When The State of Fashion 2026 landed, one number did most of the talking: 46% of fashion executives expect trading conditions to worsen over the coming year โ up from 39% the year before. Read on its own, that sounds like an industry bracing for impact. Read alongside the rest of the report, it describes something stranger: an industry that has stopped agreeing with itself.
Because in the same survey, the single biggest opportunity executives named was artificial intelligence. Pessimism about the operating environment and optimism about the tooling are now running in parallel, and the gap between them explains most of what shoppers will notice on product pages, price tags and delivery windows this year.
The pessimism is real โ and it is concentrated
The eight-point jump in executives expecting deterioration is not spread evenly across the industry. It clusters around companies whose margins depend on moving physical goods across borders on a fixed calendar: mid-market wholesale brands, department-store-dependent labels, and anyone whose costing sheet was built before 2025's trade shifts.
What has not collapsed is demand. Consumers are still buying clothes; they are buying them more deliberately, later in the season, and with far more price comparison in between. That distinction matters. A demand crisis and a cost crisis look similar on a spreadsheet and require opposite responses. Most of 2026's strategic noise comes from brands misdiagnosing which one they are in.
The industry's mood is not "nobody is shopping." It is "we no longer know what this shipment will cost by the time it arrives."
Tariffs, not demand, are the headline risk
Roughly three-quarters of executives named tariffs and trade policy as their most disruptive external issue โ the highest consensus on any single risk in the survey. For a category with thin unit margins and long lead times, that is uniquely painful. A tariff change announced in March can land on goods that were costed in November, cut in December and shipped in January.
The practical responses fall into four buckets, and you can usually tell which one a brand chose by looking at its site:
- Absorb it โ hold retail prices, take the margin hit, hope it is temporary. Visible as unchanged prices and quietly thinner assortments.
- Pass it on โ raise prices, often unevenly across categories. Visible as odd price jumps between near-identical styles.
- Re-engineer it โ change fabric weight, trims, or country of origin. Visible in composition labels that shifted between seasons.
- Move it โ relocate production closer to the customer. The slowest fix, and the one reshaping the supply map.
None of these are cost-free. The re-engineering route is the one shoppers should watch most closely, because "same style, same price, lighter fabric" is the least visible form of inflation in apparel.
Where the optimism is coming from
The counterweight in the report is efficiency. AI showed up less as a marketing story and more as an operational one: demand forecasting, size-curve planning, markdown timing, returns prediction, and the unglamorous work of describing tens of thousands of products accurately.
That last point is quietly the most consequential for how you shop. Search engines still route the large majority of discovery traffic, but a growing slice of product research now happens inside AI assistants that read structured product data rather than browsing pages. Brands with clean, specific, machine-readable product information โ real measurements, real fabric composition, real care instructions โ get surfaced accurately. Brands with vague copy get paraphrased into vagueness or skipped.
The report frames this as the arrival of the AI-assisted shopper. In practice it rewards specificity. "Relaxed midi in 210gsm cotton poplin, 48in length on a size S" survives being read by a machine. "Effortless summer staple" does not.
What this actually means if you buy clothes
Three habits travel well through a year like this one.
Read the composition, not the adjectives. When cost pressure hits, fabric is where it shows up first. A drop in gsm or a shift from a mid-weight woven to a lighter blend changes how a garment hangs, wears and lasts far more than any styling photograph suggests.
Treat measurements as the product. Letter sizing is drifting across the industry as brands re-grade for different manufacturing bases. Chest, waist, hip and length in inches are the only stable comparison points between two brands โ which is why we publish them on every PHEFEE product page rather than relying on S/M/L alone.
Buy into structure, not novelty. The pieces that survive a volatile pricing year are the ones that combine with what you already own. That is the logic behind how we build our New In drops โ tighter assortments, deliberate palettes, fewer one-outfit pieces โ and why our coordinated sets are cut to be worn split as well as together.
Frequently asked questions
Will clothing prices rise in 2026?
Unevenly. With about 76% of fashion executives citing tariffs as their biggest disruption, cost pressure is broad โ but brands are responding differently. Expect selective price increases, more aggressive markdown cycles on slow sellers, and quiet specification changes on carryover styles rather than a uniform across-the-board rise.
Why do 46% of executives expect a worse year if people are still shopping?
Because the pressure is on costs and predictability, not demand. Tariffs, freight volatility and shorter planning windows compress margins even when sales volumes hold. That is why the same survey names AI and operational efficiency as the leading opportunity โ it is a cost problem looking for a cost answer.
How can I tell if a brand cut quality to hold its price?
Compare fabric composition and weight against the previous season if the brand publishes it, check whether garment measurements changed for the same size, and look for a shift in country of origin. Lining removal and thinner interfacing are the two most common invisible cuts.
Does AI change how I should search for clothes?
It changes what works. Specific, attribute-led queries โ fabric, length in inches, occasion, fit โ now return better results than mood words, both in search engines and in AI assistants, because they match the structured data brands publish.
Sources
- The State of Fashion 2026, The Business of Fashion & McKinsey & Company โ mckinsey.com
- The Business of Fashion, industry reports and analysis โ businessoffashion.com
Editor's note: research and drafting for this article were AI-assisted and reviewed by the PHEFEE editorial desk before publication. Figures are quoted from the sources listed above; we do not publish estimates we cannot attribute.
