Artificial intelligence is no longer just a tool for making advertising faster or cheaper at L'Oréal. It is becoming the layer through which consumers discover, evaluate, and choose beauty products, and the French cosmetics giant is restructuring its marketing operations to keep pace.
Asmita Dubey, L'Oréal Group's chief digital and marketing officer, said the company's AI strategy rests on three pillars: helping employees work with AI, embedding the technology across business functions including marketing, research, and operations, and understanding how AI is changing the consumer journey. That third pillar carries the most significant implications for how the company reaches buyers.
Dubey said the consumer journey is not collapsing under AI, as some early observers predicted. It is expanding. A search that once took a few minutes now stretches to 11 minutes as users chat with AI systems, she said, raising new questions about how brands create credible content that can become part of an AI-generated answer rather than simply ranking near the top of a traditional results list.
L'Oréal has been testing advertising in Google's AI Overviews and working with platforms including OpenAI, Amazon, and Alibaba to explore how its beauty products can be found through AI search. Dubey framed the shift simply: more than a billion consumers are using AI to ask questions about their lives, from birthdays and parties to travel and beauty, and that is why the company needs to be present in those systems.
The infrastructure underneath marketing is changing as well. Dubey described an ecosystem being reshaped across publishers, platforms, creative, media, data, and technology agencies. The software layer that marketers spent the past decade building around customer relationship management, websites, and other platforms is also in flux.
At L'Oréal, technology is becoming a larger part of the marketer's job. The company has consolidated its beauty research into an internal intelligence platform that allows employees to interrogate a large body of existing research conversationally. Product development and formulation are becoming more data-driven, while image, text, and video creation are changing as generative AI tools spread.
Dubey said almost 20 percent of L'Oréal's marketing investments are now AI-led, and return-on-investment measurement already relies heavily on machine learning and AI. She described the result as a «dual muscle of creativity and technology,» where the two sides meet in what she calls an «aha» moment.
Getting there requires marketers to learn a less glamorous side of AI. Dubey said they must understand the architecture behind the systems, because L'Oréal works with hundreds of agencies and their tools. She said marketers need to be empowered to ask where the pipes are and whether the plumbing is right.
For L'Oréal, that plumbing includes standardizing advertising accounts and product data across platforms such as Google and Meta. It also means paying close attention to product information, something marketers first encountered with e-commerce and product detail pages, as consumer discovery moves from traditional search toward generative AI.
The next layer is generative-engine optimization, or GEO. This involves thinking about authority, scientific content, brand content, and product information, and how these can be structured so AI systems can understand them.
Dubey argued that the more technology enters marketing, the more important it becomes to get the fundamentals right. She offered a simple example: a universal commerce protocol might make 100,000 stock-keeping units available to an AI system, but that does not tell the system what a brand should be famous for. A sunscreen can be described as SPF 50, but it can also be described through the context in which someone might actually use it.
Ultimately, Dubey said, marketing remains about fulfilling a consumer need and creating a deep connection with the people who buy the products. AI changes the systems and the speed, but not that underlying purpose.