Shampoo and cookies receive an AI upgrade as major consumer brands revamp their laboratories.

      The narrative around AI has primarily revolved around chips, data centers, and the companies developing the models. However, it is now being illustrated in the shampoo aisle. The world's leading manufacturers of everyday products—those responsible for the bottles and packets found in most kitchens and bathrooms—claim they are utilizing artificial intelligence to design items and manage the marketing strategies that promote them, effectively transforming a technology previously linked to software into a standard practice in consumer-goods laboratories.

      This trend mirrors the broader wave of corporate adoption that has integrated AI tools into business software systems, now extending to categories as seemingly unexciting as body wash and biscuits. Procter & Gamble provides a clear example of this transformation within research and development. The company states that it employed AI to evaluate tens of thousands of peptides while creating a formula for a Pantene product, utilizing an internal database of over 8,500 formulations to anticipate how a mixture would feel on skin or hair before any actual blending took place.

      The goal isn't simply novelty; it's about efficiency. Processes that once necessitated extensive physical testing can now be streamlined using computational methods, accelerating the path from idea to consumer trials. Mondelez, the parent company of many well-known biscuit and chocolate brands, mentions a similar transition in food product development. It reports that an AI tool has facilitated the creation of numerous new formulations and that this software allows developers to operate two to five times faster than traditional techniques.

      The same generative technologies are being applied to marketing as well, creating personalized images, texts, and videos at speeds that outpace conventional studios. Unilever has particularly embraced this aspect. Its Dove brand collaborated with Crumbl to launch a cookie-scented body-care line, with AI involvement throughout the process, from product design to influencer selection and creative development. The company noted that this campaign generated billions of impressions and attracted a significant number of new customers to the brand. Regardless of opinions on cookie-scented soap, the mechanics are revealing: a single AI-enhanced pipeline spans from formulation to delivery.

      What connects these case studies is the concept of compression. In the consumer goods sector, the traditional cost of experimentation is measured in months of laboratory work and test batches, while campaign costs are gauged in agency hours. AI addresses both these challenges. Reformulation turns into a search for known ingredients, and content can be generated and varied on demand, reflecting the advertising strategies showcased when OpenAI presented AI-generated ads at Cannes.

      However, caution should be exercised regarding these claims. Much of the specific data originates from the companies themselves, and consumer powerhouses have every incentive to portray their AI initiatives as more advanced than they actually are. Product development ultimately culminates in human tasting panels and dermatological evaluations, and a formula favored by an algorithm does not necessarily equate to one that consumers are willing to repurchase. Industry researchers have noted that AI-generated marketing often tends toward the generic, lacking the distinctive brand character needed for successful campaigns.

      Nevertheless, the trend remains consistent among companies that seldom see eye to eye. The redistribution of business budgets toward AI tools and agents has become a pervasive characteristic among large corporations, from Tencent’s enterprise agents to the consumer goods R&D highlighted here, and the packaged goods sector is also involved.

      For consumers, the tangible outcomes will be quite simple: an increase in product variants, faster updates, and scents and textures that emerge and disappear more swiftly than before. Although the products may appear unchanged on the shelves, the underlying processes are evolving significantly. A bottle of shampoo is increasingly the result of a search-based approach.