Artificial intelligence (AI) is reshaping online shopping behaviors, increasingly guiding consumer purchasing decisions through intent-driven recommendations. This evolution in the shopping experience, termed agentic commerce, is shortening the buying funnel and accelerating conversion rates as consumers exhibit stronger intent following referrals from AI platforms.
Despite OpenAI’s recent decision to pull back from offering instant checkout features, which led some to prematurely declare the end of agentic commerce, the reality is more nuanced. OpenAI’s flagship chatbot, ChatGPT, has emerged as a popular recommendation tool, but it underscores the challenges of serving as a retail or transaction platform. Nonetheless, the influence of agentic AI on the purchasing journey remains significant. Notably, ChatGPT is responsible for 15% of referral traffic to Target and 20% to Walmart, highlighting its role as a trusted recommendation source, surpassing social media as the leading platform for product guidance, according to research by Accenture.
Retailers, particularly in the beauty sector, are taking notice. Ulta Beauty, for instance, is heavily investing in AI to enhance its operational infrastructure, including the shopper journey, in collaboration with technology partners like Google. Mike Maresca, Chief Technology and Transformation Officer at Ulta Beauty, emphasized the importance of being at the forefront of agentic commerce to deliver personalized and seamless experiences for consumers. He stated, “Being at the forefront of agentic commerce allows us to meet guests where they are and deliver personalized experiences that feel seamless, relevant, and undeniably Ulta Beauty.”
As beauty shopping becomes more personalized, the discovery journey is evolving. Research indicates that over 60% of beauty consumers initiate their experience through guided diagnostics, such as AI skin analyses or chats, rather than browsing entire product catalogs. Jing Feng, co-founder and COO of Bluefish, an AI marketing platform for Fortune 500 companies, noted the fundamental differences between AI-driven shopping experiences and traditional searches. She explained that the intent signals are richer, leading consumers to move through the purchasing funnel more rapidly, with real-time dynamic personalization of product recommendations.
AI-driven referrals result in stronger purchase intent among consumers directed to brands’ websites after engaging in AI conversations. Beauty brands utilizing AI-guided journeys are experiencing conversion rates that are two to three times higher than those relying on conventional browsing methods. This shift necessitates that beauty brands adapt their landing experiences to match varying consumer journeys and profiles. For example, a user researching a specific serum for oily skin will have different expectations than someone exploring options for sensitive skin.
The implications of this are profound, particularly in an industry where visuals and aesthetics typically drive interest. Ghezal Ebrat, founder and CEO of SearchBeaute.ai, remarked, “Agentic commerce shifts power away from who can capture attention and toward who best satisfies a specific user need.” This shift highlights the importance of context and relevance in AI-driven recommendations. If an AI agent is tasked with suggesting the most suitable product for a unique skin profile, mere brand awareness may no longer suffice for selection.
Consequently, beauty brands must create personalized and adaptive content tailored to the specific intents of consumers visiting their websites. Brands that clearly define their unique use cases are likely to gain visibility and recommendations on AI platforms. Traditional search engine optimization (SEO) and paid media strategies, which emphasize impressions and visibility, may not be as effective in this new landscape. Instead, discoverability increasingly depends on how well products align with a user’s specific skin type, concerns, and preferences.
A typical query on ChatGPT for a skincare product based on personal criteria yields a limited selection of recommendations, often no more than five. This narrowed selection fundamentally alters the discovery dynamics, pushing brands to compete not just for attention but for inclusion in curated recommendations. As competition for visibility intensifies, understanding the workings of AI algorithms becomes crucial for brands. While brands cannot dictate how large language models incorporate their products into conversations, they can influence the selection process by optimizing content that resonates with consumer language.
Feng echoed this sentiment, asserting that brands which communicate their unique product details clearly across all assets are more likely to appear in AI-driven recommendations. The focus must shift to how AI agents gather information to make relevant and trustworthy suggestions. Chavda, founder of Y2S Consulting, emphasized that the way brands present themselves online must be robust enough to gain the trust of AI algorithms.
As AI agents increasingly dictate beauty and skincare recommendations, the rules of brand visibility are being rewritten. The balance between intent and influence is shifting, with conversion relying less on traditional marketing methods and more on how effectively products are understood by both AI systems and consumers. While agentic AI may not yet be a direct sales channel, its capacity to generate significant intent and referral traffic to retailers is well established, paving the way for a new layer of discovery infrastructure where brand visibility hinges on trust, relevance, and precise alignment with consumer needs.
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