Fashion technology trends 2026: what is real and what is hype

KEY TAKEAWAYS Summary by the editors

1. The most tangible fashion technology trend in 2026 is AI-assisted discovery: shoppers increasingly search and compare products through AI assistants, and retailers such as Zalando have built AI-driven feeds and assistants.
2. Agentic checkout is still early: OpenAI launched Instant Checkout in ChatGPT in 2025 and in early 2026 moved purchases into merchants' own apps inside ChatGPT, citing the complexity of inventory, tax and pricing.
3. Google launched virtual try-on using a shopper's own photo in Search Labs in the US in May 2025, built on an image model trained for how fabrics fold, stretch and drape.
4. Gartner predicts that over 40 per cent of agentic AI projects will be cancelled by the end of 2027 and estimates that only about 130 vendors offer genuine agentic capabilities.
5. The State of Fashion 2026 projects the smart eyewear category to exceed 30 billion US dollars by 2030 and expects resale to grow two to three times faster than firsthand fashion through 2027.

The fashion technology trends that are real in 2026 are AI-assisted product discovery, generative AI for product content and imagery, and AI inside everyday business software. Agentic commerce, where AI agents buy on the customer's behalf, and fully autonomous enterprise agents are advancing but remain early and uneven. The common thread is that data quality decides who benefits.

Which fashion technology trends matter most in 2026?

The State of Fashion 2026 by The Business of Fashion and McKinsey, subtitled When the rules change, places technology at the centre of several of its ten themes. The AI Shopper describes consumers using AI to search and decide; McKinsey reports that more than 35 per cent of executives surveyed use generative AI for online customer service, image creation, copywriting, consumer search or product discovery. Workforce Rewired and Efficiency Unlocked cover AI inside companies, and Smart Frames addresses AI-enabled eyewear, a category the report projects to exceed 30 billion US dollars by 2030.

Is AI changing how consumers discover fashion?

Yes, and this is the most tangible shift. Large platforms are rebuilding discovery around AI. Zalando introduced an AI-driven discovery feed in July 2025 in six countries and extended it to 16 more markets in October 2025, bringing it to 22 markets, according to FashionUnited; the feed presents clothing, brands and content aligned with a user's preferences in real time. Co-founder Robert Gentz described it as part of Zalando's evolution from a primarily transactional platform to an inspirational one.

Outside retailers' own sites, consumers increasingly ask general AI assistants for product advice. For brands, this makes structured, accurate product information more important, because AI systems can only describe and recommend what they can read reliably. Optimising content for AI answers, sometimes called generative engine optimisation, is becoming a discipline alongside traditional search engine optimisation.

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Is agentic commerce real yet?

Agentic commerce, in which an AI agent completes a purchase on the shopper's behalf, moved from concept to product in 2025, but the models are still being reworked. Google announced in May 2025 that agentic checkout would let shoppers set a price target and have Google add the item to the cart on the merchant's site and complete the purchase with Google Pay, initially for US product listings.

OpenAI launched Instant Checkout inside ChatGPT in 2025. According to Digital Commerce 360, OpenAI said in early 2026 that Instant Checkout was moving to apps, with purchases taking place through merchants' own apps inside ChatGPT. The publication reported that transaction complexity, including inventory, sales tax, pricing updates and in-store stock, required constant maintenance. The lesson for fashion is that agents depend on exactly the data that brands often struggle to keep accurate.

Is virtual try-on finally ready?

Virtual try-on has improved markedly. In May 2025 Google began rolling out a feature in Search Labs in the US that lets shoppers try apparel listings on themselves by uploading a photo, initially for shirts, trousers, skirts and dresses. Google says it is powered by a custom image generation model for fashion that understands how materials fold, stretch and drape. Whether such tools reduce returns at scale, the outcome retailers care most about, has not yet been shown in public data, so brands should treat claims of lower returns with caution until they can measure them.

What is still mostly hype?

Autonomous AI agents running large parts of a fashion business are the area with the widest gap between promise and practice. Gartner predicts that over 40 per cent of agentic AI projects will be cancelled by the end of 2027 because of escalating costs, unclear business value or inadequate risk controls. It also estimates that only about 130 of the thousands of vendors claiming agentic AI offer genuine agentic capabilities, a practice it calls agent washing.

• Claims that AI will design whole collections without human designers.
• Promises of fully autonomous planning or buying in the near term.
• Vendor labels that rebrand chatbots or automation as agents.
• Return reduction figures for virtual try-on that are not backed by controlled tests.

Which non-AI trends shape fashion technology in 2026?

Technology priorities also follow business shifts. The State of Fashion 2026 expects the secondhand market to grow two to three times faster than the firsthand market through 2027, which requires systems for authentication, pricing and tracking of used items. Tariff turbulence, another of the report's themes, is pushing brands to adjust sourcing and pricing, increasing the value of planning and scenario tools.

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What should fashion leaders do about these trends?

1. Make product data complete and machine-readable, because every discovery and commerce trend depends on it.
2. Monitor how the brand appears in AI assistants and AI-driven platform feeds, and correct inaccurate information at the source.
3. Pilot customer-facing tools such as try-on or assistants with a control group before scaling.
4. Treat agentic projects as experiments with clear stopping rules and costs modelled at scale.
5. Check vendor claims against demonstrations on your own data.

The trends that matter in 2026 are less spectacular than the headlines suggest, but they are real. Brands that combine sober experimentation with steady work on their data will be best placed when the more ambitious ideas mature.

Frequently asked questions

What are the biggest fashion technology trends in 2026?

The most important trends are AI-assisted product discovery, generative AI for product content and imagery, virtual try-on and the first forms of agentic commerce. AI is also spreading inside companies through assistants and early enterprise agents. The State of Fashion 2026 names the AI shopper, a rewired workforce and efficiency gains among its ten themes.

What is agentic commerce in fashion?

Agentic commerce means AI agents that search, compare and complete purchases on a shopper's behalf. Google announced agentic checkout for US product listings in 2025, and OpenAI launched Instant Checkout in ChatGPT before moving purchases into merchants' own apps in early 2026. The field is early and depends on accurate product, price and stock data.

Does virtual try-on reduce returns?

It may, but there is no robust public evidence yet that virtual try-on reduces returns at scale. Tools have improved, for example Google's try-on using a shopper's own photo launched in the US in 2025. Retailers should test the effect on returns with a control group before relying on it.

Are AI agents overhyped?

Partly. Gartner predicts that over 40 per cent of agentic AI projects will be cancelled by the end of 2027 due to costs, unclear value or weak risk controls, and estimates that only about 130 vendors offer genuine agentic capabilities. Agents can be useful for well-defined tasks with reliable data.

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