Safety

AI-made videos used in dropshipping scam on Instagram and TikTok

Accounts with large followings on Instagram and TikTok have been posting AI-generated videos that portray teenagers being bullied for selling Christian-themed clothing, while linking to online shops.

AI-made videos used in dropshipping scam on Instagram and TikTok

Accounts with hundreds of thousands of followers on Instagram and TikTok have been sharing AI-generated videos that show teens being bullied for trying to sell Christian-themed clothing. The posts include links to online shops, appearing to use provocative, fabricated content to drive viewers toward purchases.

How the scheme works

The tactic appears to combine fake or synthetic accounts with AI-made videos to stoke outrage and direct traffic to dropshipping-style websites. The model relies on emotional engagement and viral spread: viewers disturbed or angered by the clips are more likely to click through to the linked storefronts.

Who is affected and what is known

Reportedly, many of the accounts involved have follower counts in the hundreds of thousands. It is not clear who operates those accounts, nor whether the products advertised are actually shipped to buyers. Some items on the linked sites also appear for sale on other online retailers, suggesting the listings may be copied or resold rather than unique inventory.

Transparency and disclosure issues

The videos do not include labels or disclosures required by Meta and TikTok for content that uses AI. This lack of clear disclosure makes it harder for users to recognize that the footage is synthetic or manipulated.

Responses and consequences

After Semafor contacted TikTok and Meta, several of the accounts mentioned in the report were no longer available online. The platforms were notified as part of the inquiry.

Why this matters

The case highlights risks at the intersection of more realistic AI-generated media and social media monetization: realistic synthetic video can be weaponized to provoke reactions and funnel sales, complicating efforts by users and platforms to distinguish genuine content from targeted manipulation.

Author: Rachyl Jones