The recent ASA decisions (16 September 2026) upheld complaints against ads for various AI image to video generators (or in one case, an AI companion generator app) which included examples of images of females being transformed into explicit “deepfake” sexual videos. Given the nature of the content, the decision that these were likely to cause serious or widespread offence is not surprising.
Of greater interest was the ASA’s findings that the ads also included gender stereotypes that were likely to cause harm, on the grounds that they suggested it was acceptable to objectify and stereotype women by presenting them as sexual objects. In light of the recent furore around the Novig/Sydney Sweeney marketing campaign and its perceived sexualisation of women’s sport as well, this serves as a timely reminder to marketers about the general need to avoid offensive stereotyping in their ads from a legal standpoint, as well as a moral and reputational one. This applies to gender stereotyping generally, not just sexual objectification, eg women shown as shopping or cleaning, or men as being responsible for DIY repairs or the primary breadwinner. However, the principle equally applies to other forms of stereotyping as well, for example those based on race or age.
In light of the ever-increasing use of generative AI to create advertising materials and campaigns, this issue is one that we may see re-occur more in future due to the risk of AI bias and potentially discriminatory outputs. Depending on the training data used by the relevant AI system, and the prompts provided by the marketer, there is a significant risk that content produced is based on what has gone before, and therefore reinforces traditional assumptions and biases – even if we thought or hoped these were on the way out. This can also create the risk of a vicious cycle, where further AI content is subsequently based at least in part on those generated ads, particularly where the latter is part of a successful (or at least highly publicised) campaign. In this particular context, where women have historically been portrayed in a more sexualised manner than men, AI-generated outputs may be more likely to continue to reproduce those depictions in the absence of specific prompting.
This is why the ASA has been keen to stress that marketers are responsible for any AI output featured in their ads. Ultimately it's for them to decide if an ad is compliant with advertising rules and regulations, not the AI. The issue of stereotypes and their potential to offend is one where there is often at least some degree of subjectivity; for example in the context being considered in this article there can at times be a thin line between images considered too sexually explicit to be compliant, and those that are acceptable, at least with the ASA. Indeed, readers may remember the regulator tying itself in knots over this point back in early 2024 in relation to various Calvin Klein adverts with FKA Twigs and Kendall Jenner – interestingly it also confirmed, with much less fuss, that similar images featuring Jeremy Allen White “would be unlikely to break our rules”. However, what is clear is that it will not be acceptable for the marketer to delegate the responsibility for such judgments to an AI system.
Of course, the potential for stereotyping isn't the only concern that marketers must consider when using generative AI. Other relevant issues include:
The extent to which the use of AI should be disclosed
The potential for AI to misrepresent the product/service being sold and/or to make misleading claims
The use of manipulated imagery
Potential IP infringement
In the context of gender stereotypes particularly, if the content is compliant under the Equality Act which protects people with protected characteristics of which gender is one
If you require advice or assistance with any of the issues highlighted in this article, please don’t hesitate to contact the Mills & Reeve advertising team.
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