AI hype is everywhere in retail, but for Wayfair CTO Fiona Tan, it’s not about chasing trends, it’s about making every step of the customer journey smarter, faster, and more human. In a main stage chat with CNBC’s Gabrielle Fonrouge, Tan offered a rare inside look at how Wayfair weaves large-scale AI into discovery, service, and every layer of its operating model.
From “Just Browsing” to Inspired Discovery
Tan began with a challenge familiar to anyone shopping for home goods: most customers don’t know how to describe exactly what they want. Wayfair’s latest solution is the AI-powered “Discover” tab, now live in its app. Rather than relying on endless filters or search terms, shoppers can interact with infinite AI-generated images of rooms, customizing style and features until they find the look that feels right. From there, every product is shoppable in a single tap.
Tan described this as the “AI flywheel”: every interaction, every click, scroll, and preference, feeds the learning model, allowing Wayfair to surface more relevant inspiration and recommendations over time. Unlike legacy segmentation models, which might talk to six customer types, today’s generative AI makes 1:1 personalization finally possible.
Early results? Shoppers engaging with the Discover tab convert faster and more often. But Tan is pragmatic: true adoption will take time as customers adapt to these new, more visual ways of shopping.
Human Touch at Scale With AI as an Enabler
Wayfair isn’t automating away human service, it’s amplifying it. “We’ve always prided ourselves on good customer service,” Tan said. The company is layering AI behind the scenes, helping human agents access and organize information more quickly, so customers wait less and get more accurate answers.
On the self-service side, smarter AI-powered chatbots are giving shoppers real choices: speak to a human, or resolve routine needs via bot, with both options continually improving. Importantly, Wayfair sees the value in blending human curation with AI: its “Wayfair Verified” program relies on product specialists to handpick top items in every category, ensuring that quality, install time, and value are transparently communicated, then scaling this selection with AI to thousands of products.
AI in the Back End: Quiet Revolution, Real Results
While much of the AI conversation is customer-facing, Tan emphasized the operational impact:
Coding assistants are speeding up developer productivity, but still require human oversight and expertise.
Product catalog enrichment now happens at scale, with AI cross-referencing images, text, and supplier data to ensure accuracy and depth.
Marketplace integrity is protected as AI flags and enriches product listings, minimizing “mismatched” shopping experiences.
The payoff? Operations are more efficient, product data is cleaner, and both customers and suppliers benefit.
Culture Shift: AI as Company-Wide Change Agent
Wayfair’s digital-first DNA helped but generative AI requires new thinking. Instead of limiting new tools to the tech team, Tan’s strategy is broad-based:
Every team member gets access to leading AI tools (like Gemini).
Hackathons bring together marketing, supply chain, and engineering to solve real business problems encouraging grassroots adoption and cross-functional learning.
There’s a push for everyone, not just product managers, to ask: “How can AI change my workflow? Where can we automate or improve?”
Tan’s advice to peers: stay flexible, don’t get attached to a single platform or model, and partner with solution providers who will collaborate and evolve as fast as the tech itself.
Key Takeaways: Building for ROI, Not Hype
As the session closed, Tan and Fonrouge distilled the formula:
Stay flexible: Don’t become precious about any one model or platform, experiment and pivot as needed.
Measure rigorously: Track ROI, adoption, and customer outcomes to guide investment.
Integrate, don’t just replace: Use AI to supercharge existing workflows and rethink what’s possible, not just swap out old tools.
Train and nurture talent: Invest in upskilling and foster a culture where every function feels responsible for innovation.
Wayfair’s journey is ongoing but the message is clear: AI’s real magic is in blending automation with human judgment, delivering a shopping experience that’s not just efficient, but truly delightful.
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