Low-quality, AI-generated content – or AI slop – is flooding the open web. The entire digital ecosystem is adapting to the challenges that generative AI’s exponential growth presents.
As someone who spends a lot of time thinking about media waste and ROAS, I’ve seen how easy it is for bad actors to spin up thousands of low-value websites with a few clicks. These sites exist for one reason: to capture ad dollars. And generative AI makes it easier than ever to create slop at scale.
Some forecasts suggest that nearly 90% of all web content could be AI-generated by 2026, with certain sites already cranking out more than a thousand articles a day to try and maximize ad revenue through volume.
For advertisers, AI slop muddies the waters. Budgets get wasted, consumers are misled, and legitimate publishers lose revenue.
However, many publishers are experimenting responsibly, using AI to enhance reporting or streamline workflows while still applying human oversight.
The real challenge is drawing a clear line between the AI-generated content that adds value and the kind that erodes trust and leads to significantly lower ad effectiveness.
Telling the difference
Advertisers should focus on stopping the bad while preserving what works. It’s not about banning AI altogether but blocking the kind of content that’s purely designed to game the system.
The good stuff comes from reputable publishers who disclose their use of AI, apply fact-checking and prioritize relevance and accuracy. Source credibility, content accuracy, article depth and visual quality are all signals to help differentiate quality from slop.
Meanwhile, low-quality AI slop sites tend to resemble MFA, which should stand for Made for Arbitrage. They are characterized by a high ad-to-content ratio, repetitive or shallow articles and vague disclosures on the use of AI.
AI slop is also associated with other red flags, including content that’s plagiarized or lightly reworded from other sources, “hallucinated” facts and filler phrases that add no value. These pages often have identical templates with only keywords swapped, missing privacy/contact pages and very little real user engagement – a sign they’re built by and for bots, not people.
One of the most frustrating aspects of AI slop is how easily it slips into the programmatic ecosystem. AI tools let fraudsters and bad actors develop sites that look deceptively legitimate on the surface. Slop sites will often mimic the appearance of trusted publishers, so filters don’t always catch them.
Once these pages are approved by ad exchanges, they can quickly scale, appearing in thousands of programmatic auctions across channels. That means even sophisticated advertisers may unknowingly fund slop while believing they’re buying quality inventory.
An industrywide call to action
The industry has to work together to improve transparency between advertisers and publishers. Advertisers need to know how to identify AI slop. Quality publishers that supplement their human-generated content using AI should not be penalized.
Advertisers shouldn’t have to solve this problem on their own. Supply-side platforms as gatekeepers need to raise the bar for what qualifies as inventory. That means building smarter verification layers that go beyond URL reputation, incorporating content-level analysis, engagement signals and human validation to ensure only legitimate publishers make it through the pipe.
Prioritizing performance over surface-level metrics is key to keeping out AI slop from the inventory pool. For example, SSPs and DSPs can collaborate to create standardized “content authenticity scores” or integrate trusted third-party verification APIs that flag AI-heavy or duplicate pages before ads are served. Industry bodies like the IAB could also establish clearer definitions and labeling requirements for AI-generated content, similar to brand safety categories.
Greater transparency in the supply chain would also go a long way, like clear signals about where content comes from and how it’s created.
What advertisers can do
While the industry works toward stronger guardrails, there are steps advertisers can take today.
Look for publishers that show human oversight and disclose their usage of AI. Prioritize context and engagement quality over sheer scale, cheap reach or vanity metrics.
Advertisers can avoid wasting ad spend on AI-generated slop sites by regularly monitoring campaign performance. Simply put, quality sites have a 91% higher conversion rate than traffic served on these sites.
Advertisers that focus on performance and the metrics that matter, not just the positive viewability metrics that AI-generated slop sites optimize against, can avoid this low-quality inventory.
AI is only going to evolve, and the advertising industry will only continue to embrace the efficiencies it brings. If advertisers, platforms and publishers all step up, we can collectively ensure AI’s potential is used to add value rather than undermine it.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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