AI try-on vs AR try-on
AI try-on generates a new image of the shopper wearing a product from a photo they upload; AR try-on overlays a product model on the shopper’s live camera feed in real time. Both answer the same question — how would this look on me — but they differ in what they need from the shopper, what they need from the merchant, and which products they handle well.
How each approach works
AI try-on sends the shopper’s uploaded photo and the product image to a generative model, which composes a realistic picture of that person wearing that item. It needs no camera access and works from photographs the merchant already has. AR try-on renders a 3D model of the product over a live camera feed, tracking the shopper’s face or body as they move. It is instant and interactive, but each product generally needs a 3D asset built for it.
Where each is strong
AR suits rigid items that sit in a fixed place — glasses, watches, makeup shades — because a 3D model can track a face convincingly. It struggles with clothing, where drape and fit matter more than position. AI try-on handles garments better, since the model generates how fabric sits on a specific body. Its output has usually been a still image rather than a live mirror, though realtime AI video try-on now exists; each generation also takes a moment and consumes compute.
What this means on Shopify
For a merchant, the practical difference is assets and category. AR requires commissioning 3D models per product, which is viable for a small eyewear catalogue and painful for a large clothing range. AI try-on works from existing product photos, so catalogue size matters less. Looksy takes the AI route: shoppers upload one photo and see the result on the product page, with realtime video try-on available on its Scale plan.
Sources: the public Shopify App Store listing for Looksy. Last checked 27 July 2026.
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