Why beauty brands rely on AI to power innovation and personalization

The use of AI in the beauty value chain is becoming increasingly common, both in consumer-facing offerings and behind the scenes in R&D. For formulators, AI helps deepen the science of ingredient innovation while speeding up the process. Meanwhile, the technology also lowers the barrier for consumers to try new products as choices are at an all-time high, and selecting the right one becomes more overwhelming. 

Anastasia Georgievskaya, CEO and co-founder at beauty tech company Haut.AI, tells Personal Care Insights that consumer demand for personalized beauty is a major driver in the shift to adopt AI.

“The entire industry today is centered around the promise of personalization. It’s a dominant narrative across marketing, product development, and digital experience, and AI is one of the key enablers behind it,” she says.

As a product development case study, K-beauty giant Amorepacific recently tapped the technology for the development of a novel peptide for hair care that promises to reinforce keratin. The company says AI enables it to analyze large-scale chemical and biological data to identify promising ingredient candidates for new formulations.

“Amorepacific views AI not simply as a tool for automation, but as a research partner that enhances both the depth and speed of scientific inquiry,” a spokesperson for Amorepacific’s R&I division tells us.

We sit down with the experts to discuss why and how incorporating AI across business divisions can benefit beauty brands in the years to come, as the industry undergoes a technological makeover.

Full-circle R&D

AI is transforming the way cosmetic companies approach ingredient discovery and cosmetic formulation. Amorepacific explains that it focuses on molecular-level scientific understanding to develop ingredients, and uses computational analysis to study how bioactive substances interact with skin and hair structures.

“AI supports […] the interpretation of complex biological interactions and the optimization of formulation strategies,” the spokesperson says. 

At the end of last month, the company unveiled research about the optimal hair peptide for hair keratin strengthening based on a data bank of approximately 8,000 compounds. Published in the International Journal of Cosmetic Science, the AI-powered findings identified Tripeptide-132 as the most optimal due to a superior binding affinity for hair keratin.

“Recent hair science research further demonstrates how computational simulation and molecular dynamics analyses are combined with experimental approaches to identify how specific peptides interact with hair keratin proteins, translating computation-based research directly into ingredient development,” the spokesperson highlights.

Amorepacific used AI to identify a peptide that binds strongly to hair keratin, helping support hair strengthening.The company’s AI-driven research initiatives are delivering tangible results across multiple areas beyond ingredient development, including testing.

“An AI-based automated skin irritation assessment technology trained on approximately 83,000 skin patch test images improves the efficiency of safety evaluation and global clinical research,” the R&I spokesperson explains.

After ingredient development and testing, Amorefacific uses AI to help it navigate cosmetic compliance, ensuring its products meet the requirements of each market it operates in.

“AI-driven systems support global regulatory compliance by learning country-specific cosmetic regulations and labeling standards, enabling faster and more accurate preparation and verification of regulatory documentation across diverse markets.”

The company says this integrated research ecosystem allows it to advance its beauty solutions, with AI serving as a key partner for researchers to drive innovation.

Consumers crave credibility

Beyond its R&D loop, Amorepacific says it uses AI in consumer-facing offerings, such as skin analysis and virtual makeup technologies. Haut.AI’s Georgievskaya says these types of technologies are en route to becoming industry standards.

“Many consumers have already experienced strong AI implementations from leading brands, and once they know this level of personalization exists, they naturally expect it everywhere,” she says. 

However, while many brands are experimenting with AI-driven advisors, consumer adoption still varies widely. Georgievskaya says multiple factors distinguish AI experiences that resonate with consumers from ones that remain more experimental.

“Consumers are quick to disengage from AI that feels generic, gimmicky, or disconnected from their real needs. A common example is routine recommendations based purely on quiz responses, without any actual skin analysis.”

She says that the underlying issue is that many consumers don’t fully understand their own skin and are often unsure how to accurately answer questions about their skin type or concerns. 

“This creates friction and uncertainty early in the experience, and users quickly lose confidence in results that are based on inputs they don’t trust themselves.”

In contrast, Georgievskaya explains that AI experiences combining objective skin analysis with contextual inputs tend to perform significantly better.

AI skin analysis can use geolocation data, such as UV exposure, to improve product recommendations.“Technologies that analyze the skin directly, paired with additional signals such as geolocation — to assess UV exposure — or lifestyle factors, create a much stronger sense that the system is asking the right questions and generating informed, relevant recommendations.”

These system features highlight the key differentiators to consumer adoption: perceived intelligence and credibility. “When users feel that the AI is grounded in real data, not just self-reported inputs, they are far more likely to trust and act on the recommendations,” Georgievskaya tells us.

Amorepacific’s generative AI-powered chatbot, for example, leverages the company’s internal product and consumer information database to help users choose suitable products based on their beauty concerns.

The company says the bot, called Amore Chat, can recommend products, compare options, and summarize product reviews, improving the overall user experience on its official online store, Amore Mall, which recently launched on ChatGPT.

Ensuring continuity 

According to Georgievskaya, personalization in beauty is an ongoing process. “A one-time analysis and static routine are no longer sufficient,” she says. “Consumers expect their skin care guidance to evolve continuously, reflecting changes in skin condition, environment, and lifestyle.”

She explains that brands are expected to proactively engage users, encouraging regular skin check-ins, monitoring changes over time, and updating recommendations as skin conditions evolve. “This creates a more dynamic relationship,” as it keeps consumers engaged with the brand.

Georgievskaya says technologies like Haut.AI’s skin analysis support brands to build this kind of returning-user experience. The tool enables continuous skin monitoring and routine optimization based on changes in a consumer’s skin.

“This evolution is moving personalization closer to a service model, where brands provide ongoing support rather than one-off recommendations,” she explains. 

Georgievskaya concludes that brands failing to offer AI-powered personalization risk falling short of what consumers now consider standard. “The absence of these tools creates a perception that the brand is less innovative, less helpful, and ultimately less capable of addressing individual needs.”