From helping employees work smarter to making shopping more intuitive, AI is shaping every part of the business. Online shopping is no longer confined to static product listings. Today, AI and data analytics are used to understand user behaviour, helping businesses provide customised product offerings.
While many e-commerce companies are still catching up with AI, American company Wayfair has had a jump start. Earlier this year, it launched a new AI tool called Muse, which helps customers visualise how furniture might look in a specific setting.
With Muse, users can discover, personalise, and shop for home décor and furnishings more intuitively. They can enter prompts ranging from broad concepts like “dining room” to highly specific ideas such as “moody 1920s-style living room”. Based on the prompt, Muse generates a series of AI-created inspirational scenes. Each scene features recommended Wayfair products that users can purchase immediately or save for later, creating a smooth experience from inspiration to action.
“Essentially, it (Muse) allows our customers to be inspired by something they see, and it allows them to also interact with it,” said Fiona Tan, CTO of Wayfair, in an exclusive interview with AIM.
She further pointed out that with Muse, users can generate a wide array of home decor visualisations, which are then linked to Wayfair’s extensive catalogue using visual search capabilities. Moreover, she shared that they are going to introduce the voice feature to the platform soon.
While Wayfair is not in the business of building furniture, Tan said there has been demand from customers for certain types of furniture created by them through Muse.
“We generally don’t get involved in manufacturing, but we work closely with our suppliers. If customers are asking for furniture we don’t currently offer, we can share those insights with suppliers. That way, they can decide if it’s something they want to build based on emerging demand,” she said.
The company is currently experimenting with several LLMs, including those from OpenAI, Google, and Anthropic. Tan pointed out that Gemini performs better for catalogue enrichment, ChatGPT is more effective for customer responses, and Claude is preferred for coding tasks.
Wayfair uses Gemini on Google Cloud to automatically categorise products across its 30 million product catalogue, cutting the time to curate new listings and update existing ones by 67%.
Addressing competition, particularly from IKEA, Tan pointed to their differing business models. “IKEA is very, I would say, physical stores first. They have a much smaller online presence. We’re kind of the flip. We’re mostly online.” This digital-first approach allows Wayfair to potentially leverage AI capabilities more extensively.
Wayfair isn’t the only one using AI. Its competitors are doing the same to improve the shopping experience. In 2022, IKEA launched IKEA Kreativ, a tool that helps customers design and visualise their rooms in 3D on any device.
Last October, Walmart also shared its plans to use AI, AR, and immersive tech. This included Wallaby, a set of AI models built to improve customers’ interaction with its platform. These models, which power personalised shopping, customer service, and content recommendations, are planned to roll out in the US, Canada, and Mexico by the end of 2025.
At the same time, Amazon has introduced its own AI shopping assistant, Rufus. It simplifies the Amazon shopping process by providing intelligent assistance, personalised recommendations, and seamless product discovery for users.
Key features of Rufus include the ability to guide customers on what to look for in various product categories, help them shop by occasion or purpose, facilitate comparisons between product categories, and provide personalised recommendations based on specific queries.
SEO is Dead
Reflecting on her journey as a CTO in the rapidly evolving space, Tan said she is trying to keep pace as much as possible. She believes that AI is going to have a significant impact on e-commerce. She pointed out that, in the past, e-commerce companies segmented customers into a few categories and created fixed email templates. Now, LLMs allow truly personalised experiences like generating unique subject lines and content per user based on intent and behaviour.
According to Tan, with tools like Perplexity and ChatGPT becoming “shopping agents”, the future of product discovery may not start on e-commerce sites like Wayfair, but on these AI platforms instead.
OpenAI and Perplexity AI recently announced new shopping features, allowing users to find, compare, and purchase products directly through the interface.
Tan explained that this is going to change the SEO game as well. According to her, this will require optimising content not just for Google Search, but for LLMs and shopping agents. “This is like the next version of SEO. We need to figure out what these agents value. It’s going to be much more content-rich versus just keywords,” Tan said.
How Wayfair is Using AI Coding Tools
Tan highlighted that Wayfair is integrating AI-powered code assistance across the company, not just for developers, but for all employees. Developers can choose from tools like Google Gemini, GitHub Copilot, and Anthropic Claude. “We’re trying to ensure that [non-developers] have access to GenAI tools as well, so they can become more productive in their own areas.”
She added that other coding tools like Cursor and Codeium (now Windsurf) are also being evaluated. “I wish I had more time to play around with Cursor. It seems like a really nice one for prototyping. And then there’s another one called Codium that we’re also looking at,” Tan said.
Tan is also aware of the term ‘vibe coding’. However, she still feels that developers should be mindful of what they are building with these tools. “The fact that you may not have to write a lot of actual code itself, you still need to know [the end goal],” she said, adding that analytics skills remain important. “Reviewing what is generated is also super important.”
Tan added that the company’s productivity will increase with the use of AI, but she does not think that means fewer developers will be required. Interestingly, earlier this year, Wayfair laid off 340 employees and is using generative AI to increase productivity following the company’s move to a cloud-computing environment.
With AI doing more heavy lifting and customers finding products in new ways, Wayfair seems ready for the next era of shopping, whether it starts on a website or not.
