What happened
L’Oréal is overhauling its marketing architecture to make AI a core driver of insight, content creation, targeting and measurement, according to an interview with chief digital and marketing officer Asmita Dubey.
In a Fortune interview dated Oct. 6, 2026, Asmita Dubey described L’Oréal’s three‑pillar AI strategy: upskilling employees, AI for efficiency across functions, and mapping AI’s impact on the consumer journey. The group is testing advertising in Google’s AI Overviews and collaborating with OpenAI, Amazon and Alibaba to surface beauty products in AI‑driven search results.
Dubey said roughly 20% of L’Oréal’s marketing budget is now allocated to AI‑led initiatives. The company has built an internal intelligence platform that lets employees query its extensive beauty‑research database conversationally, making product development more data‑driven. tools are increasingly used for image, text and video creation.
The firm is also standardising advertising accounts and product data across major platforms, and developing a “generative‑engine optimisation” (GEO) framework to ensure product information is structured for AI consumption. Dubey highlighted a hands‑on experiment where senior executives created an ad end‑to‑end using AI to build internal familiarity.
Why it matters
The shift shows how a major consumer‑goods company is moving from using AI as a peripheral tool to making it central to brand‑consumer interaction, a model other marketers may emulate as AI‑mediated search and generative content become mainstream.
L’Oréal’s approach illustrates a broader industry trend where AI is no longer a cost‑saving add‑on but a strategic layer that reshapes how brands are discovered and evaluated. By moving the consumer journey into AI‑mediated spaces, the company must ensure credibility and authority in AI‑generated answers, a challenge that could affect brand trust across sectors.
The reported 20% AI‑led spend signals a measurable commitment that may influence budgeting norms for other large advertisers. The internal conversational research platform could accelerate product innovation cycles, giving L’Oréal a competitive edge in a fast‑moving beauty market.
Dubey’s emphasis on architecture, data plumbing and GEO underscores that successful AI adoption requires robust infrastructure, not just tools. This highlights a potential barrier for firms lacking integrated data ecosystems, pointing to a market for AI‑ready marketing platforms.
Interactive Mechanism: How It Actually Works
Explore the underlying technology behind this development interactively.
crm_get_transaction(id='4092').Which component of an AI application is the machine-learning model itself?
What to watch next
Watch for L’Oréal’s rollout of AI‑generated ads on platforms like Google’s AI Overviews, the scaling of its internal conversational research platform, and how the company measures ROI on AI‑led spend.
The performance of L’Oréal’s ads in Google’s AI Overviews will provide early data on the effectiveness of AI‑mediated ad placements versus traditional search listings.
Scaling of the internal intelligence platform may lead to new AI‑driven product concepts or faster time‑to‑market for formulations, which could be reported in future earnings calls.
L’Oréal’s internal training experiments could be expanded company‑wide; monitoring how quickly executives adopt AI tools will indicate the pace of cultural change within large enterprises.