant acceleration from 2018 to 2022, coinciding with the public release of…" ChatGPT’s earliest models. So that would be ChatGPT 2.0 and ChatGPT 3.0.
They go on to say that "the ecosystem may reach 90% saturation around 2035," and then just get worse from there.
While 2035 may sound like a long way off, that’s less than nine years from now. If you are younger than say 50, that will occur in your career. Also, if we’re going to hit 90% in less than nine years time, it suggests that we’re hitting some percentage of it today. And I suspect that we’re going to see an increase of roughly 10 points every year from now until then. I mean, if you think about it, that’s just logical. If we’re going to be at 90% roughly nine years from now, we’ll be at 80% eight years from now, and 70% seven years from now, and 50% five years from now, and 30% three years from now.
Which is where the AI slop criticism becomes so critical.
Human beings generally are pretty good — and I’m gonna use a technical term here — they’re pretty good bullshit detectors. Sure, not everyone’s good at it to an equal degree. And sure, we all have our blind spots where we can get fooled. I know I do. But human beings are generally pretty good at sniffing out when something sounds fake.
If you’ve ever heard of "the uncanny valley" in video games or CGI, it’s where a human face looks very close to real, but not close enough, and people find it disturbing. Our brains just won’t let us accept it as real. Think about a movie like The Polar Express. It just weirded people out because it was in that uncanny valley — close to real, but not quite close enough.
AI slop, to me, is the uncanny valley of AI-generated content. AI-generated content sometimes doesn’t sound human enough and sets off your customers’ bullshit detectors, and they flag it as AI slop. They’re the first 10% this year noting that something seems off in what companies and creators they’re listening to are saying.
The funny thing about this is that sometimes people online accuse creators of AI slop even when a human being actually created the content. And it’s not because it was AI-generated. It was because it didn’t sound human, or at least human enough. It was too corporate. It was too polished. It was too fake.
I’d argue as more people get wary about the text patterns and speech patterns of AI, they’re going to also get more wary of corporations and creators relying on heavily polished statements. Marketing thought leaders — including people like me — have claimed for years that it’s important to be authentic when you speak to your customers.
If we’re picking up 10 points of AI detection every year, it’s likely that a healthy chunk of customers — 25 to 30% — will demand that you be real, that you be clearly real, in the next couple of years, if they’re not already demanding it of you today. That’s where I got that two-to-three year number in the intro.
By the way, as a quick aside, I cannot talk about this topic any further without referencing my very good friend, Mark Schaefer. Mark has written extensively on this topic and has influenced my thinking significantly. His mantra about how the most human company wins in the age of AI echoes in my brain almost every single day. I cite him in my book. He’s just a key, key speaker on this topic that you want to know about. I’m going to link to some of his thoughts in the show notes, and I would encourage you to check those out and follow him regularly.
At any rate, that’s why focusing on human connection to your customer isn’t just scarce. It’s the most precious asset you can build. Your voice — the true you — is the most precious asset you can build.
That’s why your content can no longer just be a generic explainer or a how-to video. They’re dead. They don’t work anymore. They don’t matter.
Instead, you have true, scarce, valuable assets that your content must put to work today. What are they? Well, they include several things.
The first is proprietary data. Data that you have, that you can see, and that no one else can about your customers, your market, your industry, and the world at large is something that no one else can talk about with the genuine expertise and insight that you bring to the table. It’s your story to tell, and you need to tell it if you’re going to stand apart from generic AI-generated drivel.
The second are original examples. Talk about what you’ve lived in real life — your customers, your projects, your outcomes, your experiences. There’s a reason I talk about my hotel clients and other businesses I’ve worked with on this podcast, and that’s because no one else has those specific experiences. They back up my thinking and research with real-world examples that no one else can claim. It works for my business. It’ll work for yours too.
The third, of course, is expert voice. Your expert voice. Did you notice my two-to-three year timeline that I mentioned earlier? That’s my opinion. I don’t have anything other than my expertise, my experience, and my assessment of the data that exists to back that up. I could be wrong. I could absolutely be wrong. Maybe it’s four years. Maybe it’s one and a half years. I don’t know, but I’m willing to put my name on it and make a prediction to stand out from the crowd. I’m willing to take the risk of being wrong because I believe it will help you now and it will help you in the future. And candidly, because it will help others know who I am too. If I’m right, everybody wins. If I’m wrong, I will either learn and improve — or no one should listen to me anyway. Right? Period.
Together, those three attributes help me build a connection with my clients and listeners to the podcast and audiences on social media. They all work together to build the Digital Reset brand and to foster a community of like-minded individuals who are committed to learning and growing together. That same approach can work for you too.
Here’s how I would do it.
Start by asking yourself three questions this week.
First, what is our ratio of proprietary to commodity content over the last 90 days? Are we building named assets all our own, or just generic outputs that any AI could produce?
Two, when a potential customer asks ChatGPT, Gemini, Claude, or Perplexity about our category, what specifically about us shows up? Is it a reference that could have been written only by us? Or could it have been written by anyone? One of those is better for your brand long-term than the other, as you might expect.
Three, who on our team is our named voice? Are we amplifying their signal? Are we boosting their signal? Or do they get buried in the content calendar of just generic stuff we put out there? Think about which of those has a future too.
One big takeaway these questions should point you to is to focus on what makes you… you. What makes your brand stand apart? What makes you distinct? What makes you different from anyone else in the space — and different enough that people will listen to you, and different enough that eventually people will give you money? Not for your content, but for the solutions and products and services that you offer. That’s where you want to live. That’s where you need to live — because in two to three years, if you don’t already live there, you are in big, big trouble.
Also, I don’t want you to listen to this episode and necessarily think, "we need to publish less content." I mean, sure, this is about quality over quantity. Absolutely true. But it’s about publishing more of what’s scarce and less about publishing what’s already abundant.
That’s why I wrote the introduction to this episode — and the whole episode, for that matter. Not because I can write faster or cheaper than artificial intelligence. I can’t.
But because only I can produce the most scarce resource of all: me. For better or worse, when you’re hearing these episodes — when you’re watching them on YouTube or listening to them on Spotify — you’re hearing my experiences, you’re hearing my data, you’re hearing my voice. And that will be true today, two to three years from now, and for as long as you’re willing to keep listening.
AI did not kill content marketing. AI will not kill content marketing. What it’s done is make the cheap parts worthless and the expensive parts crucial. Your job is to know which is which. Your job is to put your focus on the parts that are crucial. And it’s to do that now and in the longer term too. And if you get that right, you don’t have to worry about the next two to three years or the next nine. You’ll be in great shape no matter what happens.
If this episode gave you a clearer picture of how you should approach content marketing in the age of AI, do me a favor. Send it to a colleague who’s thinking about that problem for your business. You might just save them from going down the wrong path.
You can find the show notes from this episode as well as the full archive of all past episodes by going to timpeter.com/podcasts.
And if you’re ready to go deeper on making your brand the answer that AI reaches for, my book, Digital Reset: Driving Marketing and Customer Acquisition Beyond Big Tech, is the roadmap you need. You’ll find the link for that in the show notes too.
Thank you so much for listening today. I genuinely appreciate you. Until next time, please be well. Be safe. And be excellent to each other. I’ll see you soon.
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