What to Do as Discoverability Destabilizes
The hidden pattern behind the creator economy’s discovery crisis—and what creators should build next
Something strange is happening across the creator economy—and if you’ve been in this space for more than a couple of years, you can feel it even if you can’t quite name it:
Reach is declining
Traffic is unpredictable
Advertising costs are climbing
The systems that used to reliably connect creators with audiences feel...Unstable.
I’ve been building online since the mid-2000s. I’ve watched multiple waves of “everything just changed” sweep through this industry—and usually, it’s a platform update, a market correction, something that settles back to normal if you figure out the new rules fast enough.
So when creators in my circles started saying several years ago that the playbook that defined the 2010-20s wasn’t working anymore, part of me wanted to file it under, “algorithm shifts, adjust and move on.” And honestly, I did just that for a long time, especially because over in the publishing world, I taught direct sales around crowdfunding, website stores, and subscriptions and memberships. My direct sales bubble was thriving, and I thought it was primarily exclusivity to Amazon’s KDP Select program that was causing authors many of their problems.
And that was part of the story, but not the full story. I’ve spent the last several months—if not years—trying to understand what is really happening and why it’s happening now.
What I’ve landed on is a pattern—one that’s been repeating long before the internet existed. Once I saw it, everything I’d been experiencing stopped looking chaotic and started looking almost boringly predictable.
This essay is about the structural pattern underneath the chaos—and why it matters for every creator trying to build something sustainable right now.
We All Agree…Something Is Breaking
Let’s start with what creators are actually experiencing, because the specifics matter.
Organic reach on social platforms has been declining for years—not gradually, but in large lurches:
A video hits millions one week and 6 months later, identical content dies at two hundred views
Facebook organic reach for pages dropped from roughly 16% in 2012 to under 2% by the early 2020s
Amazon’s algorithms swing in ways that destabilize book sales that had been steady for years
Newsletter deliverability erodes quietly as inboxes get more aggressive about filtering
Customer acquisition costs across digital advertising have roughly doubled since 2019
In my publishing bubble, I’ve talked to authors—smart, strategic authors with strong backlists—who watched their book royalties drop 30-40% in a single quarter with no clear explanation. But it’s not just Amazon that’s experiencing challenges…It’s every social, retail, and advertising platform too.
As algorithms throttle human-made content, some estimates suggest AI-generated content online has increased by over 1,000% since 2023.
Creators experience all of this as enshittification—a term coined by Cory Doctorow that perfectly captures what it feels like when a platform that once served you starts serving itself at your expense—and despite all your efforts to build the platform in the first place. Declining reach, inconsistent performance, higher acquisition costs, the constant sense that the rules changed overnight with no notice and keep getting further and further from helping you.
Despite the obvious enshittification of the system, most creators do not rage against the machine. Instead, they interpret these symptoms as a personal failure or a puzzle to solve. “I need to post more.” “I need better content.” “I need to figure out the new algorithm’s rules.”
I get the impulse. I’ve had that impulse. For me, it has always been because others are succeeding still—so success must still be possible, I just don’t have the right winning combo of content, timing, and luck.
Of course, this is illogical in some sense—someone is always winning an algorithm because it’s a system that must have winners. What’s changing is not if there are winners or not, but more subtle factors that are harder to track:
If the winnings are getting better or worse
If the churn of who wins at any given time is more distributed across creators
How much it costs to win (and if it even makes economical sense to win)
The underlying business model or the “why” of winning and how the creator is actually getting paid
The ecosystems around algorithms are actually quite complex—something I learned when doing a deep dive and writing over 1000 pages on retailer algorithms at Amazon, Barnes and Noble, Google Play, Apple, and Kobo. And social and advertising algorithms are experiencing similar complexities as retailer algorithms.
For example, a Youtuber who is winning may be getting paid through advertising revenue and brand sponsorships. But someone using Youtube as a marketing channel may be getting paid through products and services off-platform. Those are different motivations that may give different creators different levers to pull within the algorithms. That complicates the analysis and breaks down the playbooks too.
In truth, when there’s change in the air, the issue is not the content, and the algorithms aren’t failing randomly. They’re optimizing exactly as the platforms designed them to—for ad revenue, for session time, for platform-native content, for engagement loops that keep users inside the walled garden. Those are rational business decisions from the platform’s perspective, they just happen to be terrible for creators.
Hence, enshittification. We know it’s happening, but it’s still not the whole story.
The real question is: why is enshittification happening everywhere, all at once, across every major platform? The answer is something that most people aren’t looking at.
What Is Actually Breaking Across All Algorithms
The real bottleneck in any media ecosystem has never been production, but human attention.
A person has roughly sixteen waking hours, which gives them limited reading and watching capacity, and emotional investment. There is a hard cap on how much culture any individual can consume. That cap hasn’t changed since the invention of the printing press—and it’s not going to change now.
The internet has always had more content than anyone could consume. There was already more content than a person could process in 2005, and the same trend happened in 2010, and 2015, and 2020, and 2025.
Content surplus is not new. We’ve been drowning in content for decades. So what is it then?
What actually breaks the systems is when a technology comes along and makes content production dramatically cheaper and faster, creating a fresh explosion of supply that the current filtering tools weren’t built to handle.
The problem isn’t that we moved from scarcity to abundance. We’ve been in abundance for a long time. The problem is that we keep experiencing new scales of abundance—content explosions so large that the discovery systems managing the previous scale can no longer keep up.
And that is what is happening now with generative AI.
Luckily…There Are Answers in History Around How We Respond
After the printing press exploded book production in Europe, readers couldn’t evaluate everything. New professions emerged to handle the surplus—editors, critics, publishers. These people didn’t create art, but they did create value as filterers and curators. Publishing houses became the discovery layer for literature.
This same pattern has happened across all creator industries:
The rise of mass-market magazines created editors and editorial brands that decided what was worth reading
The emergence of radio, and music becoming effectively free to the listener, created an ecosystem of DJs, programmers, and labels that shaped what people heard
The expansion of film and television created studio executives, distributors, festival programmers, and critics who filtered what reached audiences and what mattered culturally
The rise of blogging and online media created aggregators, tastemakers, and niche editorial hubs that helped readers navigate the flood of digital writing
The social media era created influencers, recommendation networks, and algorithm-amplified human tastemakers who could surface what spread through culture
Every time a technology triggered a fresh supply explosion, the existing filtering layer buckled—and new curators emerged to help people navigate the flood.
The internet is not exempt from this pattern. It’s just moving through it faster than any medium before it.
And once you see the pattern, the current moment stops looking chaotic. It starts looking like a very specific phase of a very specific cycle.
The Hidden Pattern Underneath the Chaos
Here’s where it gets interesting—and honestly, this is the part that made me sit back and go, oh.
The internet has always relied on both automated discovery and human curation running in parallel. Even during the peak of algorithmic feeds, people still discovered culture through critics, tastemakers, communities, and word of mouth. The difference between eras isn’t whether humans or machines do the filtering—it’s which system dominates and where power sits.
What shifts is the balance. And that balance is driven by one thing—the relationship between the current scale of content supply and the dominant filtering system’s capacity to manage it.
Here’s how that has played out.
The Directory Era (1990s). The earliest web was small enough to organize by hand. Yahoo Directory, DMOZ, and similar projects had editors manually categorizing websites into browsable lists. This worked because the web was still small—a few hundred thousand sites could be meaningfully sorted by teams of humans. Automated search existed, but human curation dominated. Then millions of websites appeared—a fresh supply explosion—and human-scale curation couldn’t keep up. The balance tipped toward automation.
The Search Era (2000s). Google’s PageRank replaced editorial judgment with mathematical ranking—the more websites link to something, the more important it probably is. Search became the dominant discovery layer for nearly two decades. Human curation didn’t disappear—book reviews, music critics, magazine editors all continued to work—but search dominated. Google search specifically also heavily weighted inbound links—a human curation signal—through a proprietary scoring called Pagerank. All of this made the surplus manageable again, until SEO manipulation, content farms, and sheer web scale overwhelmed mathematical sorting, and the balance began shifting again from individual blogs to social media sites.
The Algorithmic Feed Era (2010s). Instead of users searching for content, platforms like Facebook, Instagram, YouTube, TikTok started allowing creators to publish right there. You didn’t need to run a website anymore—and online branding wasn’t only for the nerdiest among us (tech people, bloggers). Then, social sites started pushing content to users automatically. Discovery became passive as algorithms decided what you saw. This powered the entire Creator Economy boom. Unknown creators could publish something and have a platform’s algorithm carry it to millions. The surplus of content was once again enormous, but algorithmic feeds made it navigable—for a while. Human curation continued underneath—communities, word of mouth, fandom networks—but algorithmic discovery dominated.
The AI Saturation Era (2020s). And this is where we are. AI turns content production into something close to a zero-cost activity. Anyone can now generate articles, videos, images, books, and marketing copy at scale. Generative AI didn’t break algorithmic systems, but instead triggered the next supply explosion—one that stress-tested a system already under strain. Long story short, most of the systems running on algorithms have buckled. The surplus went from overwhelming-but-navigable to overwhelming-and-unnavigable. Discovery systems built for the previous scale of abundance cannot handle this one.
Here’s the important takeaway of this history lesson: none of these systems replaced the previous one. Directories still exist in niche form. Search is still massive. Algorithmic feeds still run social media.
Instead, each era became infrastructure underneath the next. What changed in all cases was which layer held the most power over how people found things.
And further—every time the dominant filtering system strained under a new scale of supply, the same thing happened—trust-based human curation became more valuable again. The automated systems that had been handling the volume were no longer keeping up, and people needed human judgment to help them navigate the new flood.
That’s the pattern:
Step 1: New production technology triggers a supply explosion; meanwhile, attention stays fixed
Step 2: Existing discovery and surfacing filters buckle
Step 3: The filtering layer reorganizes—and trust-based, human curation regains importance
Step 4: Automation tools catch up on what human signals matter the most
Step 5: People come to the tool because it’s genuinely useful; human curation wanes
Step 6: Money flows to the tool; power users come, then celebrities come, then scammers come, then the general population comes
Step 7: The tool reaches a tipping point of market share, becoming dominant
Step 8: The tool can’t grow monetization through new users, so it moves to charging creators
Step 9: Enshittification is declared; the alt-tools flood the market, trying to chip away at market share
Step 10: The cycle begins again at Step 1
We’ve seen it many times before, and now we’re inside it again.
Why This Moment Feels Different
If this is a repeating cycle, why does this moment feel like more than a normal platform shift?
Because the scale of the supply explosion is unprecedented, and the rate of change itself is destabilizing for Big Tech.
Every previous transition increased content supply by a significant amount. The printing press, the web, social platforms—each one made production meaningfully cheaper and faster…But all of this was happening inside format silos. What was consolidating in film didn’t immediately affect what was consolidating in books, and vice versa.
Previous supply shocks were format-specific:
The printing press exploded book production
Radio exploded audio distribution
The web exploded text publishing
Social platforms exploded short-form video and image production
Each one overwhelmed its own filtering layer.
In contrast, generative AI is collapsing the cost of content production toward zero across every format simultaneously. Text, image, audio, video, code—all at once, and very quickly—with new collapses month to month. That has never happened before.
That’s why creators across every platform and every format are feeling the instability simultaneously. A single production shock (generative AI) is straining every filtering system at once.
Creators Are the Canary in the Coal Mine
If you’re a creator reading this, you already know something I want to name explicitly: we have been the earliest signal of every one of these shifts.
We were the first to notice SEO degrading. The first to see Facebook reach collapse. The first to feel Amazon’s algorithm swings. The first to watch newsletter deliverability erode.
We detect these shifts first because our income sits directly on top of discovery systems. When the ground shifts, we feel it in our revenue before anyone else sees it in their data.
I felt it. I’ve been watching my own content’s discoverability erode for the last couple of years and asking myself whether I was doing something wrong or whether the ground itself had moved. The answer—which took me longer than I’d like to admit—is that the ground moved. And it’s still moving.
Institutions—traditional publishers, record labels, Hollywood studios—can be less affected at first because they rely on different discovery systems—brand recognition, media relationships, retail distribution, cultural gatekeeping. Those legacy systems are more resilient than algorithms, which usually buys the institutions time. But they’re not immune—Hollywood is fighting over AI, publishing is struggling with copyright law, and the music industry is grappling with AI-generated content flooding streaming platforms.
As the Curation Layer Reorganizes, Who Holds the Power?
So the filtering layer is reorganizing. What does the new mix look like?
I’d rather start with what it’s not. The future is not “humans replace algorithms” or “AI replaces human taste.” It’s a rebalancing of roles. Machine systems and human curation have always coexisted—the question is which one dominates and where power sits. What’s shifting is the balance.
Two developments are converging simultaneously.
The first is trust-based curation regaining importance at scale. People are increasingly relying on trusted creators, communities, newsletters, fandom networks, events, and collaborative ecosystems to decide what’s worth their attention. Instead of trusting an algorithm to surface the right content, they’re trusting people—curators with taste, communities with shared values, creators they’ve built relationships with over time.
You can already see this everywhere. Curated newsletters are booming. BookTok recommendation networks drive more book sales than most publisher marketing departments. Fandom communities on Discord and Reddit organize entire genres. In-person events and festivals are becoming discovery hubs.
This isn’t new—it just got buried under automation for a while. Now that automation is straining under the latest supply explosion, trust-based curation is resurfacing as a primary filtering mechanism—this time with internet-scale tools and reach.
If you’ve been building community, building fandom, building real relationships with your audience—you’ve been building filtering and curation infrastructure for the next era, whether you knew it or not.
The second is AI agentic discovery. Instead of you browsing, scrolling, and comparing, an AI agent will likely soon be doing it for you. AI shopping assistants, AI research tools, AI conversational search—these are early versions of a world where a bot handles your navigation through the surplus. Big Tech is investing heavily here. Google, Amazon, OpenAI, and others are all building toward a future where AI agents are the primary way people move through the internet’s content surplus.
Both are real. Both are already happening. And the most likely future involves both—working together in ways most people haven’t thought through yet.
And it’s not all that different than what we have had. Algorithms have always run on rudimentary signals from humans—viewing, linking, liking, sales, engagement—that are supposed to indicate meaning. And humans have long used machine- or industry-generated filters to curate meaning too.
While AI agents are excellent at navigating large volumes of content and filtering for relevance and efficiency…
…They struggle with taste, identity, cultural meaning, and the emotional resonance that makes someone fall in love with a story or trust a creator. Those things require human judgment operating inside a relationship of trust.
Machines handle the scale. Humans provide the meaning.
But the question of who builds and who controls the curation layers matters enormously. If that layer is entirely owned by the same Big Tech companies that built the algorithmic systems currently straining under their own weight...We’ve just moved the same power dynamics to a new platform.
We currently have a window in which we—individually and/or collectively—can take back some of the power around this dynamic.
As Creators, it’s our time to unenshittify things.
There is One More Layer to This Which Indicates Opportunity
Consumers will consume based on trust—and the largest sentiment out there is people are tired. Trust in journalism and the media has eroded, trust in politicians has definitely eroded. The issue platforms are having is not just that AI is flooding their algorithms and gaining traffic, but that there’s so much of it that is just not good. When a platform delivers even 20% of bad experience and doesn’t have enough value to force people to stick around, people will lose the habit of the platform.
You can likely intuitively feel this too—regular YouTube watchers ditching it because 20% of the videos are low-quality AI content. Readers leaving Kindle Unlimited because of too many bad reading experiences. Scrollers abandoning TikTok because it’s the same tired AI-generated videos again and again.
On a personal level, I’ve pulled back from YouTube because it’s so hard to find creators I am interested in. The same has happened with TikTok—my oldest child and I were using it for a few minutes, a few nights a week to practice identifying AI together, as I thought it was an important skill to discuss with him. After very little time, it was showing us the same few types of videos that had no value to his growing brain, and eventually there was not even interesting AI education to be had.
We have also pulled back on our children watching YouTube for any reason—we are more likely to direct them to a show on Netflix or Disney where we understand the branding and can keep them from watching low quality AI content.
Once those habits are out, it’s hard to reestablish them—especially when the humans don’t really miss the habit + know the habit is not great from them anyway.
We are on platforms almost entirely because of the dopamine hit—so if those platforms can’t give it to us reliably, it’s much easier to check out.
The 10-step process that has dominated how the internet does discoverability may also be breaking down. Because platforms need to become dominant, and domination requires consistent good dopamine hits, and consistent good dopamine hits requires good discoverability and effectively keeping the scammers out.
AI is making life difficult for large platforms on both ends.
Fragmentation is normal in competitive systems, and for creators, the last big fragmentation to tear down major gatekeeping was around institutions. Record labels, radio stations, publishing houses, cable channels, and film studios survived, but they never pieced back together their empires. Instead, Big Tech companies Google, Amazon, Apple, Facebook, and Spotify carved out their own pieces of the market and kept them.
I believe that the rapidity of AI could keep systems destabilized for a while, if not permanently, which means there’s more and longer opportunity for trusted curation to emerge.
What This Means for Creators
Here’s the part that changes what creators should be building.
In the algorithmic era, creators were content producers operating inside someone else’s discovery system. You made the content, but the platform decided who saw it. For a while, that bargain worked and was helping creators rather than squeezing them.
In the emerging era, creators who build trust networks, communities, events, ecosystems, and recommendation loops are no longer just making content inside discovery systems. They’re becoming part of the filtering infrastructure itself.
That’s not a small shift. That’s a fundamental restructuring of where power sits in the Creator Economy. In the algorithmic era, platforms controlled discovery and creators were dependent on their systems. In the emerging era, creators who build their own discovery ecosystems—audiences, communities, events, fandom, collaborative networks—become the discovery layer themselves.
And that...Is a big deal. Because the more content exists, the more valuable trust-based filtering becomes. Creators have been building that trust for years, often without realizing it was going to become the most valuable thing they own.
I don’t say that lightly, because this shift has cost me and a lot of creators I care about real money and real momentum. But here’s what I actually find exciting—what comes next may actually favor creators more than what we’re leaving behind, because our structural position is stronger.
The rest of this series explores what we while discoverability is destabilizing…Because there’s so much we can do to reclaim our space and prepare for the future of the Creator Economy.
Signals I’m Watching
These are real-world developments that reinforce the patterns I’ve described. I’ll be tracking signals like these throughout the series.
Organic Reach is Collapsing
Instagram’s organic reach fell to just 4.0% in 2024—an 18% decline year over year—and dropped further to 2–3% for publishers by mid-2025. If you’ve built an audience of 50,000 followers through years of consistent work, fewer than 1,500 of them see any given post. The algorithm has decided the other 48,500 people who chose to follow you don’t get to see your content. (Blog Herald)
Facebook organic reach has fallen from 16% in 2012 to 1–2% in 2025, Instagram’s reach rate dropped 12% to 3.50%, and LinkedIn saw an even more dramatic 34% slide. The decline is happening everywhere, not just on one platform—the structural shift away from organic distribution is industry-wide. (Hootsuite)
A 2026 survey of 1,000 U.S. creators found that 46.2% of Instagram creators, 76% of TikTok creators, and 59.1% of long-form YouTube creators receive fewer than 1,000 views per post. The vast majority of creators are struggling for visibility across every platform, confirming that building meaningful reach remains the primary challenge. (Influencer Marketing Factory)
Platforms have quietly shifted from distribution engines to discovery engines—prioritizing AI-driven content matching over follower relationships. Up to 50% of the content users now see in their Facebook feeds comes from “unconnected sources,” accounts they don’t follow. The implicit bargain of “build an audience, and the platform helps you reach them” has been quietly voided. (DMNews)
Customer Acquisition Costs are Climbing
Customer acquisition costs have surged 222% over eight years, with the acceleration particularly pronounced in digital channels. The average financial loss per acquired customer jumped from $9 in 2013 to a projected $29 by 2025. Channel saturation, privacy regulations, and diminishing marginal returns are all compounding. (SimplicityDX)
Between 2023 and 2025, customer acquisition costs jumped 40–60%, driven by higher competition, privacy rules, and attribution challenges. Privacy changes like iOS updates and GDPR have made targeting less precise, driving up costs even as platforms improve. (Phoenix Strategy Group)
Growing customer acquisition costs contributed to a 10-point decline in the importance of new customer acquisition as a marketing priority. The IAB’s 2026 Outlook Study found that while 54% of marketers still cite acquisition as a top goal, that figure has dropped significantly—and the focus on driving repeat purchases has nearly doubled since 2024, pointing to challenges in bringing new business in. (IAB)
AI-Generated Content is Flooding the Internet
Europol warned that as much as 90% of online content may be synthetically generated by 2026. This isn’t just text—it includes images, video, audio, and deepfakes across every format simultaneously. (Europol)
Meltwater reports a ninefold increase in mentions of “AI slop” in 2025 compared to 2024, and research by Kapwing estimates that 21–33% of YouTube’s feed may consist of AI slop or “brainrot” videos. “AI slop” was named Word of the Year 2025 by both Merriam-Webster and the Australian National Dictionary. (Future Center UAE)
Content grounded in lived experience, tested knowledge, and real-world work is being buried under an AI flood across Facebook, Pinterest, and beyond. As AI begins training on its own output, distortions will compound, creating an internet that feels more synthetic by the day. Nieman Journalism Lab predicts that in 2026, AI will outwrite humans. (Nieman Journalism Lab)
Trust-Based Curation Is Resurfacing Through Newsletters
The world's largest newsletters now operate like media companies—with multiple publications exceeding 1 million subscribers. 1440, The Rundown, TLDR, Morning Brew, The Hustle, Nice News, MarketBeat, and others have built massive audiences through curation-first models. The common thread: they offer curated value that feels uniquely human in a landscape increasingly saturated with AI-generated content. (Paved)
Readers increasingly prefer newsletters from individuals rather than faceless brands, and personality-led content is the key differentiator from AI-generated competition. Newsletters need to hook people on their unique perspective and style—giving readers something they can't get anywhere else. As HubSpot data shows, 64% of newsletter professionals believe newsletters will be mostly AI-generated by 2030, which paradoxically makes the human-curated ones more valuable, not less. (HubSpot)
Over 17,000 writers now get paid on Substack, and the platform added more than 1 million paid subscriptions between November 2024 and March 2025 alone. Notably, roughly 25% of paid conversions now come from Substack's own internal recommendation and feed features—meaning the platform is building its own trust-based discovery layer. (Backlinko)
Beehiiv housed more than 50,000 newsletters as of 2024, nearly doubling from the year before. The growth isn't just in volume—it's in sophistication. Beehiiv's November 2025 "Winter Release" expanded its vision significantly, adding AI-powered website building, digital product sales, podcast hosting, and advanced analytics—positioning it as a complete creator operating system rather than just an email tool. (IEM Labs)
Creators on Patreon have surpassed $10 billion in cumulative payouts and over 25 million paid memberships, with annual creator earnings now exceeding $2 billion. More than 250,000 active creators monetize on the platform, up 15% from 2023. Patreon has been boosted specifically by the increasing value of smaller creators and the growth of private communities. (Contrary Research)
Community-Driven Curation Is Reforming Alongside Traditional Algorithmic Discovery
More than 50 million books recommended by BookTok were sold across Europe in 2025, generating €800 million in revenue. In Germany alone, 28 million BookTok-recommended books were sold—more than double the 12 million sold in 2023. TikTok announced the expansion of its BookTok Bestseller List into the UK, Italy, and Spain. (TikTok Newsroom)
In 2024, BookTok-driven demand helped generate 59 million print book sales in the U.S., contributing to an estimated $760+ million in revenue tied to TikTok-discovered titles. What began as a grassroots reader movement has evolved into one of the most powerful commercial engines in publishing—and it hasn’t slowed heading into 2026. (WriteStats)
By 2026, BookTok creators have become essential marketing partners for every major publishing house. Publishers now acquire books based on their “TikTokability”—they want plots that creators can summarize in a 10-second emotional hook. Bookstores feature “As Seen on BookTok” sections that have become some of the highest-performing areas in stores. (Rolling Stone)
AI Agentic Discovery is Emerging
Agentic commerce—where AI agents autonomously discover, compare, and purchase products on behalf of consumers—is emerging as one of the defining commerce trends of 2026. Amazon, Google, OpenAI, and Meta have all launched AI shopping tools in the past year. AI platforms are expected to account for $20.57 billion in U.S. retail ecommerce spending in 2026, nearly quadrupling 2025 figures. (eMarketer)
Google launched its Universal Commerce Protocol (UCP) in January 2026, partnered with Walmart, Target, Shopify, Etsy, and 20+ others. Brands now face a three-ecosystem world: Amazon’s proprietary agents, Google’s UCP, and OpenAI’s approach. McKinsey forecasts $3–5 trillion globally in agentic commerce by 2030. (CNBC)
OpenAI pivoted away from its Instant Checkout feature after realizing users researched products in ChatGPT in droves but weren’t completing purchases there. Walmart’s data showed ChatGPT’s integrated checkout performed three times worse than having users complete purchases on the retailer’s own site—highlighting that this space is still being figured out. (CNBC)
The Power Reordering Between Platforms Institutions, and Independent Creators is Building
The number of AI copyright infringement cases filed against AI companies more than doubled in 2025, from around 30 to over 70. The biggest development was the $1.5 billion settlement in Bartz v. Anthropic—and settlements and partnerships were the dominant trend, with more expected to multiply in 2026. (Copyright Alliance)
Warner Music Group settled with both Suno and Udio in November 2025, and Universal Music Group settled with Udio in October 2025. These deals established licensing partnerships where new AI models would be trained on authorized catalogs with artist opt-in provisions—shifting from pure litigation to commercial partnership. (Copyright Alliance)
Disney and Universal filed a first-of-its-kind copyright suit against Midjourney, while Pulitzer Prize-winning author John Carreyrou led a December 2025 lawsuit against six major AI companies. Lawsuits and licensing deals surged in 2025 as authors, journalists, record labels, and Hollywood studios fought over unauthorized use of intellectual property for model training. (Caixin Global)
Consumers Shift Toward Trust and Authenticity
The UK government scrapped plans in March 2026 that would have allowed AI companies to train on copyrighted music without permission. Over 10,000 submissions flooded the consultation, with only 3% supporting the AI-friendly approach—a massive backlash from the creative industries. (Silverman Sound)
Spotify has removed over 75 million tracks it classified as “spammy,” many of which were low-effort AI-generated content. Apple Music launched “Transparency Tags” in March 2026, and Deezer uses proprietary detection technology to automatically tag AI-generated music. The music industry is grappling with AI flooding streaming platforms across every major service. (Jam.com)
Consumer preference for AI-generated content has dropped to 26%, down from 60% three years ago. The Sprout Social Q4 2025 Pulse Survey reinforces that consumers prioritize human-created content in 2026, assigning new value to authenticity as a brand differentiator. (Sprout Social)
While 77% of marketers believe AI effectively crafts emotionally resonant content, only 33% of consumers agree—a 44-percentage-point disconnect. Research also shows 52% of consumers reduce engagement with content they believe is AI-generated, even before confirmation. (NetInfluencer)
The Association of National Advertisers chose “authenticity” and “agentic AI” as its dual Words of the Year for 2026. Marketing professor Colleen Kirk notes that “consumers are becoming ever more skeptical of the human origin of advertisements and marketing messages” while emphasizing that “authenticity is always best.” (Phys.org)
This is Post 1 of The Infinity Era, an eight-part series on how AI, curation, and creator ecosystems are reshaping how the internet discovers and values creative work. The full series publishes on Letters on the Future.
Hi! I’m Monica Leonelle, futurist, storyteller, and context curator exploring how technology and AI are reshaping the future of creative work. I’m a USA TODAY bestselling author, former software engineer, and Chicago Booth MBA who has published 50+ books. I’ve spent the last two decades building, analyzing, and writing about the creator economy from the inside, and my work has been featured in outlets including Forbes, Inc., Newsweek, AdAge, and The New York Times.