Published: June 07, 2026, 13:56 UTC
The first wave of AI influencers was easy to identify. Lil Miquela had her blunt fringe and freckles, Imma her bubblegum pink bob, Shudu Gram her flawless but clearly synthetic complexion. They were obviously digital productions, backed by studios, announced with fanfare, coordinated with brand deals.
That era is over. The fake people on social media have started looking much more like everyone else, and platforms are struggling to keep up.
From obvious to ambiguous
Robert Hart, a reporter at The Verge, documented the shift in a piece published Sunday as part of his weekly newsletter The Stepback. He describes a timeline where early AI influencers required studios, money, coordination, and polish. Characters like Emily Pellegrini and Aitana Lopez moved closer to reality, posting from nice restaurants, Coachella, and Wimbledon. Not relatable in the way most people live, but no less relatable than professional human influencers.
Lopez is the product of a Spanish creative agency called The Clueless, which manages an entire stable of AI influencers. Pellegrini’s creator, a pseudonymous figure who goes by Professor EP, used to manage OnlyFans creators. Now he sells courses teaching people how to make AI influencers of their own.
A lot of people are paying attention. The novelty has worn off, Hart writes, and early AI influencers stood out because there were so few. Now they are part of a much larger flood of AI-generated content inundating social media: low-quality text, slop images and videos, and an endless stream of synthetic engagement.
What platforms are doing
Social media companies have been slow to respond. AI influencers now slide into users’ direct messages, upsell drop-shipped products, and build follower counts that are themselves partly synthetic. Platforms that built their business models on engagement metrics have little incentive to remove accounts that drive interaction, even if the accounts are not real.
Some platforms have introduced AI content labels, but enforcement is inconsistent. The labels are often self-reported by creators, which means the most deceptive accounts have no reason to use them. Detection systems trained to spot the first generation of AI influencers fail against newer, more sophisticated models that generate photorealistic faces, write natural captions, and mimic genuine interaction patterns.
The economics behind it
The business case for AI influencers is straightforward. A human influencer requires payment, travel, production costs, and management. An AI influencer requires a one-time model creation and ongoing compute for generation. The margins are extraordinary, and the barrier to entry is falling.
Professor EP’s course on creating AI influencers is one of many. The infrastructure for synthetic content creation has matured to the point where individuals, not just studios, can spin up convincing personas. The result is a marketplace where real engagement metrics are increasingly untethered from real people.
What it means
Brand partnerships with AI social accounts are down 30% compared to 2024, according to Business Insider, suggesting that the advertising industry is becoming wary of the reputational risk. But the supply of synthetic content continues to grow faster than the demand for it declines.
The problem is not just that AI influencers exist. It is that they have become indistinguishable from the baseline noise of social media. Platforms built to connect people now host millions of accounts that simulate connection. The technical question of how to detect them is becoming a philosophical one: if an AI influencer generates real engagement, does it matter that the account is not a person?
Sources: The Verge (June 7, 2026); Business Insider (March 20, 2026); TIME (2026)