E.l.f. Beauty Says AI Answer Engines Are Already Changing How People Shop

Why It Matters

Reaching even a modest share of agentic commerce forces retailers to overhaul technology stacks and media spend, while the ongoing debate creates strategic uncertainty for brands planning AI integration.

Key Takeaways

• Agentic commerce projected at 10% by 2030
• Retail media analysts doubt full AI-driven transactions
• AI reshapes discovery, but funnel stages persist
• Shoptalk debate highlights industry split on AI adoption
• Brands must balance automation with human touch

Pulse Analysis

Generative AI answer engines are quickly becoming a new front‑line for product discovery, allowing shoppers to ask natural‑language questions and receive curated recommendations. e.l.f. Beauty’s recent remarks at Shoptalk underscore how brands are experimenting with these tools to shorten the awareness phase and drive higher conversion rates. By embedding large language models into storefronts, retailers can surface relevant items in real time, creating a more conversational shopping experience that blurs the line between search and personal assistance.

The debate at Shoptalk centered on the feasibility of fully agentic commerce—transactions completed without human intervention. Scot Wingo’s 10% by 2030 forecast reflects confidence in rapid AI adoption, yet Andrew Lipsman’s rebuttal highlights persistent friction points such as trust, payment security, and regulatory compliance. Retail media platforms, which currently monetize the middle of the funnel, must anticipate a shift in spend as AI potentially compresses the funnel, reducing the need for traditional display and paid‑search campaigns. This uncertainty forces marketers to hedge investments between proven media channels and emerging AI‑driven experiences.

For retailers, the practical takeaway is to adopt a phased AI strategy. Begin by integrating answer engines for discovery and support, while maintaining human oversight for checkout and post‑purchase service. Simultaneously, monitor consumer sentiment and transaction data to gauge readiness for deeper automation. Brands that balance AI efficiency with a human touch are likely to capture early market share, whereas those that overcommit to fully agentic models risk alienating shoppers still accustomed to conventional buying pathways.