Today, Unilever’s Beauty & Wellbeing business – covering hair care, skin care and wellbeing with brands like Dove, Vaseline, Dermalogica and Nutrafol – represents one-quarter of the company’s entire annual turnover, generating EUR 12.8 billion in 2025. And it’s a business arm the company is future-proofing.
Scientists at Unilever Beauty & Wellbeing are using AI, automation and machine learning to speed up innovation processes “beyond anything previously possible”, cutting formulation cycles down from five or six days to one or two, reducing concept-to-brief timelines to mere days, and speeding up claims generation by 75%, according to the company.
Discovery, collaboration and innovation
And AI-driven product innovation at Unilever Beauty & Wellbeing is already hitting shelves. Pond’s Skin Institute Hydra Miracle range, for example, features Unilever’s Cera-Hyamino technology which was developed using various AI-led digital tools to mine 30 terabytes of microbiome data and identify ideal ingredient combinations. Dove’s Damage Therapy range is also backed by a flurry of patents that centre on the analysis of more than 100,000 data points on hair properties, achieved using advanced measurement tools, robotics and AI.
“For our 4,500 researchers, AI isn’t just a time-saver; it’s changing how we discover, collaborate and innovate,” said Jason Harcup, chief R&D officer at Unilever Beauty & Wellbeing.
Speaking to Premium Beauty News, Harcup said AI has been part of Unilever’s toolbox for decades through machine-learning and advanced analytics but recent advances in generative AI and large language models have “significantly expanded what’s possible”.
“As our scientific and consumer datasets have grown, the challenge has shifted from collecting data for extracting meaningful insights from it. Today, AI plays a role across the entire innovation journey: from understanding emerging consumer needs to scientific discovery and product validation,” he said.
Consumers, science, product
Unilever is using AI to delve into consumer needs, wants and desires in realtime, tracking sentiment, buzz, engagement and search terms online 60% faster than before, Harcup explained. Unilever Beauty & Wellbeing analyses more than 1,000 external data sources across social media, search, retail and competitive activity every month. “This always-on intelligence feeds directly into the product development process, allowing Unilever’s R&D teams to act on trends quickly.”
A good example of this working, he said, is the recent launch of Vaseline Originals featuring new ready-to-use formats of its flagship brand. The campaign launched two products on TikTok Live: the Vaseline Brow Tamer and Vaseline All-in-One Primer & Highlighter Jelly; products that tap into “enduring beauty rituals emerging across digital communities”, the executive said.
AI is also helping Unilever scientists access, connect and analyse large volumes of scientific data to back innovations, claims and new product positioning. Unilever’s own AI-powered agent, for example, can connect more than 150,000 scientific documents from decades of research and its AI-created virtual cohorts use existing microbiome datasets to analyse around 2,500 subjects simultaneously.
The aim here isn’t to replace real-world testing but instead access and explore vast amounts of data, faster. The automation of repetitive tasks and use of powerful tools and modelling is also leading to new discoveries and faster, precise product and formulation designs.
Importantly, Harcup said working with AI frees up Unilever scientists to focus more on creative work that holds more impact. Human expertise, he said, remains non-negotiable for Unilever Beauty & Wellbeing as it onboards more AI tools and technologies.
Human oversight and expertise
The company has trained more than 40,000 employees globally through AI learning programmes, functional training and hands-on workshops to ensure teams can use these tools “responsibly and effectively”, the executive said.
“We are committed to the responsible and ethical use of AI and have clear responsible AI principles in place, maintaining human oversight and accountability, and ensuring scientific expertise remains at the centre of decision-making.”
Use of virtual cohorts, for example, will always be overseen by in-house scientists and remains “complementary to real-world testing”, he said. These virtual cohorts offer scale and speed, helping Unilever Beauty & Wellbeing scientists understand potential outcomes earlier in the development process, but real-world testing and human validation remain critically important and essential in bringing products to market.
Looking ahead, Harcup said Unilever Beauty & Wellbeing will continue embedding AI across its innovation ecosystem but will also invest in future areas of “significant potential”, such as predictive science, digital twins, agentic AI and more personalised consumer experiences.
The real opportunities, he said, sit “at the intersection” of understanding realtime consumer needs and mapping scientific data. “Consumer insights are at the heart of everything we do, while science allows us to translate those insights into superior-performing products. AI helps connect those two worlds by bringing together external consumer signals, proprietary research and scientific data to identify unmet needs and guide formulation, claims and product design with greater precision.”
