Fashion meets AI: unlocking consumer insights with connected garments

Fashion has no shortage of AI. Forecasting tools read social feeds for emerging trends, recommendation engines sort catalogues and generative tools write product copy. Most of them work from the same data: what shoppers browse and what they buy. What happens to a garment once it leaves the store, how long it is kept, whether it is resold and who owns it next, has rarely been recorded at all.

Connected garments change that, though not always in the way the term suggests.

The phrase covers two quite different things. The first is the sensor garment: activewear or medical textiles with sensors that measure heart rate, movement or temperature. These collect continuous data about the wearer and need power, pairing and usually an app. They are valuable in their niche, and they raise obvious questions about consent and personal data.

The second is the identity garment: a garment carrying a tag in its care label or lining, read by a phone tap over near-field communication (NFC) or, at a distance, by a radio-frequency identification (RFID) reader. An identity tag does not measure the wearer. It records moments: when the garment was tagged, sold, scanned, passed to a new owner or resold. For most fashion and luxury brands this is the kind that scales, because it adds nothing to the experience of wearing the garment.

It is also the kind that answers the questions brands actually ask. Not how a jacket moves on a body, but where it went, who has it now and what happened to it after the first sale.

Each tap is a small, structured record: which item, when, where, and whether the tap was genuine. Across a range, those records add up to a picture no point-of-sale system holds.

• Where products actually are. Scans by country and location show where a style is being worn and resold, including places it was never officially sold.
• Who owns them now. Ownership transfers record when a garment changes hands, so a brand can see how long pieces stay with their first owner and how many owners follow.
• Which pieces keep circulating. Resales recorded against the item show which lines change hands and which stay put.
• Where risk is building. Invalid and repeated scans, counted per country, point to copies and grey-market activity before they reach a customer complaint.
• Who is newly interested. A person who scans a garment and leaves their details becomes a named lead, credited to the owner whose garment they scanned.

Cycle

Why a garment's record grows: each tap gives the next one a reason

One garment's record

1

A tap

An owner or a buyer taps the tag in the care label.

2

A record

Which item, when, where, and whether the tap was genuine.

3

A picture of the range

Where pieces are, who owns them, which keep circulating.

4

A reason to tap again

Proof, an easy way to pass it on, a direct line to the brand.

One garment's record

1. 1

   A tap

   An owner or a buyer taps the tag in the care label.

2. 2

   A record

   Which item, when, where, and whether the tap was genuine.

3. 3

   A picture of the range

   Where pieces are, who owns them, which keep circulating.

4. 4

   A reason to tap again

   Proof, an easy way to pass it on, a direct line to the brand.

5. ↻Back to 1: A tap. One garment's record.

A loop of four stages around one garment's record. First, an owner or a buyer taps the tag in the care label. Second, the tap becomes a record: which item, when, where, and whether the tap was genuine. Third, across a range, those records show where pieces are, who owns them and which keep circulating. Fourth, the brand can give owners a reason to tap again: proof, an easy way to pass the garment on and a direct line to the brand. That brings the loop back to the next tap.

That later life is where a growing share of fashion's activity happens. Boston Consulting Group (BCG) and Vestiaire Collective reported in 2025 that the secondhand market is expanding three times faster than the firsthand market. Each of those resales is a moment brands have traditionally missed.¹

Structured lifecycle data is what makes AI useful rather than decorative. In a 2025 survey of data management leaders, Gartner found that 63% of organisations lack, or are unsure they have, the right data management practices for AI. A model asked about a brand's products can only answer from what the brand has recorded.²

Customers are moving too. BCG and Altagamma's 2026 study found that among luxury consumers who use AI weekly or more, 79% have used it to research luxury products or experiences. As more of that research runs through AI tools, accurate and structured information about each product becomes more valuable, to the shopper and to the brand.³

They trust what it tells them, too. On the same study's net trust score, from a survey of more than 10,000 luxury consumers in 11 markets, AI tools rate 29 points as a source of information about luxury, close to word of mouth at 36 and about twice social media and influencers at 13. The brand's own website rates highest, at 42.³

Three practical points for brands considering connected garments.

• Put the identity where it will stay. A care label is designed to last the life of the garment, which makes it a natural home for a tag.
• Make the tap worth it for the owner. Proof of authenticity, an easy way to pass the garment on and a direct line to the brand give people a reason to scan.
• Respect the owner's privacy. Lifecycle data is about products, not surveillance. Each owner should decide whether their step appears in a product's public history.

Connected garments do not make fashion predictable. They make a garment's whole life visible, from the moment it is tagged through every later owner, and they give a brand's AI something real to work with.

Vera puts that lifecycle record to work through Ask Vera. A brand team asks questions in plain language about its own scans, certificates, owners, leads and transfers, and gets answers drawn from the brand's own records, alongside market and benchmark data Vera gathers for the category. Benchmarks compare a brand's scan, resale and ownership numbers with the market without anyone seeing another brand's data. Return on investment (ROI) analytics report the value delivered against what the brand spends with Vera, as a single multiple rather than a scan count.

None of this replaces judgement. It shortens the distance between a question a merchandiser has and the data that answers it.