Consumer goods companies are increasingly turning to artificial intelligence to shorten product development cycles, generate novel formulations and respond to supply-chain weaknesses, executives told attendees at a recent industry summit.
French cosmetics group L'Oreal, which began integrating AI into laboratory work four years ago, said the technology enabled it to identify molecules used in skincare and redeploy them in haircare. Fabrice Megarbane, president of L'Oreal's consumer products unit, said the firm has been able to design products roughly four times faster than before as a result.
Megarbane highlighted a recent example in which molecules previously applied in skincare were adapted into a shampoo formula that uses collagen to add lift and fullness to hair. "You can really go much faster by imagining ... new associations of molecules and new benefits of molecules," he said at the Consumer Goods Forum's Global Summit in Vienna in late June.
The move to embed AI into formulation and testing comes as consumer companies face pressure to speed innovation and reduce costs against a backdrop of changing consumer preferences. L'Oreal's push follows its chief executive's launch of a "beauty stimulus plan" last year after the group recorded its slowest sales growth in years.
Executives at food and household product manufacturers report similar gains. Mondelez, the owner of Cadbury and Toblerone, described human product development augmented by AI as a "game-changer." Filippo Catalano, the company's chief information and digital officer, said AI has helped the company accelerate processes and rethink recipes.
Mondelez uses tools that can produce novel recipe ideas for human evaluation, reduce the number of physical samples generated in innovation, and adapt formulations to shifting consumer tastes or sourcing constraints. The company said its AI-assisted work contributed to products such as Gluten Free Golden Oreo cookies and a refreshed Chips Ahoy recipe. In the biscuit category, Mondelez reported that 60% of recipes produced using its AI tool performed better on metrics including nutrition, sustainability and cost.
Catalano framed AI's role as both a productivity and risk-management lever, noting potential to reduce reliance on single sources of supply by enabling formula adjustments that account for ingredient availability. "You can optimise how you develop your recipes," he said, adding that AI is "accelerating things you could do already, but compressing the time from months to weeks or years to months."
Other consumer companies, including owners of well-known food and oral-care brands, are deploying AI to speed ingredient testing, generate recipe ideas and address supply-chain vulnerabilities, executives said. The collective push reflects a broader industry imperative to do more innovation with fewer resources and to respond faster to evolving consumer demand.
Summary
Major consumer goods firms report measurable time savings and improved formulation outcomes from AI tools, ranging from molecule repurposing in cosmetics to AI-assisted recipe development in packaged foods. Companies say the technology helps compress timelines, cut sample volumes and provides flexibility to adjust formulas amid sourcing challenges.
Key points
- L'Oreal has applied AI in its labs for four years and says it can now create products roughly four times faster by repurposing molecules across skincare and haircare.
- Mondelez reports AI-assisted recipe generation has lowered sample counts, aided development of products like Gluten Free Golden Oreo and a Chips Ahoy refresh, and delivered better performance on nutrition, sustainability and cost for about 60% of AI-generated biscuit recipes.
- Other consumer firms are using AI to accelerate ingredient testing, spark new recipe ideas and reduce supply-chain single-source dependencies.
Risks and uncertainties
- Pressure to innovate faster and reduce costs - Consumer goods and retail sectors face an operational imperative to compress development timelines while managing margins.
- Shifting consumer tastes - Rapid changes in preferences create uncertainty for product development and product-market fit in consumer-facing categories.
- Supply-chain vulnerabilities - Dependence on single sourcing remains a risk for manufacturers; AI is being applied to mitigate this, but the underlying exposure persists in procurement and manufacturing operations.