AI has changed content creation overnight. What once required time, skill or a production budget can now be spun up in seconds.
That’s led to an explosion of low-quality, made-for-advertising (MFA) content, not just across obscure websites, but also on social platforms like TikTok, YouTube and Meta.
For years, MFA was a mostly web-based problem: cheap, SEO-bait sites built to farm impressions. Social media marketers have always had concerns about monetizing some types of user-generated content, but the channel has been – for the most part – free of the MFA model.
Now, generative AI has supercharged that model, and it’s infecting social media feeds and vertical video platforms. With automated tools, bad actors can pump out thousands of videos a day, tailored to algorithmic incentives, at near-zero cost.
On social platforms, these videos blend seamlessly into feeds, making them harder to detect and block. That’s a problem for advertisers who rely on programmatic pipes that don’t always distinguish between authentic creator content and automated filler.
Why this matters for advertisers
MFA moving to social isn’t just a brand safety concern. It’s a waste and trust problem.
Ad budgets that should be funding meaningful creator ecosystems are instead being siphoned into AI-generated junk designed to keep viewers scrolling instead of connecting. This leads to:
- Wasted impressions that deliver minimal engagement or brand lift
- Erosion of media quality, as automated videos crowd out authentic creators
- Brand adjacency risks that can chip away at consumer trust when ads run next to obviously low-effort or misleading content
Social media is where the majority of digital ad dollars now flow. If MFA continues to spread on social channels unchecked, it could undermine the very environments brands depend on for reach and cultural relevance.
Platforms can’t solve it alone
Some social platforms are taking proactive steps against this growing issue, building new detection systems and experimenting with labeling AI content. But they’re up against the speed and volume of generative AI. And the economics of AI slop are simply too attractive: infinite content at minimal cost.
Advertisers need to step up by defining what appropriate AI content looks like for their brands. There’s a distinction between worthwhile AI content and MFA. This distinction also applies to AI content on social media.
MFA is engineered to exploit algorithms and ad systems while prioritizing monetization at the expense of meaning, artistry and audience connection. While gen AI can aid these practices, it can also be used for legitimate creative expression that enriches culture, rather than degrading it.
The challenge for advertisers is to identify where AI actually serves creativity and community. Each brand should set hard limits on what it will accept, rather than leaving it up to social platforms to come up with a “one size fits all” approach.
Here are three steps advertisers should take now to protect their budgets from waste as AI brings MFA to social media:
- Verify, don’t assume. Add independent layers of verification to see exactly where ads are running. Don’t accept platform reporting at face value.
- Define your comfort zone with AI content. Work with brand-suitability and safety partners to distinguish between AI-assisted creative expression and AI-generated MFA or fraud.
- Use AI thoughtfully. Automation can enhance efficiency, but advertisers should ensure it doesn’t compromise authenticity or quality.
A familiar inflection point
Digital advertising has been here before. Programmatic’s early days were plagued by low-quality supply, opaque reporting and misplaced trust. Standards eventually caught up, but not before marketers spent years cleaning up the mess.
The rise of AI-generated content is another inflection point. The difference now is nuance: not every AI-generated video on social media is a threat, but MFA and AI spam are.
The advertisers who act early, with clearer definitions, stronger partnerships and smarter verification will be the ones who preserve consumer trust, protect their budgets and thrive in an AI-native social media ecosystem.
“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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