The Creator Economy Is the Future of Work // Most Creators Will Never Earn Minimum Wage From It

I have a confession to make before we get into this one.

I built a social agency. I knocked it down. And I am currently sitting in the exact career crisis this piece is about — trying to figure out whether my future is in the industry I have spent years inside, or whether it’s time to walk into the casino and pull the lever.

I still have fractional clients. I’m still doing the work I know how to do, building out marketing departments, helping brands figure out who they are and how to talk to people. But I’m also doing this — writing, creating, putting my thinking out into the world — because somewhere in the back of my mind I’ve started to wonder if the thing I’m helping other people build is actually the thing I should be building for myself.

Which makes me an extremely unreliable narrator for this piece. Or possibly the most reliable one.

You decide.

Two Things Are True Right Now

Thing One: The creator economy is one of the fastest-growing industries in the world. It is currently valued at $234 billion. Brands now allocate up to 25% of their digital marketing budgets directly to creators. Creator ad spend is growing at four times the rate of the overall media industry. The influencer marketing sector alone is on track to hit $34 billion in 2026. The money is real. The opportunity is real.

Thing Two: 73% of creators earn less than $30,000 a year. The median creator income is $3,000 annually — and it declined between 2023 and 2025, while the market boomed. The top 1% of creators receive 21% of all ad payments. The top 10% receive 62%.

Both of these things are true. And they are true because of each other.

What’s Happening to the Old Industry

Let me give you some numbers from the world I came from first, because context matters here.

The traditional advertising industry is not quietly restructuring. It is — to quote the trade press directly — holding “a funeral for advertising.”

Since 2024: IPG has laid off thousands. Omnicom has laid off thousands more. P&G cut 7,000 roles. Between August and December 2024, the American ad industry lost 4,600 roles. Job openings in advertising and marketing fell 7.5% between 2022 and 2025. The holding companies that have dominated the industry for decades are consolidating, automating, and cutting — in that order.

And where is that budget going? To creators. The same brand dollars that used to pay a full creative team’s salaries now pay a creator’s sponsorship fee. The transaction is real. The redistribution is happening.

On paper, this sounds like a revolution. The little guys winning. The monolithic agencies finally getting what they deserve. The creative class taking back the means of production.

On paper.

The Casino

Here’s what nobody in the creator economy wants to say out loud: the platforms are, functionally, casinos.

Every creator showing up consistently, posting into the void, chasing the algorithm — is pulling a lever on a slot machine. Some will win big. Most will walk away empty-handed after years of trying. A tiny few hit the jackpot and become the story everyone else points to as proof it’s possible — because that story is essential to keeping everyone else playing.

But the house — Instagram, TikTok, YouTube — always wins. It doesn’t matter whether you make it or not. Your content, your data, your audience, your attention, and your hope are all value flowing upward to the platform, regardless of what flows back down to you. They need you to believe you are one viral post away, because the moment you stop believing, you stop producing — and the machine stops running.

The dream isn’t a side effect of the creator economy. The dream is the product.

This is why the median creator income has fallen while the market size has grown. The money is real. It’s just not going to most of the people creating the content that makes the platforms valuable enough for brands to spend it.

You Can’t Be Made Redundant (But You Can Be Deleted)

Here’s the thing that the “become a creator” conversation usually offers as its killer argument: you can’t be made redundant from your own audience.

And that’s true. Your boss can’t call you in on a Friday afternoon. No holding company can restructure you out of existence. No client conflict can end your contract.

But the algorithm can demonetise you overnight. A platform update can halve your reach with no warning and no appeal process. A single controversy — deserved or not — can unravel years of work in 48 hours. Your account can be suspended. Your account can be deleted. The platform can simply change what kind of content it wants to reward, and if you built your identity around the old version, you start again.

You don’t have a boss. You have an algorithm. And the algorithm doesn’t offer severance.

The difference between employment and platform dependency is not as large as the creator economy would like you to think. You’ve just traded one form of precocity for another — one with better aesthetics and worse labour protections.

Who Actually Makes It

There’s a truth running underneath all of this that I find both uncomfortable and clarifying, because I can see it from where I’m sitting.

The people who tend to break through in the creator economy are not, by and large, people who emerged from nowhere. They are people who already had something: skills developed inside the industry they’re now disrupting. Networks built over years of doing the work. Financial runway — savings, a partner’s income, client work on the side — that allowed them to build an audience before the audience paid anything back.

Emma Chamberlain’s runway wasn’t family money. It was being 16 and living at home — which is its own form of financial insulation that most adults contemplating the same leap simply don’t have.

The creator economy dismantled the gatekeepers of the old industry. But the skills, connections, and stability required to succeed in it? Still flows disproportionately to the people the old industry already trained.

The revolution redistributed the format. It did not redistribute the advantage.

I say this as someone who is quite consciously using the decade I spent inside marketing to inform the content I’m creating outside it. I am not outside this observation. I am a data point in it.

Where That Leaves Me (And Maybe You)

I am sitting in a strange place right now. I still have clients. I’m still the person helping brands think through how to build, what to say, who to say it to. That work funds the time I need to figure out whether I can build something for myself — whether my thinking is interesting enough, consistent enough, me enough, to build an audience around.

Which means I am simultaneously: the person helping brands understand the creator economy, and the person tentatively walking into the casino, chip in hand, wondering whether to play.

I think a lot of people in marketing and advertising are in this exact moment and not saying it out loud. The industry is changing fast enough that staying still feels risky, but the creator economy is not the sure thing it’s being sold as. The ground between those two positions is uncomfortable. There’s no map for it.

What I keep coming back to is this: the creator economy is genuinely worth something to the people who approach it with honesty — about what they actually think, what they actually know, and what they actually can’t see yet. The content that tends to cut through isn’t polished performance. It’s the specific perspective that nobody else has, shared without too much dressing.

Which might be the most reassuring thing I can say — and also, I’m aware, the thing every casino tells you about why your particular hand is worth betting on.

What I Know For Sure

The money is moving from the old industry to the new one. That’s real and it’s not reversing.

Most people playing the creator game will not make a living from it. That’s also real and also not reversing.

The platforms extract value from everyone, winners and losers alike. The algorithm is not your friend. You are building on land you do not own.

And the people best positioned to navigate all of this are the ones who can see the system clearly enough to make an honest decision about where to place their chips — rather than the ones who got swept up in the dream without reading the odds.

Two things can be true. The casino is real. The house always wins. And sometimes, knowing that, you still decide to play.

I’m still deciding.

Further Reading & Sources

On the creator economy and income inequality:

• Creator Economy Statistics 2026 — inBeat Agency — comprehensive data

• Creator Economy Income Distribution — Archive.com — the distribution breakdown

• Creator Economy Market Size — Precedence Research

On the advertising industry’s collapse:

• A Funeral for Advertising — Storyboard18

• Large Agency Layoffs — CM Galaxy

• AI or Accountability? The Real Story Behind 2025’s Layoffs — Advertising Week

Next up: The creator economy gave real people a seat at the table. Now the house is building AI influencers to replace them.

I have to preface this by saying, I wrote and worked on this piece pre 28th of February, when US and Isreal attacked Iran. I do however think it is more relevant than ever so I am sharing it now. I hope you are safe, brave and blessed <3

There is something quietly disorienting happening right now that almost nobody is naming directly.

We are all technically living in March 2026. But we are not living in the same year.

Depending on when you first paid serious attention to artificial intelligence — and how deeply you followed it — you may be operating with a mental model that is anywhere from three years out of date to current. The gap between those positions is not a small one. It is the difference between thinking AI is a clever search engine and understanding that autonomous systems are already making decisions without human input. It is the difference between protecting your position inside an existing structure and quietly questioning whether that structure itself can hold, and wondering what will come next.

This is not a piece about who is paying attention and who is not. It is about the speed of change, the unevenness of access, and the unfamiliar feeling of realising it is March 2026 and that perhaps time has now fundamentally shifted.

All responses to experiencing the rise of AI and the changing of time — curiosity, anxiety, denial — are human. None of them are wrong.

Let’s have a look at the timeline shall we…

The Timeline

November 2022 — The starting gun

ChatGPT launched on 30 November 2022. According to a UBS analysis cited by TIME magazine, it reached 100 million monthly active users within two months — faster than any consumer application in human history. TikTok required nine months to reach the same milestone. Instagram required two and a half years.

Most people experienced it as a curiosity. A useful toy. Something that wrote emails and summarised documents. Almost nobody — including, by their own subsequent admission, many of the people who built it — understood the scale of what had just been released into the world.

March 2023 — The people building it start to worry publicly

GPT-4 launched on 14 March 2023. It was multimodal — able to process both images and text — and demonstrated human-level performance on several professional benchmarks, including passing a simulated bar exam in approximately the top 10 percent of test takers.

In the same month, over 1,000 researchers and technologists signed an open letter calling for a six-month pause on AI development, citing societal and humanitarian risks. On 30 May 2023, hundreds of AI scientists and industry leaders — including Geoffrey Hinton, widely described as the godfather of modern AI, who had just resigned from Google to speak more freely — published a formal Statement on AI Risk: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

That statement was largely buried by the news cycle within a week.

2024 — The year it became structural

According to McKinsey’s State of AI report, 78 percent of organisations reported using AI in at least one business function by 2024 — up from 55 percent the year prior. OpenAI previewed Sora, a text-to-video model, demonstrating that the disruption would extend beyond images to video, voice, and human likeness. The European Union passed the world’s first comprehensive AI regulatory framework. Governments were drafting regulation approximately two years after it was needed.

2025 — The year of agents

This is where most people’s understanding currently stops. They still think AI is the thing that writes their emails. It is not, or not only.

McKinsey’s 2025 State of AI report recorded that 88 percent of organisations now use AI in at least one business function, and that 62 percent were at minimum experimenting with AI agents — autonomous systems capable of planning, reasoning, and executing multi-step tasks without human instruction. The World Economic Forum’s Future of Jobs Report 2025, drawing on a survey of 1,000 companies across 55 economies, projected that by 2030, 92 million existing roles will be displaced while 170 million new roles are created — a net gain globally, but one requiring the restructuring of 22 percent of all jobs and the obsolescence of 39 percent of existing skill sets within five years.

March 2026 — The reckoning

Steve Yegge, former engineering lead at Amazon, Google, and Sourcegraph, published a widely circulated essay in February 2026 describing what he calls the AI Vampire: the phenomenon of AI-driven productivity gains being absorbed entirely by employers, leaving workers exhausted without corresponding compensation or reduced hours. His proposed antidote was explicit: “Go touch grass every day. Do something without AI. Close the computer. Go be a human.” He argued the sustainable new workday, once AI is genuinely integrated, is three to four hours of cognitive work.

AI is no longer an experiment running alongside normal operations. It is inside them. Caroline Clark, writing in her Substack Liftoff with Caroline in February 2026, identified a convergence of three simultaneous consolidations — economic, political, and informational — all accelerated by technology. Drawing on Yanis Varoufakis’ book Technofeudalism, she describes how the AI companies now emerging mirror the pattern of cloud computing in the 2010s: a race to claim territory, lock in customers, and charge rent for access to infrastructure rapidly becoming as essential as electricity. OpenAI is backed by Microsoft to the value of $13 billion. Anthropic by Google ($2.3 billion) and Amazon ($4 billion). The entities controlling the frontier models are a very small number of very large players. Everyone else pays for access to infrastructure they did not build and do not own.

The IMF published a working paper in April 2025 finding that AI-driven productivity gains compound existing wealth inequality: those with capital are better positioned to benefit from the returns AI generates, while those whose labour is displaced have fewer resources to retrain or reposition. The Center for Global Development has documented a parallel divergence between nations — wealthier countries positioned to use AI to enhance productivity in high-value sectors, widening the gap with economies that cannot afford equivalent adoption.

The structure is not failing dramatically. It is continuing to perform. It is asking us to perform along with it. And the gap between those performing fluency with the shift and those genuinely navigating it is widening — quietly, without announcement, every single day.

The Levels — What Year Are You Actually Living In?

This is not a hierarchy. It is a map. The same person may occupy different positions in different areas of their life simultaneously.

2022 thinking AI is a clever chatbot. Interesting as a novelty. Working and living largely as before. The shift is theoretical.

2023 thinking Using AI for drafting, summarising, basic tasks. Treating it as faster search. Has not yet understood that the disruption is structural rather than functional — that it is not a better tool for doing the same things, but a different relationship between human capability and economic value entirely.

2024 thinking Integrating AI meaningfully into daily work. Beginning to understand which roles and industries are at risk. Possibly anxious. Still operating within the existing professional structure, using AI to preserve a position within it rather than questioning the structure itself.

2025 thinking Understands the agent shift — that AI is now acting, not just responding. Building with AI rather than just using it. Beginning to question whether the structures themselves can hold: employment models, intellectual property law, the meaning of value, the social contract between people and institutions.

2026 thinking Sees the full arc. Not panicking. Not denying. Understands that the most significant questions are no longer technical or economic — they are human. What kind of communities do we want to live in? What skills matter when most cognitive tasks can be performed by a machine? What is the difference between productivity and a life well lived? Quietly investing in things that will hold regardless of what the economy does. The embodied. The local. The slow. The trusted.

The Quiet Before

The WEF Future of Jobs Report 2025 projects that 39 percent of existing skill sets will be obsolete by 2030. McKinsey found that only 7 percent of organisations have fully scaled AI across their operations. The gap between those two facts is where most of us are currently living.

Nobody knows what comes next. The people building the technology do not know. The institutions attempting to regulate it do not know. The economists modelling its impact do not know. The range of outcomes on the table, from profound human flourishing to serious civilisational disruption, is genuinely wide. We are inside it, without the distance required to see its shape clearly.

What is clear is that the shift is already underway. It does not require your awareness to proceed.

How you prepare is a personal question with no universal answer. Mine looks like this: learning as much as I can about AI, regulating my nervous system, building real life skills, and reflecting seriously on my own values and where I actually stand.

That is not a recommendation. It is just where I am.

References

Center for AI Safety. (2023, May 30). Statement on AI risk. https://www.safe.ai/work/statement-on-ai-risk

Center for Global Development. (n.d.). Three reasons why AI may widen global inequality. https://www.cgdev.org/blog/three-reasons-why-ai-may-widen-global-inequality

Clark, C. (2026, January 24). #31 — Rewriting the belief that governs the world. Liftoff with Caroline.

Liftoff with Caroline

#31 - Rewriting the belief that governs the world

At Davos this week, Mark Carney addressed a room full of the world’s elite and political leaders to talk about Canada’s new role in the international order. It’s a brilliant speech and…

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8 months ago · 7 likes · Caroline Clark

Clark, C. (2026, February 14). #34 — The power of three. Liftoff with Caroline.

Liftoff with Caroline

#34 - The power of three

Part of this article references Technofeudalism by Yanis Varoufakis, which I recently finished reading as part of a book club with CPO Connect, a community for product leaders at Head of level and above. We held the book discussion yesterday, so credit for some of the ideas in this article must also go to fellow colleagues in the book club: Harry, John…

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7 months ago · 8 likes · Caroline Clark

IMF. (2025, April). AI adoption and inequality (Working Paper No. 2025/068). International Monetary Fund. https://www.imf.org/en/publications/wp/issues/2025/04/04/ai-adoption-and-inequality-565729

McKinsey & Company. (2025). The state of AI: How organisations are rewiring to capture value. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

OpenAI. (2023). GPT-4 technical report. https://cdn.openai.com/papers/gpt-4.pdf

Swartz, J. (2023, February 8). Why ChatGPT is the fastest growing web platform ever. TIME. https://time.com/6253615/chatgpt-fastest-growing/

Varoufakis, Y. (2023). Technofeudalism: What killed capitalism. Penguin.

World Economic Forum. (2025, January 8). Future of Jobs Report 2025. https://www.weforum.org/press/2025/01/future-of-jobs-report-2025

Yegge, S. (2026, February). The AI Vampire. Medium. https://steve-yegge.medium.com/the-ai-vampire-eda6e4f07163

It’s all a bit fucking boring.

Yes, this is a rant… (how did you guess?!)

Let’s just say that my break from working in social media for the last 14 years has meant that when I’ve come back online to peek into the crazy world you are all still adding to and consuming, it feels a bit, well, DULL.

I get it. We are bored people spinning around on a rock, no longer hunting and gathering but instead trying to figure out how to pay our rent or mortgages and make something meaningful and valuable in a very capitalist society.

But really, coming back online after a good long break in my now flourishing and beautiful balcony garden… what on earth is going on?! I had felt the undercurrent before - the “erm, we draw the line here” feeling when it comes to my career in social and not becoming a “prompt engineer” in the “attention economy”- but now there is no stepping back into this and thinking it is anything other than pretty shit.

AI slop has absolutely ruined my enjoyment of Pinterest, my previously favourite channel. All I’m now seeing are either AI prompts for fashion shoots (indistinguishable from real life) or gardens that, frankly, no amount of pruning will get you to.

LinkedIn makes me want to throw up in my mouth every time I hear “I’m delighted/honoured/proud”. Are you really though, Janet?! You couldn’t even write this post.

If I manage to read ONE post written in someone’s actual voice and not AI, it feels like a miracle after scrolling for 10 minutes.

Instagram is now flogging me “AI influencer” courses. Trust me, very few are making money and it is not worth the water used to power it.

Honestly, it is like the emperor’s new clothes out here. Are we all OK?! And HONESTLY, if I read the word “honestly” again, I want to chuck my laptop across the room. That, or “the real rub?”. IYKYK. WE ALL KNOW.

This comes across a bit like I’ve lost my mind, but I know for a fact it is not me (spoiler, it is all of us) and is in fact us as a society. We are numb. We are in denial. We are losing touch with who we are and what matters — at speed.

2026 feels like a much better time to opt out of adding to this absolute, boring chaos. Alas i’m writing about it. However, we are going to look back at this year (and ourselves) and cringe SO hard. The irony as I write this and post it online. I’m already cringing.

I predict there will be a race to be the last online and the last on social media. Like the great Facebook exodus for anyone under 40. The last ones consuming content will be the losers.

Will no one take a stand and do the most obvious thing ever and make a platform based on the “trust economy”?! (which is the most valuable commodity of our lives now) If you do, please share the link.

Again, if you didn’t get the messages, i’m bored online. Apart from Substack, thank goodness for Substack.

And yes, I bastardised ‘After the Ball"the 1899 painting by Catalan artist Ramon Casas i Carbó with Grok. Oh the irony.

Right, back to the garden.

These images are intended to be read as proof of human creation and posting, of real life being shared. A cry out to escape AI generated content. They are meant to reassure us that what we’re seeing is real. That a person was there.

I understand the instinct. When polish becomes cheap, we reach for texture. When perfection feels suspect, we trust mess.

But here’s the uncomfortable turn.
Mess itself can now be prompted.

Not just copied, but convincingly generated. With all the right cues. The accidental composition. The casual clutter. The appearance of effortlessness. What once felt like proof of life is now just another style.

That’s where something quietly shifts.

AI generated using this prompt: A macro photograph of a messy handwritten note on lined paper, written in blue ink with a ballpoint pen. The handwriting is slightly inconsistent in size and slant, appearing rushed but with the lines. Include subtle pen-pressure variations, slight paper smudging, and a few scratched-out words. The note is filled with to-do list items, arrows pointing to circled words, and marginalia. Realistic lighting from a slight angle,, 4k, no CGI look

Two stages of response

What’s striking is that many people are still responding as if we’re in an earlier phase.

Stage one is about proof.
People are trying to demonstrate humanness, and consuming content they believe signals it. Messy becomes meaningful. Imperfect becomes trustworthy. Texture becomes truth.

This makes sense. These signals worked for a long time.

Stage two is quieter, and more unsettling.
It’s the realisation that these same signals can now be generated just as easily. That the markers we’re relying on to identify one another in online spaces are no longer reliable.

The shift has already happened, but our shared understanding hasn’t caught up. The cost that once made these signals meaningful has collapsed faster than our ability to recognise it.

In that sense, much of what we’re seeing feels less like awareness and more like delay. Not denial as refusal, but denial as lag. People are still operating with a signalling system that no longer holds.

Why these signals stopped working

In economic theory, and later in communications and organisational studies, this dynamic sits within signalling theory, first formalised by economist Michael Spence in his work on information asymmetry.

Signalling theory looks at how observable traits or behaviours are used to signal underlying qualities in situations of information asymmetry. For a signal to function, it needs to be costly or difficult to fake. That cost is what gives the signal credibility.

Online, mess and imperfection functioned as signals of humanness precisely because they implied time, presence, and lived experience. They were not easily reproducible at scale, which made them meaningful.

But once those same markers can be generated cheaply and convincingly, they lose their signalling power. When a signal no longer carries cost, it can no longer reliably distinguish what it was meant to signal.

The breakdown here is not a failure of human judgement. It’s environmental. The conditions that once made these signals meaningful have changed.

Why this feels like a threshold

When any content can be generated, imperfection can be generated, and even proof of humanness can be generated, trust can no longer sit inside the feed.

It has to move elsewhere.

Into time.
Into consistency.
Into relationships.
Into reputation.
Into voice, presence, and embodiment.
Into things that cannot be instantly reproduced.

This is why there’s a renewed pull toward IRL experiences, smaller communities, slower media, and long-form thinking. Not as nostalgia, but as a structural response to a broken signalling environment.

The hidden cost

I’m not saying AI is bad.
I’m not saying this content is fake.
I’m not saying the trend isn’t a breath of fresh air.

What I am saying is that the audience is being pushed into a role they were never meant to occupy.

We’re no longer just consuming. We’re constantly, quietly verifying.

Who made this?
How was it made?
Why should I trust it?

That level of vigilance is cognitively exhausting. Historically, systems don’t survive that unchanged.

Social platforms were built on the assumption that authorship was legible. That you didn’t need to interrogate every artefact for signs of human life. When that assumption breaks, the system doesn’t end. It mutates.

The uncanny part

We’re not failing to read the signals.
The signals are failing.

And when that happens, people don’t just lose trust in content. They lose trust in the environment that trained them to read it.

That’s why this moment feels heavier than a trend cycle. It’s not about AI images versus real ones. It’s about what happens when the markers we rely on to recognise one another stop working.

A quiet threshold

I don’t think this is the end of social media. But it may be the end of a particular assumption. That authenticity is immediately legible. That reality can be read at a glance online.

When humanness becomes something you have to signal rather than something that’s assumed, you’ve crossed into a new phase.

And we’re only just learning how to live there.