Artificial intelligence
Customer & Marketing
The transformation described in the previous articles can only succeed if the teams (management, bookers, lawyers, creatives) master the issues and the tools. In Palmer IA’s study on luxury personalization, it is recalled that 70% of luxury consumers say they are more loyal to brands offering advanced personalization, and that brands investing in AI and immersion increase their personalized revenues by 20%. Another publication points out that multimodal AI makes it possible to cross text, image and sound for richer experiences. To exploit these opportunities while controlling the risks (legal, reputational), teams need to be trained.
This module introduces the basics: what is generative AI? How does a multimodal model work? Participants discover that AI can answer a question about a photo, generate an image from text or summarize a video. The module addresses the difference between predictive AI (analytical models) and creative AI (text, image and audio generators). The role of data, bias and security is discussed.
Participants analyze real-life cases:
Fashion: digital twins for H&M, AI retouching for Zalando, virtual catalogs.
Cosmetics: skin analysis applications and fitting chatbots (over 2,000 possible combinations).
Perfumes: immersive campaigns combining text, music and generated images.
Watchmaking: photorealistic 3D rendering of movements; dial customization.
Jewelry: online configuration of rings and necklaces via avatars.
We discuss the economic impact (cost reduction of up to 70%) and customer perception (importance of authenticity).
This module details the FWA (New York): separate consent requirements for clones, commission and duration limits; California laws prohibiting unfair clauses; the European AI Act and its transparency obligations. Lawyers learn how to draft the clauses described in article 2, and how to incorporate transparency obligations into contracts.
Bookers can familiarize themselves with the pricing models proposed in article 3. Simulations show how to set a creation fee, calculate a royalty per image generated or negotiate a revenue-sharing clause. Case studies confront participants with perfume or watch brands seeking a global buy-out. The effects of cost reductions (up to 70%) on talent remuneration and perceived value are discussed.
This module explores red lines and tricky scenarios. Teams learn how to detect risks: misleading deepfakes, reinforced stereotypes, cultural appropriation. The example of the Valentino campaign criticized for the aesthetics it generated is discussed. Participants develop responses to fictitious crises and build a discourse of transparency. We discuss diversity: how AI can amplify representation (variations in morphology, skin color) and how to avoid standardizing faces.
The final module is aimed at executives and project managers. It describes how to set up an ethics committee (article 4), document prompts, audit suppliers and publish transparency reports. We encourage the creation of an internal lab, like Palmer IA’s “AI Lab”, which structures strategic, financial and digital use cases. This lab supports the implementation of pilots (recommendation agents, data analysis) and monitors legislation and innovations. Managers learn how to align AI strategy with the luxury house’s culture, and how to finance projects by assessing their return on investment.
AI transformation isn’t just about tools: it’s also about people and ethics. Training teams, implementing processes and adopting clear scales will help preserve the creativity and value of luxury. Market figures show immense potential (up to $275 billion in additional profits), but also legal and reputational risks. By accompanying its customers through this transition, Elite can become a benchmark player. The five articles in this report constitute a roadmap: it’s up to Elite to use them as a lever for its strategy, for the benefit of the talents and companies that place their trust in us.