Putting generative AI to one side, in what ways, specific to your area of expertise in the beauty industry, are you seeing AI being used? Can you share some AI success stories?

Beyond experimental or generic applications, the AI creating the most immediate value in cosmetic R&D today is AI that can be directly applied to accelerate research and innovation. Its strength lies in its ability to support formulators at the very start of the development process, where complexity, uncertainty, and time pressure are highest.

One of the most tangible impacts is guided formulation. By providing structured starting points rather than a blank page, AI helps R&D teams explore formulation pathways more efficiently. It enables teams to reduce trial-and-error, anticipate constraints earlier, and concentrate laboratory work on the most promising options. This shift significantly improves speed, resource allocation, and overall innovation efficiency.

AI also plays a critical role in knowledge capitalization and expertise retention. Years of formulation experience, often dispersed across teams, documents, and individuals can be transformed into structured and searchable knowledge. Best practices, formulation rules, and expert decision logic become reusable assets rather than forgotten data. AI-driven decision support can then align formulation choices with internal standards, regulatory requirements, and brand DNA. This capability is particularly valuable for global R&D organizations facing team turnover, where maintaining consistency and preserving expertise are constant challenges. AI helps retain, share, and scale expertise across the organization.

Which AI platforms, tools, or technologies do you feel are bringing the greatest benefits to your sector, particularly regarding speed, cost, innovation, or problem-solving?

The AI technologies delivering the greatest benefits to cosmetic R&D today are those that are natively embedded within PLM platforms built for the cosmetics industry. Rather than relying on standalone AI tools, the most impactful solutions operate directly on structured formulation, ingredient, and regulatory data already used by R&D teams in their daily workflows.

By leveraging raw formulation data and historical knowledge, they can instantly propose tailored base formulas, highlight potential risks, and guide decision-making early in the development process. This significantly reduces trial-and-error, shortens development cycles, and helps teams focus lab work on the most viable options.

AI platforms bring the greatest benefits when they are: domain-specific, built on expert-curated data and integrated into existing R&D workflows. In cosmetic R&D, AI succeeds when it accelerates innovation without compromising compliance, quality, or expertise.

What are your top three recommendations for companies in your sector considering AI and what should they absolutely avoid?

For companies in the cosmetics sector considering AI, the first and most critical recommendation is to start with data, not technology. AI cannot compensate for fragmented, poorly structured, or unvalidated information. Building a robust digital backbone where R&D, ingredient, regulatory, and supplier data are centralized, classified, contextualized, and traceable, is the true prerequisite for any successful AI initiative. Companies that rush into AI without this foundation risk accelerating errors rather than innovation.

The second recommendation is to adopt AI solutions that are domain-specific, explainable, and embedded within existing R&D workflows. In cosmetic development, AI must understand formulation logic, regulatory thresholds, and market-specific constraints. Black-box technologies or generic AI platforms may appear powerful, but without transparency and contextual intelligence, they reduce credibility and limit user adoption. AI should support expert decision-making by providing clear, justifiable insights, not obscure recommendations.

Finally, companies must ensure that human expertise remains at the center of all AI-driven processes. Trustworthy AI in cosmetic R&D is built on a human-in-the-loop approach, where formulators and regulatory experts remain full responsibility for decisions, validation, and accountability. Since AI holds no legal responsibility for products, it must be used to enhance expertise, accelerate learning, and reduce complexity, never to replace scientific judgment. Companies that use AI to support expert decision making will be the ones creating durable innovation and measurable value over time.