The beauty sector is undergoing a transformative shift with the integration of generative AI (gen AI), poised to add $9-10 billion to the global economy. Early adopters are already leveraging this technology, but scaling remains challenging due to rapid innovation. As leaders deploy gen AI at scale, the gap between industry pioneers and laggards will widen. This article explores four key use cases for gen AI in beauty, strategies for implementation, and long-term imperatives for success.

Prioritizing Key Use Cases for Gen AI

The beauty industry can harness gen AI across various functions, from consumer insights to internal operations. Four priority use cases stand out for their potential impact: hyperpersonalized targeting, experiential product discovery, rapid packaging development, and innovative product formulation. These applications not only enhance customer engagement but also accelerate product development cycles.

Hyperpersonalized targeting allows brands to craft tailored marketing messages that significantly boost conversion rates by up to 40%. By analyzing vast consumer datasets, gen AI creates microsegments and generates personalized content. For instance, a customer named Camille might receive an automated message highlighting products that complement her recent purchases. Brands must ensure these messages align with their ethos and avoid potentially harmful connotations. Integrating gen AI with digital asset management systems automates asset categorization, freeing marketing teams for higher-value tasks. Investing in in-house capabilities offers greater agility and control over consumer data.

Enhancing Customer Experience and Product Development

Experiential product discovery and rapid packaging-concept development are two areas where gen AI can revolutionize the customer journey and operational efficiency. Chatbots powered by large language models provide more engaging and personalized recommendations, improving conversion rates by up to 20%. Virtual try-on experiences allow consumers to visualize product effects on their skin, reducing costly returns. In physical stores, interactive screens can offer personalized content based on customer profiles, enhancing the in-store shopping experience.

Rapid packaging-concept development accelerates the design process. A designer can prompt gen AI to generate multiple packaging options, which are then refined based on consumer feedback. This iterative approach reduces concept development time by up to 60%. Innovative product development benefits from gen AI's ability to predict ingredient compatibility and formula efficacy, cutting research time from weeks to days and saving up to 5% on raw materials. While physical testing remains necessary, gen AI streamlines the process, enabling faster iterations based on consumer feedback.