AI Labels Flag the Tool, Not the Lie: Why Ad Disclosures Fall Short

In October 2025, three AI-generated clips of police detaining and pepper-spraying protesters drew millions of views across X, Instagram and TikTok. The videos, built with OpenAI's Sora, carried visible watermarks. Users still cited them as evidence the events happened, according to NewsGuard. That result frames a hard problem for advertisers: synthetic content now functions as visual proof, not merely decoration.

Sourin Chakrabarti, who works on AI labeling for advertising at Meta and writes in a personal capacity for AdExchanger, argues that current disclosure systems flag the production tool rather than the illusion. His analysis lands as AI ad generation reaches industrial scale.

What did the fake NHS ad reveal?

Full Fact investigated a campaign showing a supposed doctor, claiming affiliation with Guy's and St Thomas' NHS Foundation Trust, testing a weight-loss patch and appearing to grow thinner on camera. The trust called the posts "completely fraudulent." Google's Gemini detected SynthID watermarks confirming AI involvement.

The watermark only proved AI was used. It could not say whether only the doctor's face was synthetic, or whether the medical authority, hospital connection, personal experience and physical transformation were all invented. Chakrabarti writes that a generic label tells consumers AI built an ad but leaves them guessing where reality ends.

The pattern repeats. In 2025, the Australian Medical Association warned that deepfakes impersonating prominent doctors promoted unproven products; clinicians discovered the fraud only when patients asked whether to swap prescribed treatments for advertised cures. In 2026, Chinese regulators launched an enforcement campaign against businesses mass-producing fabricated consumer-experience posts.

The legal principle predates generative AI. In FTC v. Colgate-Palmolive Co., a shaving cream commercial used a plexiglass prop in place of real sandpaper, and viewers were misled because the simulation was presented as a genuine test. Chakrabarti draws the operative line: does an ad merely illustrate a claim, or does it ask viewers to treat a synthetic scene as real-world proof?

How big is the disclosure gap?

Scale is the pressure point. In 2025, advertisers created three times as many Gemini-generated assets on Google as in 2024, including nearly 70 million in the final quarter alone. Meta has reportedly aimed to automate ad creation and targeting with AI by the end of 2026. Because these tools sit inside ad-creation systems, safeguards cannot rely on after-the-fact consumer complaints across millions of ads.

Existing labels do not distinguish severity. Google shows "How this ad was made" panels, Meta attaches "AI info" labels and TikTok offers "AIGC" self-disclosure controls. The EU's Article 50 rules require transparency for synthetic media, China mandates explicit AI markers and New York requires ads to identify synthetic performers. Yet the same label can appear on an ad with a decorative AI background and one with a fully fabricated testimonial.

What would a risk-based system change?

Chakrabarti, building on the IAB's January 2026 disclosure framework, proposes three tiers:

• Routine editing: basic edits and decorative backgrounds receive no additional warning.
• Lawful simulations: synthetic media that could be mistaken for real evidence must state what it represents, such as an "AI reenactment of a verified customer testimonial."
• Outright rejection: fabricated endorsements, invented expert opinions and unsupported results are blocked, mirroring FTC guidance that permits AI avatars but prohibits fake testimonials attributed to them.

Platforms could implement this by requiring advertisers to disclose the role of any AI-created person or scene, whether generated material depicts product performance, and what real-world evidence supports the claim. Meta, Google and TikTok already accept advertiser declarations, so the questions fit existing workflows. Chakrabarti also urges platforms to retain records of advertiser answers and consumer-facing notices, an auditable trail some in the industry call a served disclosure receipt.

The Advertising Standards Council of India's 2026 draft guidance already identifies fabricated experts, endorsements and exaggerated results as high-risk uses that labeling alone cannot fix. TikTok Shop prohibits AI-generated professional identities selling health products and alterations that misrepresent performance.

Under such a system, the weight-loss patch ad would fail: the advertiser would have to identify the doctor as synthetic, classify the transformation as a performance claim and substantiate it. The goal, Chakrabarti writes, is labels answering the question consumers actually face: not whether AI made the ad, but whether AI made up the reason to buy.