This week: AI moves from product search to direct checkout,
virtual try-on gets ready for mainstream launch,
and styling tools become embedded features instead of separate apps.
The thread connecting these three developments is clear —
AI is moving from experimental features to standard infrastructure for fashion e-commerce.
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1. AI Shopping Jumps From Discovery to Checkout
ChatGPT, Google Gemini, and Perplexity now let shoppers complete purchases without leaving the chat window.
During the 2025 holiday season,
retail traffic from AI search engines surged 700% year-over-year,
with conversion rates 31% higher than other sources (Adobe Analytics).
Industry analysts are calling this the biggest e-commerce disruption since mobile phones.
Brands like Glossier, Skims, and Spanx already enable direct checkout inside ChatGPT.
OpenAI is integrating 1 million Shopify partners’ checkouts,
while Microsoft Copilot and Google Gemini offer similar capabilities.
On February 11, Google Ads launched a new AI Mode shopping ad format and rolled out UCP-powered checkout.
This Universal Commerce Protocol (UCP) is an open standard created with major retailers including Shopify, Etsy, Wayfair, Target, and Walmart, creating a shared language for AI agents to communicate across the entire shopping journey.
The shift matters because 95% of searches don’t include brand names,
according to fashion e-commerce platforms.
People ask for “outfits for a weekend wedding” or “professional blazer for interviews” instead of searching for specific brands.
AI platforms scrape product details and descriptions rather than selling keyword ads, so detailed content now drives discovery.
This fundamentally changes how customers find your products.
Traditional SEO targeted Google’s algorithm.
AI shopping requires rich product descriptions that answer questions about fabric,
fit, use case, and styling.
If your product page just says “Blue Blazer - $89,” you won’t appear when someone asks an AI for “smart casual blazer for tech startup interviews.”
The takeaway: If your product pages have thin descriptions or missing details,
you may not appear in AI search results.
Most shoppers discover through use cases, not brand names,
so rich content drives visibility.
Start auditing your product descriptions now — focus on fabric composition,
fit guidance, styling suggestions, and specific use cases.
2. Alta Brings AI Styling Directly Into Brand Websites
Fashion app Alta partnered with New York brand Public School to embed AI styling tools directly into retail sites.
Shoppers can click a “Style by Alta” icon on product pages to see how pieces look on a personalized avatar that reflects their body type and wardrobe preferences.
The collaboration was announced February 14, 2026,
marking Alta’s first major retail integration.
The integration means the same avatar a customer builds in Alta’s app works across partner brand sites, preserving sizing, fit preferences, and style history.
That continuity matters — it reduces the friction of creating new profiles for every store and turns styling into a portable layer across retail touchpoints.
Over 100 million outfits have been generated on the Alta platform since its 2023 launch, and Time and Vogue named it one of the best innovations of last year.
This marks a shift from standalone styling apps to embedded tools.
Instead of leaving a brand’s site to use a separate app,
customers get styling recommendations within their shopping flow.
Public School designers Dao-Yi Chow and Maxwell Osborne had been looking for an AI partner and virtual try-on avatar solution, and Dao-Yi has been an Alta app user himself.
For brands, this partnership demonstrates a new distribution model for AI styling tools.
Rather than building proprietary technology in-house,
brands can partner with platforms like Alta to embed proven styling features directly into their e-commerce experience.
The approach lowers technical barriers and lets brands test AI styling without major development investment.
The takeaway: Embedded styling tools reduce friction and keep shoppers on your site longer.
As platforms like Alta become standard,
brands that offer personalized styling experiences may see higher engagement and lower return rates.
Consider partnerships with styling platforms or native features that let customers visualize complete outfits, not just individual products.
3. Zalando Launches Virtual Try-On for All Customers
Zalando is rolling out virtual try-on to all customers in 2026,
marking the technology’s shift from pilot to mainstream feature.
Generative AI has made try-on imagery photorealistic enough to show how specific fabrics and cuts lay on different body types.
Virtual try-on could reduce returns by up to 64%, according to industry estimates —
a critical breakthrough given that returns cost fashion retailers billions annually.
A wave of AI-powered try-on startups—Doji, Zelig,
Stiled—have emerged alongside tech giants like Google investing in the technology.
The shift makes virtual try-on a standard e-commerce feature instead of a novelty.
Earlier generative AI models struggled with realistic fabric drape and body shape accuracy, but 2026 models can now display how knit fabrics stretch differently than wovens, or how a structured blazer sits on shoulders of different widths.
For brands, this means customers expect to see garments on bodies similar to their own before purchasing.
Retailers with limited model diversity in product images may struggle as try-on tools become the norm.
When customers can visualize a dress on their own body type with one click,
product photos featuring only one model size become a competitive disadvantage.
The economics matter too.
Returns represent one of fashion e-commerce’s biggest cost centers.
If virtual try-on can cut return rates by even half the 64% estimate,
the impact on profitability is substantial.
Brands that adopt try-on technology early may gain a significant cost advantage over competitors still managing high return rates.
The takeaway: Virtual try-on is becoming a baseline expectation,
not a premium feature.
If your product images don’t show garments on diverse body types,
customers may look elsewhere for retailers offering personalized visualization.
Start preparing diverse on-model imagery now —
the brands that can show products on multiple body types will have content ready when virtual try-on becomes universal.
What This Means for Your Brand
Here are three practical shifts for fashion brands in 2026:
Enrich product descriptions — AI search engines scan your product details,
not just brand names.
Detailed fabric specs, use cases,
and fit notes drive discovery in ChatGPT and Gemini.
Audit your product pages and add specific details: fabric composition,
care instructions, fit guidance, styling suggestions, and use cases.
“100% cotton poplin, relaxed fit, professional or smart casual,
pairs with tailored trousers or dark denim” performs better than “cotton shirt.”
Prepare diverse on-model imagery —
Customers expect to see garments on bodies like their own.
Virtual try-on and styling tools make body-inclusive imagery a competitive requirement.
If your catalog only shows garments on one model type,
start planning shoots with diverse body types, ages, and presentations.
The brands with diverse imagery libraries will be ready when virtual try-on platforms ask for training data.
Test embedded styling experiences —
Standalone apps are giving way to embedded tools.
Explore partnerships or native features that let shoppers visualize outfits without leaving your site.
Even simple features like “complete the look” suggestions or outfit galleries can reduce decision paralysis and increase basket size.
LaonGEN helps you generate on-model imagery at scale,
so you can show your garments on different body types and contexts without booking multiple photoshoots.
Whether you need product photos for AI search optimization,
diverse model representations for virtual try-on,
or styling variations for embedded tools,
AI generation lets you create the content library you need.
Start with one free lookbook per day to test fit and styling for your catalog.
Ready to see your garment on a model?
Test free with one outfit, then scale with credits when you’re confident.
Need team plans, bulk generation, or enterprise security?
→ Enterprise inquiry
Sources: AI Just Had Its Big Shopping Breakthrough (Business of Fashion), ‘Clueless’-Inspired App Alta Partners With Public School (TechCrunch), Generative AI Is Revolutionising Virtual Try-On (Business of Fashion)
