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Study finds that AI labelling does not hurt video ad performance

By our African Marketing Confederation News Team | 2026

As regulatory pressure around using AI in video advertising grows, researchers examine how labelling requirements may impact ad performance.

Control room with a wall of video screens displaying a Mediascience logo and live feeds, plus three desk monitors showing the same logo.

Photo: MediaScience

A new study has found that labelling a video advertisement as AI-generated does not hurt how it performs. The results showed no decline in any performance measure and an increase in AI-creation awareness across all four labelling conditions tested. For well-made ads, disclosure is not the threat the industry assumed it was. 

 

This is according to research from MediaScience, an industry leader in media and advertising innovation research, in collaboration with the Ehrenberg-Bass Institute for Marketing Science at Adelaide University in Australia. 

 

The regulatory pressure around AI in video advertising is intensifying. In the United States, New York’s ‘AI Transparency in Advertising’ law takes effect June 2026. Similarly, in the European Union, the ‘EU AI Act’ introduces binding disclosure obligations in August 2026.  

 

But, until now, brands faced having to navigate compliance without understanding how labelling requirements will impact ad performance. 

 

The MediaScience-Ehrenberg-Bass Institute study tested four labelling approaches across 900 respondents, reflecting frameworks under consideration by US and EU legislators: a text label in the first three seconds of the ad, a delayed text label from seconds four through to six, a full-duration text label and a full-duration icon. Each was tested against a control with no labelling. 

 

No adverse change in advertising performance 

 

Research data shows no adverse change in advertising performance across any of the labelling conditions. Brand choice, ad memory, brand recognition, brand attitude, ad liking, and perceived production quality all showed no significant difference from the no-label control. 

 

“There has been a lot of anxiety in the industry about what happens when you tell people an ad was made with AI,” says Dr Duane Varan, CEO of MediaScience. “The data gives us a clear answer: if the creative is good, disclosure does not hurt it. Advertisers do not need to be afraid of the label.” 

 

Displaying a disclaimer during the first three seconds increased viewers’ awareness that the content was AI-generated by 28%. Running the label continuously throughout the ad increased awareness by 36%. 

 

While 42% of respondents preferred the visual icon, it was the least effective at increasing AI awareness. On ad memory, text labels outperformed the control score of 36 across all conditions: 46 for the 3-second label, 40 for the delayed label, and 49 for full-duration. The icon scored 38, near the control. 

 

The study also found that audiences feel the strongest need for AI labelling when it generates humans (60%), followed by animals (46%), product placement (45%), and voices (45%).

author avatar
Jason Lottering