Introduction

The cosmetics and dermatology sectors are entering a new phase where science, transparency and innovation must coexist in how results are communicated.
While AI imagery has unlocked new creative opportunities, it still operates as a black box, meaning the way it interprets or generates data cannot always be traced. This opacity raises legitimate concerns when the goal is to communicate clinically validated results with full scientific rigor.

By contrast, 3D visualization provides complete traceability throughout the process. At Aetherma, every image is directly derived from real clinical data, such as instrument readings, dermatologist scoring, segmentation and masking of cutaneous areas, and each step (from raw data to final render) can be audited. This ensures that what is seen corresponds precisely to what has been measured, which both protects scientific integrity and fosters consumer trust.

We are also aware that consumers may initially react with caution toward visuals that do not feature “real people”. However, this is precisely where education and context play a key role. By explaining that 3D images are scientific visualizations of real measured results, brands can shift potential skepticism into curiosity and understanding. It becomes an opportunity to educate consumers about skin health, clinical rigour and responsible innovation, clarifying that the image isn’t “fake”, but faithfully data-based, anonymised and controlled.

The Role of AI in the Future

While we emphasise the power of 3D visualization today, we recognise that AI will be a fundamental pillar of the next generation of tools in our field:

• Data evaluation: AI algorithms can help analyse large volumes of clinical and imaging data, identify subtle patterns or correlations, and expedite insights that would otherwise take lengthy manual review.
  
  
  

• Predictive modelling: AI can assist in forecasting skin-condition progression, simulate outcomes under different protocols, and thereby optimise the workflow for 3D visualization and study design.
  
  
  

• Pipeline optimisation: AI can streamline pre-processing of images (e.g., automatic segmentation, mask creation, anomaly detection) thereby reducing turnaround time and refining cost-efficiency of clinically-driven visuals.
  
  
  

Rather than replacing 3D, AI becomes the “engine” behind the scenes, AI for insight, 3D for proof. In practice, it means the brand uses AI to extract robust parameters and refine processes, and then uses traceable 3D renderings to communicate those parameters in a transparent, brand-safe way.

Regulatory & Compliance Outlook

The legal/regulatory environment is moving rapidly and will materially influence how visuals (whether AI-generated, 3D, or hybrid) can be used in consumer-facing communications:

• In the European Union, the EU Artificial Intelligence Act (“AI Act”) came into force on 1 August 2024. Wikipédia+2White & Case+2
  
  
  

• Many provisions will apply in stages: for example, transparency obligations for AI-generated content, including deepfakes, will apply from August 2, 2026. wilmerhale.com+1
  
  
  

• The Act defines obligations for “providers” and “deployers” of AI systems, including for image, audio or video content that could falsely appear authentic (i.e., deepfakes). Passle+1
  
  
  

• Specifically for advertising and marketing: The Advertising Standards Authority (UK) advises that if AI is used in an ad in a way that consumers might not recognise, transparency and disclosure are required. asa.org.uk
  
  
  

• While most cosmetic communications may not (yet) fall into the highest-risk AI category, the direction is clear: brands using generative or synthetic visuals will increasingly need to demonstrate traceability, transparency and consumer safeguarding. www.personalcareinsights.com+1
  
  
  

Practical Implications & Timeline for Cosmetics Communications

• Now (2024-2025): Brands should adopt best practices around how visuals are derived from data, ensure the chain of processing is documented, and prepare for increased scrutiny around synthetic content.
  
  
  

• Mid-term (2025-2026): The transition period for key transparency provisions under the AI Act means regulatory enforcement grows — by August 2026, marking or disclosing AI-generated content becomes more likely.
  
  
  

• Forward-looking (2027+): As standardised codes and norms emerge (watermarking, metadata tagging, clear consumer disclosure), brands that already rely on traceable 3D workflows will have a competitive advantage in credibility and compliance.
  
  
  

In sum, the future of clinical visualization will not pit 3D and AI against each other — it will integrate them intelligently.
AI for insight; 3D for proof; and consumer education for trust.