Shampoo bottles, biscuit recipes, and skincare serums do not usually share a headline. Right now they do, because L’Oreal, Mondelez, and Nestle are all using AI product development to get new items onto shelves faster than their labs ever managed on their own.
How L’Oreal Cut Development Time by Four
L’Oreal has run AI in its laboratories for four years, and the payoff shows up in the numbers. A senior L’Oreal executive told Reuters the company can now build products four times faster than before, largely by using AI to map how molecules behave before anyone runs a physical test.
From Skincare to Shampoo
L’Oreal Consumer Products President Fabrice Megarbane said the technology has let the company predict how an ingredient will act on skin or hair long before lab work begins. One result is a collagen-based shampoo built from molecules that were originally developed for skincare products.
That reuse of existing research is the real trick. Instead of starting from zero for every new category, L’Oreal’s AI tools flag which molecules already sitting in its portfolio might work somewhere else entirely.
Mondelez and Nestle Apply the Same Logic to Food
Cosmetics is not the only industry doing this. Nestle and Mondelez are both leaning on AI for product innovation, using it to test ingredients faster, generate recipe ideas, and manage supply chain risk.
Recipes Built and Tested by Machine
Mondelez has gone furthest with generative recipe tools. The company said 60 percent of the recipes its AI system produced performed better on nutrition, sustainability, and cost than recipes built the traditional way. A Mondelez executive named Catalano noted the same tool helps the company lean less on single-source ingredients, since it can suggest formula swaps quickly when supply or pricing shifts. Food scientists and human tasters still sign off on every AI-generated recipe before it moves forward.
Nestle’s work leans more toward reformulation. The company plans to remove artificial food colorings from its products worldwide by the end of 2026. Getting there meant screening natural alternatives, running them through production tests, and checking shelf life, according to Chief Technology Officer Stefan Palzer. Nestle has also built a materials-discovery tool for packaging, pairing chemical language modeling with IBM Research’s regression transformer to link molecular structure to physical properties.
Why the Whole Industry Is Racing to Catch Up
Haleon, the maker of Sensodyne, signed a five-year AI partnership with Microsoft in June 2026 covering everything from consumer research to supply chain planning. Unilever is moving in a similar direction. None of this is really about replacing chemists or food scientists. It comes down to compressing timelines that used to run for years into a matter of months, so companies can react to shifting tastes and rising costs before a competitor beats them to it.
Conclusion: AI Is Becoming Standard Kit in Product Labs
L’Oreal’s fourfold speed gain and Mondelez’s 60 percent hit rate are early data points, not proof that AI can run product development on its own. Human teams still make the final call in every case reported so far. What has changed is how much ground those teams can cover before a product even reaches a lab bench. Companies still watching from the sidelines now have real numbers to weigh against the cost of staying manual.
Curious how AI is reshaping content strategy too? Check out our guide to AEO and GEO content optimization for more on where AI meets everyday business.
