For more than a century, beauty has been built on chemistry, the controlled mix of ingredients that make a product safe, stable, and pleasant to use. That hasn’t changed. What’s changed is what sits around it. The modern beauty company now builds and tests those formulations using new digital models, bio-testing methods, and engineered devices that have become common only recently.
That integration showed up clearly recently, when Fortune named L’Oréal the most innovative company in Europe in its first regional ranking, with Unilever close behind in second place. In the American version of the same list, the top positions are occupied, predictably, by technology manufacturers such as Apple, Nvidia, and Microsoft. Europe’s list looks different. Here, beauty and personal-care companies are applying the same digital methods those firms use to design hardware and software, modelling, simulation, and real-time data analysis now sit alongside traditional formulation work.
The recognition hasn’t been isolated, earlier in the year, IMD’s Future Readiness in the Era of Adaptability report ranked L’Oréal as the world’s most future-ready consumer packaged goods company, citing its use of AI and analytics to speed product development and its long-term R&D investment (Unilever placed third). And in October, TIME named three of L’Oréal’s developments among its Best Inventions of 2025: the AirLight Pro hair dryer, built with startup Zuvi, the Lancôme Nano Resurfacer, a handheld skincare device, and Melasyl, a molecule for treating localised pigmentation. Between them, they cover hardware, device software and chemistry: a hair dryer built on infrared-control design, a skincare tool modelled on medical-device workflows, and a molecule advanced through computational screening.
It’s an impressive list of accolades but then the structure behind those results is equally impressive. L’Oréal operates more than twenty research sites and employs over 4,000 scientists and engineers. Its €160 million Research and Innovation Center in Clark, New Jersey (its largest outside France) completed this year, houses labs for biochemistry, material testing, and computational modelling. The company’s filings show revenue rising from about €41.2 billion in 2023 to €43.5 billion in 2024, with an operating margin of 20 percent. Company leadership attributes the performance to the group’s balanced model, science-driven innovation, and ongoing Beauty Tech transformation.
All of which is to say the company now develops products in a far broader way than it did in the 1990s. Chemistry’s still central, it always will be, but optics, materials science, and micro-engineering sit beside it. AirLight Pro was co-developed with Zuvi, whose engineers came from drone design. The Nano Resurfacer uses surface-modelling techniques borrowed from medical-device manufacturing. L’Oréal formalises this kind of partnership under its open-innovation programme, designed to pull external technology into its own pipeline.
Other large beauty groups are doing similar. Estée Lauder and Microsoft have an AI Innovation Lab using Azure OpenAI and Copilot tools, Shiseido’s VOYAGER platform combines AI-based formulation functions and a large internal dataset, and Ulta Beauty’s data platform connects to its app, loyalty, and store systems to forecast repeat purchases, a system it says supports a 95 percent repurchase rate.
Taken together, they show how the cosmetics lab itself has changed shape. For years, most digital investment gravitated to marketing and e-commerce. In leading groups today, some of that investment is moving inside the scientific and industrial process. Formulators use simulation tools to model ingredient behaviour before lab testing. Manufacturing teams use sensors to monitor batch consistency in real time. Sustainability teams extract carbon data directly from production databases. In those settings, R&D uses modelling and monitoring tools more common in tech, even though the final product remains cosmetics.
Those systems create new tasks and record keeping requirements. Every connected device or diagnostic tool collects data that must be stored and governed under privacy law. Product testing now generates digital as well as chemical documentation, which has to match national and EU rules. The EU’s forthcoming Digital Product Passport regime under the Ecodesign for Sustainable Products Regulation will rely on similar product-level data systems.
Talent and supply chains are adapting too, large groups are hiring machine-learning specialists, materials engineers, and computational biologists alongside formulators. Hardware suppliers once focused on consumer electronics are now building for personal-care devices. The distinction between a wellness gadget and a beauty gadget is mostly branding, but it’s widened the circle of who gets to build beauty tech in the first place.
Across the board, R&D budgets are rising. L’Oréal puts around €1 billion a year into its labs (roughly 3.5 percent of revenue) and its competitors are moving in the same direction, putting more budget behind data systems, simulation, and devices. The goal isn’t to turn beauty into tech, The aim is to make design work faster and easier to track, because efficiency matters more when growth levels off.
That slowdown is already visible in McKinsey’s State of Fashion: Beauty 2025 report. It estimates the global beauty market at roughly $580 billion in 2024, up from about $525 billion in 2023, a strong year, but not one likely to repeat. Growth is expected to ease to around four to five percent a year through 2027 as input costs, competition, and marketing spend continue to climb. In that environment, McKinsey notes, efficiency becomes the growth strategy: predictive demand planning, AI-assisted formulation, and digital-twin manufacturing are all likely to help hold margins steady even as expansion slows.
That environment also changes what “innovation” means. In years gone by, the word usually meant a new serum or hero product. Now it describes the systems that keep those launches moving. The creativity’s still there, but it’s wrapped in process.
So when Fortune put a cosmetics company at the top of its innovation list, it wasn’t praising a breakthrough product. It was recognising how the company runs. The ranking looks at hard data, how much firms invest in R&D, how deeply technology sits in their operations, and how clearly those investments show up in performance. That’s why companies like L’Oréal and Unilever score well. They’ve built the same kind of disciplined, system-driven structures you’d expect from hardware manufacturers or software firms, only applied to beauty and personal products.
In practice, that looks plain. Labs pair chemists with data scientists while production lines feed quality and sustainability data directly into governance systems. Work moves more easily between internal teams and external partners. None of it looks dramatic, but it all adds up. The tools have multiplied, the methods have expanded, and the results are starting to show up in rankings that used to belong only to tech – to the extent that now beauty technology has a clear runway ahead of it, and one with extensive sky to explore.
