You’ve met Ralph Lauren’s bear, but are you ready to meet his bot?

The world of Ralph Lauren has always invited you to fantasise. You could buy a crisp Oxford shirt and, for a moment, feel like you belonged on a sailboat off the Nantucket coast or at a polo match in the Hamptons. His empire was built not just on clothes, but on an idea of taste—the quiet assurance of knowing how to pair loafers with linen, or how to wear denim without ever looking undone.

Now, in 2025, that idea is being mediated by something far less romantic: a chatbot. You’ve met Ralph Lauren’s bear, but are you ready to meet his bot? Ask Ralph, the new in-app stylist that Ralph Lauren launched with Microsoft’s Azure OpenAI under the hood, is the latest sign that fashion’s flirtation with tech has become a full-blown marriage.

How does it work? You feed it a prompt: “What should I wear to a concert?” or “How can I style my navy-blue men’s blazer?”, and, in turn, it offers polished, shoppable laydowns: head-to-toe Polo looks, links to buy, and a tone as carefully buttoned as a purple label blazer.

That buttoned-up commercialism is the point. David Lauren describes Ask Ralph as a way to “step into our world,” to translate decades of archive, lookbooks, and brand philosophy into an instantly accessible styling assistant. It’s smart retail theatre: archive + inventory + conversational AI = a 24/7 stylist that never needs coffee breaks.

But the real story isn’t that Ralph Lauren made a bot. It’s what that bot forces us to ask next: who owns taste when a machine mediates it? Take my test drive, for example. Ask Ralph gave me the kind of outfits a conscientious department store salesperson might: safe, cohesive, and very buyable. I got repeat looks—a plain grey dress paired with a black scarf and bag cropped up several times. For a casual outdoor wedding, it suggested a white sundress with a cream cable-knit bucket hat. Far from original and nothing extraordinary. It offered an olive turtleneck and blue jeans. When I cheekily asked if AI was “deeply un-chic,” the bot politely declined to engage. Charming, underwhelming, yet so on-brand.

And Ralph Lauren isn’t alone. From Louis Vuitton and Walmart to H&M and Zara, brands are racing to marry their catalogues with conversational commerce. Market experts project virtual shopping assistants to swell from hundreds of millions to billions in the coming decade. Big tech, from OpenAI, Google, Microsoft, to Amazon, supplies the scaffolding. New multimodal models can read text, voice, and images, and are already making bots feel more human; who could forget the row over a chatbot voice that sounded a little too much like the Her-style Samantha?

The landscape is shifting faster than fashion’s usual slow waltz with tech, and that velocity brings promise: better fit, fewer returns, more personalised discovery, and—crucially for sustainability, smarter inventory. Stella McCartney’s work with Google Cloud and AR try-ons from Burberry point to real, practical uses. Startups like Zelig, which combines virtual try-on, intelligent styling, and a “dynamic digital closet,” argue that true personalisation comes when models are trained with fashion expertise, not just product attributes. “Fashion isn’t math—it’s more like magic,” Sandy Sholl of Zelig says, and her human-in-the-loop approach is built around that tension.

There’s also evidence that AI can spot patterns humans miss. Researchers at Pusan National University used ChatGPT and DALL-E to forecast fall menswear trends and produced images that, in many cases, eerily echoed real runway looks. But the study also proved the obvious: prompts need an expert hand. AI can remix the past and amplify signals in mountains of data, but trendsetting—the lightning bolt that starts a movement—still requires human curiosity, risk, and yes, mischief. This goes to prove that AI can predict many things, but not the spontaneous cultural jolt that invents a new silhouette.

 

And then there’s the dark side. The likelihood is that models’ images and body scans could be repurposed by brands without fair recompense, leading to the “Frankensteining” of likenesses and new forms of exploitation. Instances of AI-generated imagery appearing on e-commerce sites—sometimes with alarming errors—show how quickly ethics and consent can be outpaced by deployment. The choices we make now will determine whether AI entrenches inequitable power structures or helps reimagine the industry for the better.

So where does that leave taste? For shoppers, the potential is limitless. AI can be an immensely useful stylist: it can suggest looks, decode sizing, and stitch together your existing wardrobe with new pieces. For brands, it’s a powerful commerce lever. But taste, especially the deliciously local, idiosyncratic, messy kind, lives in context. Will a model trained on Ralph Lauren’s archive grasp why a Mumbai monsoon demands breathable, quick-dry linens and an umbrella that doubles as a statement? Will it know the lighting of Lagos nightlife or the layered subversion of Seoul streetwear? Perhaps, in time. With diverse data and localised inputs, AI will learn to be more than a one-size-fits-all chic.

Until then, fashion’s human talents still matter most: storytellers, rule-breakers, and those who can ask the right question to a machine and then know what to do with the answer. Brands should ask themselves not only how fast they can deploy bots, but whose tastes and codes they’re amplifying. An algorithm may be excellent at selling you a polo; it’s another thing to teach it how to fall softly in love with a sari’s sequins in stormy weather.

Let Ask Ralph handle the neat, useful bits—pulling catalogue looks, suggesting pairings, streamlining shopping. Let the technologists keep refining what personalisation can mean. But the soul of style prides itself on being unruly. It lies in the kurti worn unabashedly with sneakers, the vintage scarf borrowed from an aunt, the much-too-worn oversized blazer shrugged on in defiance of trends.

Algorithms can tidy up our closets, but they can’t yet capture those moments when fashion feels less like a calculated move and more like a secret between you and the mirror. The question isn’t whether machines can dress us; it’s whether we’ll let them define what it means to be well-dressed.

Lead image: Ralph Lauren

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