AI stylists promise wardrobe breakthroughs, but a human touch still wins

Three AI-powered startups promise to democratize dressing for a wide range of body types, offering personalized styling without the cost of a traditional personal stylist. ShapeShopp, Style DNA and BU Style each pursue a different path: ShapeShopp blends body-shape analysis with human curators; Style DNA converts closet photos into outfit ideas aided by color typing; BU Style pairs clients with a human stylist who reads body language and behavior. A New York Post fashion writer tested the trio to see whether AI can pull someone out of a fashion slump without sacrificing personal style.

ShapeShopp operates around a three-tier membership plan, ranging from $9 to $99 a month, and uses a soon-to-be-patented system to identify body shape from the relationship between shoulders, waist and hips rather than from clothing size. The tech also analyzes garment attributes such as necklines, pleats and waist placement, scoring items by how well they fit different figures. After that, human stylists curate weekly shoppable catalogs drawn from the aligned selections. The aim is to reduce the online shopping frustration that tends to produce fitting-room failures, according to co-founder Amy Wister.

For the assessment, the author wore a skintight black bodysuit and leggings; the algorithm labeled her body as green — narrower shoulders, fuller hips, and a defined waist at the top. The recommended strategy was to add visual weight to the upper body, especially the shoulders, to create balance. An Aritzia twill dress with a button-up midi, patch pockets, tie waist, and flowing fabric was singled out as a good example for work. In testing, the dress proved flattering in store and aligned with a look that felt chic without feeling too corporate. ShapeShopp suggested daytime silhouettes with horizontal or rounded necklines such as scoop, crew, square, boat or sweetheart to avoid exaggerating shoulder-hip contrast; for nights out, it was acceptable to emphasize the upper body.

The writer also tried Style DNA, an AI personal stylist app that turns photos of a closet into outfit ideas while also pitching new clothes from real retailers based on a body-type profile. The app asks for selfies to determine a color type, assigns a Style Formula, and then uses an AI stylist chatbot to propose outfits and answer questions. The service costs $29.99 a month and relies on a color-type label — in this case True Winter — to tailor recommendations. The test produced outfits that felt more like random mashups than coherent wardrobes, including a floral office blouse layered over a skintight black minidress as a work look that never felt quite right.

Natalie Tincher, founder of BU Style, represents the human-centric option. BU Style emphasizes reading body language, confidence and intention as part of dressing, rather than relying on algorithms alone. Memberships range from about $141 to $875, with flexible formats that can focus on new items, wardrobe edits or a full makeover using the client’s existing closet. Tincher led a virtual session after the Style Strides questionnaire and an upload of the writer’s wardrobe, explaining how she categorizes a client as having a primary Creative influence with Polished as a secondary. Using the closet, Tincher styled three outfits entirely from pieces the author already owned: a polished work look built from a roomy black sweater and a vintage floral skirt; a night-out look centered on the black minidress paired with a black leather blazer; and a daytime social look built around a pair of jeans paired with a floral corset top layered over a lace shirt. Tincher also suggested a small number of pieces to buy to complement the closet, but the emphasis was on rethinking what was already there. The experience felt personal, practical and enjoyable, transforming neglected items into outfits that felt like the writer’s own.

The experiment left a clear verdict: StyleDNA can be a playful entry point for inspiration, but ShapeShopp offered the most consistently usable results for real-life shopping, and BU Style delivered the strongest, most transferable sense of personal style when applied to an existing wardrobe. In the end, the writer found that AI can expand options and speed up discovery, but human judgment remains essential for fit, nuance and confidence. The emerging picture is not AI versus human stylist; it is AI empowering humans to dress better, faster, and more affordably, with the most reliable outcomes arising when technology and people work hand in hand.