The challenge

AI is no longer futuristic. Around three in four organisations globally are now using it in some capacity. For the L’Oréal R&I team, the question wasn’t if, but how could AI be applied in a way that truly adds value to consumer science? Unlike purely digital research, this team’s work is inherently human: observing how real people use real products, how they feel about them and how these fit into daily life.

The challenge was clear: how to integrate AI without losing the richness of the human experience, ensuring insights remain tactile, emotional and actionable.

The solution

We manage several online research communities for L’Oréal R&I, supporting qualitative product evaluation. Together, we partnered on conducting a pilot to test a new workflow that integrates our proprietary AI-powered assistant. The process began with participants evaluating prototypes, benchmarking against competitors and sharing experiences through digital discussions, video diaries, surveys and mood boards. For this test, we focused on supercharging visual analysis of the mood boards, which generated hundreds of images uploaded by participants.

Manually reviewing this volume of data for themes and patterns usually takes days. Our AI tool accelerated the process, leveraging large language models in a secure, walled environment where client data never leaves the system. Using our proprietary ‘Visual Decoding Canvas’, we leveraged carefully curated prompts to guide AI analysis, detecting themes, gaps and even conducting semiotic analysis. The AI acted like a “smart co-researcher,” interpreting the data through multiple lenses – from a journalist to an R&D scientist – enhancing both speed and insight quality.

This approach allowed us to rapidly identify patterns, surface emotional drivers and gauge the strength of each theme. In practice, this revealed critical nuances: for example, while functional performance was comparable across products, AI uncovered that scent was a key emotional driver, shaping overall product preference. By making these hidden insights visible, the team could adjust launch priorities, R&D focus and marketing messaging with confidence.

The impact

The impact has been immediate and tangible. AI reduced analysis time from days to hours, freeing human analysts to focus on curating insights, building stories and strategic interpretation. At the same time, AI uncovered emotional nuances that might otherwise have been missed, driving sharper, more confident decision-making. Indeed, the launch of this test product has been highly successful as a direct result of the AI-supercharged learnings from our study.

This pilot proves that AI doesn’t replace human expertise, it amplifies it. By combining secure, AI-enabled tools with rigorous research and close collaboration, L’Oréal now has a repeatable approach to generate high-quality, actionable insights at speed.