AI Didn't Invent Slop—It Learned From Corporate America

Everyone’s losing their shit about AI slop.

Scroll through any platform and it’s wall-to-wall panic about ChatGPT articles junking up Google, bots flooding comment sections with gibberish. “AI is destroying the internet!”

Except AI didn’t invent meaningless content. We did. We’ve been mass-producing it for decades, and we trained entire generations of workers to churn it out without question.

I still remember an email thread from my old Fortune 500 job. Twenty-three messages about “aligning strategic priorities for Q4 stakeholder engagement.” By message fifteen, nobody knew what problem we were solving. By message twenty-three, someone scheduled a meeting to “synthesize our thinking.”

The meeting was forty-five minutes of corporate nothing-speak. The deliverable? A shared doc that seven people would “contribute to” and nobody would ever open.

If ChatGPT made that, we’d call it slop. Since humans did, we called it Tuesday.

The Original Content Farm

Anthropologist David Graeber nailed it in 2018 with Bullshit Jobs, roles that even the people doing them knew were pointless. But he missed an important element in his analysis: these jobs weren’t just creating meaningless work. They were creating meaningless content.

Think about your average corporate day:

• Consultants pump out strategy decks for managers who don’t strategize

• Managers write executive summaries for executives who don’t read

• Analysts analyze things anyone with Google could figure out in ten minutes

It’s a content factory that makes BuzzFeed look scholarly.

A friend at big four consulting firm showed me her team’s monthly haul: sixty-seven PowerPoints, forty-three “insights reports,” twenty-nine optimization frameworks. Implementation rate? “Maybe three things. And we were going to do those anyway.”

That’s not work. That’s slop with a salary.

How the Slop Machine Works

Corporate slop is genius because it’s self-perpetuating. Unlike AI slop that dies when people ignore it, human slop gets validated by other humans making slop.

Here’s the cycle:
Someone creates a “competitive analysis” (five companies, one chart). Meeting happens. Three people nod. “Let’s expand the scope.” Now you need a “market assessment” (ten companies, bigger chart). Leadership wants “strategic recommendations” (obvious conclusions with bullet points). Those become “implementation frameworks” (fancy to-do lists).

Six months and $200k later, someone changes a process an intern could’ve fixed on day one.

But everyone got paid, so it worked perfectly.

The Data That Proved It

I should know about meaningless work. I used to work at Asana, the company that coined the term "work about work" back in 2008. We were founded specifically because our co-founders got frustrated watching Facebook employees spend most of their day in meetings and emails instead of building products.

Our research consistently found that knowledge workers spend 60% of their time coordinating, searching for information, and managing priorities rather than doing the skilled work they were hired for. Think about that: only 27% of your workday goes to your actual job. The rest is slop with a salary.

The numbers were brutal. People lose 157 hours annually to unnecessary meetings. They work 455 extra hours late each year just to catch up on real work. Managers spend 62% of their time coordinating instead of leading or strategizing.

Asana published this research from 2019 through 2024, documenting a crisis that had been building since smartphones took over offices. This wasn't an AI problem waiting to happen. This was a coordination problem that had been strangling productivity for over a decade.

The "work about work" Asana measured was exactly what Graeber described: meaningless activity that exists to justify more meaningless activity. The only difference was we put numbers on it.

The Assimilation Trick

Here’s why we can’t see our own slop: the system trains us not to.

You start a corporate job thinking you’ll solve problems. Instead, you learn to navigate systems. You master their jargon until you forget your own words. You optimize their processes until you can’t remember what problem you came to solve. You produce their content until busywork feels important.

It’s not stupidity. It’s assimilation.

The machine doesn’t want you to ask whether the deck should exist. It rewards you for making better decks. It doesn’t want you to question the meeting. It promotes people who run efficient meetings about nothing.

After a few years, you stop noticing the work is meaningless. You just get better at producing it.
But what if you didn’t?

The Double Standard

The same people freaking out about AI destroying content are liking LinkedIn posts about how a barista’s latte art revealed the secret to customer retention.

“What my morning coffee taught me about leadership” gets 10,000 likes. ChatGPT writes the same post and suddenly we’re worried about the future of human communication.

The only difference? One comes with a job title.

What We Actually Trained AI On

Here’s what nobody wants to admit: AI learned slop from studying human slop.

Every boring AI blog post about productivity hacks was trained on thousands of boring human blog posts about productivity hacks. Every spam AI email learned from decades of human spam emails. Every generic AI LinkedIn post studied years of humans posting generic LinkedIn content for engagement.

We spent twenty years filling the internet with marketing fluff and SEO garbage, then acted shocked when AI learned to make marketing fluff and SEO garbage.

We’re basically angry at our digital kid for repeating what we taught them.

The Economics Make No Sense (But Perfect Sense)

AI slop exists because content creation is free.
Human slop exists because meaningless work is expensive, which makes it valuable for budget justification.

I know someone earning $120k to make quarterly reviews that summarize stuff everyone already knows for meetings where nothing gets decided. Economically insane. Organizationally rational.

Same incentives as AI slop. Just with better PowerPoint templates and dental plans.

The Real Crisis

AI slop will get filtered out. Google will adapt, platforms will evolve, people will learn to ignore it.

Human slop won’t disappear because it props up entire organizations. It keeps people employed and budgets spent. We’ve built an economy around producing content nobody wants for systems nobody understands.

Then we got mad when AI made it obvious how pointless it all was.

That’s the actual crisis.

What This Means

The most radical thing you can do isn’t optimizing the machine. It’s refusing to feed it.

Stop making decks nobody reads. Stop attending meetings about meetings. Stop creating reports that summarize other reports. Stop producing content that only exists to justify producing more content.

I know that’s easier said than done when your mortgage depends on looking busy. But recognizing the game is the first step to not getting played by it.

The machines aren’t ruining content. They’re just really efficient at making the content we were already ruining.

The slop was coming from inside the office all along.

David Graeber’s Bullshit Jobs: A Theory (2018) documented how modern work creates roles that even their occupants know are meaningless—a problem that extends way beyond individual jobs into entire content ecosystems.

Asana's Anatomy of Work research provides comprehensive data on "work about work" and its impact on productivity.