When folks take into consideration synthetic intelligence, they typically image glossy start-ups or futuristic labs. However what occurs when AI meets an organization that has been innovating for over 100 years?
Unilever is likely one of the world’s largest client items corporations, residence to manufacturers like Dove, Hellmann’s and Vaseline, with merchandise utilized by 3.4 billion folks day by day. And behind these on a regular basis gadgets is a deep and evolving dedication to science.
From cleaning soap and margarine within the early Twentieth century to at the moment’s breakthroughs in sustainable packaging and customized skincare, Analysis and Improvement (R&D) has all the time been our engine of progress. However now, that engine is being reworked by AI.
AI is not only a brand new software in our labs, it’s a new mind-set. And for an organization with a century’s value of scientific knowledge, that could be a game-changer.
AI is reshaping each trade, however the corporations that would be the most profitable are those that know adapt, study, and construct on what they already know. Whereas many legacy corporations are exploring modernize by means of AI, the actual alternative lies in how they harness their institutional reminiscence: the many years of analysis, product growth, and client insights that may typically sit untapped. This requires deep area experience, sturdy knowledge stewardship, and a tradition that values studying as a lot as legacy. When these components align, AI can grow to be a catalyst for transformation, by revealing the complete potential of what has come earlier than.
Unilever was born within the Victorian period, formed by the commercial and scientific revolutions. Over the many years, now we have developed by responding to cultural shifts; from the transformation of home life within the mid-Twentieth century to at the moment’s shifting expectations round pores and skin well being, magnificence, and wellbeing to the rising urgency of sustainability. When new supplies like Formica and stainless-steel turned widespread in mid-century kitchens, our scientists developed merchandise tailor-made to those surfaces. This was not simply chemistry, it was a scientific response to a altering lifestyle.
That very same mindset—science in service of actual life—nonetheless drives us at the moment. However the questions we’re asking have grow to be extra complicated: How will we help the pores and skin’s pure microbiome? How will we clear properties with out disrupting the ecosystems that dwell on our surfaces? How will we design merchandise which might be each efficient and sustainable? These usually are not easy issues, and so they require new methods of doing science. That’s the place AI is available in.
With machine studying, we will uncover patterns that may take human researchers lots of of years to detect. We’re utilizing AI to grasp how microbes work together with our merchandise, how pores and skin responds to environmental stressors, and the way we will personalize formulations for various wants and areas.
However here’s what makes our method distinctive—we aren’t ranging from scratch. Like many legacy corporations our R&D archives stretch again over 100 years. We’ve got information of each formulation, each trial, and each client perception. This historic depth offers our AI fashions one thing extremely uncommon: context. Whereas many corporations are simply starting to construct their knowledge units, established corporations like ours are standing on a basis that has been fastidiously constructed for generations.
Our scientists can unlock proprietary information that was as soon as siloed, scattered throughout groups, or locked in an archive. A century of skincare experience is now structured, searchable, and able to be utilized. We’re utilizing AI to attach the dots throughout many years of analysis, accelerating discovery in new supplies whereas concurrently optimising formulations for particular wants, like totally different pores and skin varieties. We’re shifting from analysis and discovery to formulation design and refinement in a single, built-in course of, serving to us reply quicker and extra exactly to folks’s wants world wide.
This isn’t about changing scientists with algorithms. It’s about creating the circumstances the place human expertise can thrive. Agentic AI methods give our groups the flexibility to ask higher questions, discover extra prospects, and unlock insights from our knowledge. By amplifying human creativity and empathy not automating it, we’re enabling our scientists to deal with what they do greatest: imagining, experimenting, and designing merchandise that meet actual human wants.
So why ought to this matter to anybody outdoors Unilever?
As a result of it reveals what is feasible when legacy meets studying. In an period the place AI is reshaping each trade, the businesses that thrive is not going to simply be the latest or the loudest, they would be the ones that know adapt, study, and construct on what they already know.
AI rewards knowledge maturity. It rewards curiosity. And it rewards corporations that see expertise not as a menace to custom, however as a method to reimagine it.
We shouldn’t have all of the solutions. However now we have discovered that staying curious, being a “learn-it-all” not a “know-it-all,” is what retains an organization related for a century. AI helps us keep curious at scale.
We imagine the following 100 years of innovation might be pushed by corporations that embrace the partnership between human expertise and agentic AI: hybrid methods that increase creativity, empathy, and scientific instinct. This isn’t only a story about expertise. It’s a story about legacy, studying, and the enduring energy of science to form the on a regular basis—solely now with a bit of assist from synthetic intelligence.
Alberto Prado is world head digital & partnerships at Unilever.
