Editor’s Note: On a recent discussion forum, the topic of using Ai simulations as a marketing tool for showing consumers how they would look after using a specific skincare product caused a stir, and I was asked for an opinion which I present here as promised…
In the past, when we advertised cosmetic products, before-and-after photography was often key to sales success in the marketplace. At least, that is, until deceptive ‘airbrushing’ became more widely used, with much ‘chagrin’. Fast-forward to today, using ‘posh’ computer programmes, called generative Ai, to create before-and-after skincare simulations is now creeping into the marketing toolbox for promotion/advertising. However, it has both advantages and challenges, especially when considering those regulatory and advertising implications!
Here’s an overview:
The Advantages (sort of…)
1. Enhanced Visualisation – Generative Ai can provide a highly realistic simulation of how skin could improve after using a product. This can make marketing more engaging and personalised, helping consumers visualise potential results.
2. Personalised Results – Ai could generate results tailored to individual skin types, tones, and conditions. This level of personalisation could create more trust and relevance in marketing efforts (?!?).
3. Cost Efficiency – Ai-generated simulations might reduce the need for costly clinical trials or physical photoshoots of participants over extended study periods, saving time and resources.
4. Innovation and Engagement – Offering interactive tools where users can see projected results based on Ai analysis could boost engagement, attract tech-savvy consumers, and create a sense of innovation around the product.
However, these advantages, also become Disadvantages!
1. Accuracy and Ethical Concerns – Simulations never accurately represent realistic outcomes, leading to deceptive marketing practices. Ai models can easily exaggerate the effects or show idealised results that are not attainable by average users. For example if a simulation is developed from clinical study data, and that study is flawed or has very few participants with questionable results, then the Ai simulation would be ‘misleading’. A study of only 30 volunteers would not be considered representative of a given population especially if the significance of the data was questionable.
2. Consumer Mistrust – If consumers perceive the Ai-generated simulations as manipulated or unrealistic, it could erode trust in the brand. False advertising claims may lead to backlash if the results do not match real-world experiences.
3. Over-promising Results – Ai models may inadvertently exaggerate product effectiveness, leading to dissatisfaction or even legal challenges if the promises are not fulfilled.
4. Technological Bias – Ai systems may unintentionally reflect biases in skin tone, age, or gender, showing better results for certain demographic groups and excluding others, which could lead to ethical issues.
Regulatory and Advertising Authority Considerations
1. Truth in Advertising – Regulators such as the Federal Trade Commission (FTC) in the USA and Advertising Standards Authority (ASA) in the UK require that product claims, including skincare results, be truthful and substantiated by robust evidence. If Ai-generated simulations are seen as misleading or deceptive, they would be subject to legal action or regulatory penalties. For example, if the Ai overstates the product’s effectiveness or fails to accurately represent average user experiences, it could be considered a violation of advertising guidelines. The (US) Federal Trade Commission has recently ruled on the use of Ai generated images to promote product claims and referrals(1,2).
2. Substantiation of Claims — Authorities typically require that skincare claims be backed by clinical trials, user studies, or other scientific evidence. Ai simulations may need to be clearly labeled as “simulated” or “for illustrative purposes only” to avoid IMPLYING that the outcomes are guaranteed or scientifically proven. If a brand uses Ai simulations to make specific performance claims, it would need to demonstrate that these claims are supported by rigorous, real-world evidence, not just Ai-generated ‘moving’ images!
3. Transparency and Disclosure – Regulators would require clear disclosures that Ai was used in creating the images and that the results are simulations, not guaranteed outcomes. This ensures that consumers are not misled by the visuals! Advertisements using Ai simulations would need disclaimers stating that the images are not based on actual product results unless the company can prove a direct correlation between the Ai-generated result and real-world usage.
4. Potential Bans or Restrictions – Some advertising regulators may very well impose restrictions or even bans on the use of Ai-generated before-and-after images, especially if these simulations are found to be misleading or difficult for consumers to interpret accurately (as we have seen with the FTC).
Finally,
While generative Ai can realistic simulations as the next step to before-and-after photography, it also introduces significant risks related to misleading claims and consumer trust. Regulators and advertising authorities will scrutinise such practices to ensure they comply with truth-in-advertising standards, transparency, and substantiation of claims. Brands using Ai-generated simulations must tread carefully, clearly state that that the images are Ai generated and based on an “x” number of volunteers under “y and z conditions”, ensuring they do not exaggerate product benefits or mislead consumers.
In my opinion?
Stick to ‘reality’! Reality grounds you in authentic cosmetic product experiences, and that so-important meaningful human (consumer) connection, while AI simulations, though ‘fun’, can’t fully replicate the depth and unpredictability of real life cosmetic consumer behaviour and habits.
https://www.ftc.gov/business-guidance/blog/2023/02/keep-your-ai-claims-check
Theresa Callaghan
Theresa Callaghan, a PhD biochemist with over 35 years of experience in corporate skin care research, has held key R&D senior roles for companies including LVMH, Unilever, Marks & Spencer, J&J, Evonik, Hill-Top Research, and proDERM. In 2008, she created Callaghan Consulting International, focusing on cosmetic claims development with brands and ingredient suppliers. She is a widely published author, frequent speaker, and contributor to peer-reviewed journals. Her acclaimed book, 'Help! I'm Covered in Adjectives: Cosmetic Claims & The Consumer', is now in its second edition and translated. She is a member of the Society of Cosmetic Scientists (SCANCOS) and British Herbal Medicine Association. Theresa serves on the editorial peer review board of the International Journal of Cosmetic Science. She also mentors, and has her own Cosmetic Claims Insights Column with Euro Cosmetics.
