If “the internet is cooked” had a corporate deck, 2025 would be slide one.

The word slop—once basically “wet leftovers for animals”—became a serious label for something we all recognize: cheap, mass-produced AI content that looks like information but behaves like noise. Merriam-Webster didn’t just nod at the trend; it crowned “slop” Word of the Year and formalized the definition as AI-produced low-quality digital content made in quantity.

Here’s the uncomfortable part: AI slop isn’t just a “quality problem.” It’s a systems problem:

So, this isn’t a rant. It’s a field report: scale, impact, and governance paths that don’t rely on wishful thinking.

1) What Counts as “AI Slop” (And What Doesn’t)

Let’s separate terms that get mixed together:

That’s why the Merriam-Webster definition matters. It anchors the term in two critical properties:

  1. produced usually in quantity
  2. low quality

Intent can be malicious or merely lazy. Slop doesn’t need a conspiracy; it only needs a CPM.

2) The Scale: Are We Actually Past the Tipping Point?

A lot of “AI dominates the internet” claims are vibes dressed as statistics.

The cleaner way to talk about scale is: in specific measurable slices of the web, AI output is now comparable to human output.

Graphite analyzed a dataset of online English-language articles over 2020–2025, and Axios visualized the result: by May 2025, human-written articles were about 52%, while AI-written articles were about 48%.

That’s not “the whole internet” (and the methodology matters), but it’s still a cultural threshold:

Also, even Wikipedia’s “AI slop” entry frames the term around mass production and monetization dynamics.

3) Why 2025 Made Slop Inevitable: The Incentive Stack

Three forces made 2025 feel different:

3.1 The marginal cost of content went to ~zero.

If you can generate 1,000 “SEO articles” in an afternoon, content becomes a commodity. And commodities flood markets.

3.2 Distribution is automated.

Recommendation algorithms don’t ask “is this meaningful?” They ask, “Will someone pause for 1.2 seconds?”

3.3 Monetization doesn’t care who wrote it.

Ad networks pay for impressions. Affiliate programmes pay conversions. That’s a slop subsidy.

This is why slop is not only on social media. It’s also in:

4) The Damage: It’s Not Just Annoying

4.1 Workslop: The workplace version of slop.

BetterUp Labs + Stanford Social Media Lab describe “workslop” as AI-generated content that looks polished but lacks substance, creating an “invisible tax” where colleagues spend time cleaning it up.

The key takeaway isn’t the exact dollar figure. It’s the dynamic:

AI doesn’t always remove work; sometimes it moves work downstream to the next person.

4.2 Marketplace trust is getting sandblasted.

There’s measurable evidence of likely AI-written reviews climbing on major fast-fashion/low-cost e-commerce platforms.

Originality.ai reports likely AI reviews about Temu on Trustpilot, rising to 10.90% in 2025 (and up sharply from earlier years). Cybernews reports similar figures for Temu and Shein, framing this as a surge in AI-generated reviews.

When reviews become synthetic, “social proof” collapses. And platforms pay the cost in customer support, refunds, and reputation.

4.3 Elections: Deepfakes as The Sharpest Edge of Slop.

Not all slop is deepfake, but deepfake is the slop category that gets people hurt.

During Ireland’s presidential race, multiple outlets reported an AI-generated video falsely claiming candidate Catherine Connolly had quit, prompting platform removals and legal/political scrutiny.

Even if the election outcome doesn’t flip, the trust damage compounds:

5) The Governance Reality: The 3-Layer Strategy That Might Work

We don’t “solve” slop with one law or one detector. We reduce it by attacking three layers: provenance, distribution, and economics.

5.1 Provenance: Labels, Metadata, and Traceability

China’s Cyberspace Administration of China (CAC) published the Measures for the Labeling of AI-Generated Synthetic Content, with an effective date of September 1, 2025.

The directional lesson isn’t “copy China.” It’s that labelling becomes part of the infrastructure:

5.2 Distribution: Platform friction beats perfect detection.

Detection is hard—and getting harder.

Research on “faithfulness hallucination” detection is improving (e.g., FaithLens proposes joint detection + explanation). But even great detectors won’t catch everything, and false positives create backlash.

So, platforms will need friction:

Friction is less glamorous than AI vs. AI, but it works because it changes behavior.

5.3 Economics: Stop paying for junk.

If ad networks and affiliate programmes keep paying for slop, the slop machine will keep running.

A practical governance move:

This is the “follow the money” layer, and it’s the most neglected.

6) The Weird Twist: Even “Words of the Year” Became a Signal

You’ll see sloppy claims floating around, like “The Economist picked slop as word of the year.”

It didn’t. The Economist’s official Word of the Year piece for 2025 chose TACO (“Trump Always Chickens Out”).

But the broader cultural signal is real:

Together, they map a coherent 2025 mood: we’re drowning in synthetic content and engineered emotion.

7) A Practical Playbook for Teams (Not Governments)

If you’re not a regulator, here’s what you can do inside a company/product:

7.1 For Content Teams

7.2 For Product + Platform Teams

7.3 For Engineering Teams Shipping AI Features

The goal is not “no AI.” The goal is no cheap amplification of low-value output.

Final Take: Slop Is an Incentive Failure Wearing a Tech Costume

AI slop exists because it’s profitable to produce and cheap to distribute.

So, the fix is unsexy:

If we do nothing, the web doesn’t “end.” It just becomes a place where signal costs money and noise is free.

And that is how a civilization ends up eating content troughs for breakfast.