For a lot of the final decade, style firms relied on scale, low sourcing prices and tactical promotions to develop revenue. Today, these levers not present the identical benefit.
Costs alongside the worth chain are rising, pushed by tariffs — most notably US-imposed — along with inflation and provide chain disruptions. It is estimated that tariffs launched in 2025 will drive worth will increase of 35 % for attire and 37 % for leather-based items within the brief time period. To add to this, style’s reliance on low-cost labour in sourcing international locations is below rising scrutiny, elevating questions on honest pay and sustainability.
Consumers are extra price-sensitive, constraining margins and limiting the flexibility to cross on prices. Seventy % of buyers intend to spend much less throughout attire classes from Q3 to This autumn 2025, and virtually 80 % say that when costs go up, they won’t purchase at full worth however will look ahead to a sale, purchase a cheaper different, postpone their buy or purchase secondhand.
Cash is below stress as sooner development cycles and uneven demand lead to overstock and tie up working capital in stock. The variety of days style firms held stock earlier than turning it into gross sales rose 4 % from 2023 to 2024, inflating warehousing and logistics bills.
Executives recognise these pressures and say altering margin, price and money methods would be the second most-significant theme to form the trade in 2026, second solely to tariffs and commerce disruptions.
Leading firms are pioneering know-how to reshape their financial fashions
Automation of cost-intensive processes frees up assets
By automating elements of processes equivalent to sourcing, stock administration and bodily sampling, firms can get monetary savings to dedicate to customer-facing differentiators, equivalent to personalisation, product innovation and enhanced retailer experiences. Generative and agentic AI are evolving shortly and promise to rework processes like these.
Leading gamers are overcoming challenges in scaling AI use circumstances
Research means that as much as 90 % of initiatives fail to scale past the pilot section. This is brought on by structural limitations (equivalent to weak governance, poor information high quality and fragmented instruments) and cultural limitations (equivalent to absence of incentives to reward considerate danger taking), each of which constrain experimentation at scale.
Digital instruments, backed by sturdy information foundations are enabling main gamers to beat these hurdles. Coach-parent Tapestry has used generative AI design device Adobe Firefly to scale its use of “digital twins,” that are digital replicas of actual merchandise. Digital twins had been first created to assist product growth, decreasing the necessity for bodily samples, then expanded to functions like content material creation for social media campaigns and in-store merchandising.
Digitisation can unlock double-digit reductions to sourcing prices
Rising enter prices, geopolitical tensions and shorter development cycles are bettering provide chain agility a high precedence for price financial savings.
While many style manufacturers nonetheless depend on legacy methods, top-performing manufacturers are digitising their sourcing practices to enhance flexibility in response to modifications in demand and provide chain shocks.
Brands are pursuing digitisation in several methods: Many companion with third-party suppliers equivalent to product lifecycle administration platforms, whereas others construct proprietary methods. Shein, for instance, has begun providing its digitised provide chain platform as a service to exterior manufacturers.
Looking forward, the following wave of innovation will probably be pushed by AI, enabling firms to leapfrog from early foundational sourcing fashions to superior, AI-driven fashions. Using instruments equivalent to AI brokers, firms can hyperlink methods like product lifecycle administration and enterprise useful resource planning to create a unified view of sourcing, enabling real-time analytics and unlocking double-digit price financial savings.
AI can provide an edge in a price-sensitive market
The hunt for the bottom costs is intensifying, pushed by rising worth sensitivity, the surge of dupes and use of each established shopper instruments equivalent to Google Shopping and Lyst in addition to newer entrants like Phia. This shift means manufacturers should precisely align costs with perceived buyer worth to stay aggressive.
AI is unlocking new ranges of precision and agility on this process. Leading firms are leveraging AI to combine price, competitor and buyer information in actual time to optimise pricing, both by constructing proprietary pricing engines, or leaning on specialist distributors that ship related capabilities. In doing so, they might not solely optimise costs but additionally construct richer perception to information future pricing choices.
Demand-driven methods are gaining traction as a lever to scale back stock pressures
Inventory challenges proceed to weigh closely on the style trade. The variety of days stock excellent — that means the common variety of days a firm holds inventory earlier than changing it into a sale — reached all-time highs in 2024, primarily based on evaluation from the McKinsey Global Fashion Index.
Upcoming laws will intensify the monetary burden of stock
In 2026, laws such because the Ecodesign for Sustainable Products Regulation within the EU and the Responsible Textile Recovery Act in California will penalise unsold or out of date inventory, impose recycling and take-back obligations, and lift the prices of non-compliance.
Demand-driven stock optimisation is one technique to shield margins
Technologies equivalent to digital textile printing, mixed with AI instruments that analyse demand and optimise manufacturing workflows, are making on-demand options extra possible. Initiatives equivalent to Nike’s SNKRS Reserve system, which permits a choose group of shoppers to preorder sneakers earlier than they’re made, illustrate how firms are starting to experiment on this area.
Some manufacturers are even growing their very own stock administration platforms that generate insights from information throughout operational and business capabilities to enhance accuracy and velocity.
How ought to executives reply to those shifts?
Prioritise essentially the most impactful areas to scale innovation
Evaluate the place margin positive aspects could be unlocked by assessing the total firm P&L — for instance, enhancing money movement by higher stock administration or boosting income by providing fewer reductions.
Target high-return applied sciences. Focus on options that sort out the largest inefficiencies first. Use a pilot-test-learn-scale method to handle danger, measure affect and scale promising options throughout the enterprise.
Support innovation with enablers equivalent to information sharing and alter administration
Enable information sharing between capabilities for sooner, more-informed choices. External companions equivalent to AI and cloud suppliers must also be built-in.
Support staff with satisfactory coaching and alter administration to allow widespread adoption of latest processes. Strong governance constructions are wanted to maintain momentum, with clear possession to make sure accountability, outlined resolution rights to allow efficient collaboration and aligned incentives throughout capabilities to stop pilots from stalling or remaining siloed.
Encourage experimentation and deal with failures as studying alternatives. Leadership ought to embody the tradition they wish to construct, talk overtly and sign that AI is a precedence that gives growth alternatives.
Reinvest freed-up assets into customer-facing differentiators
Redirect financial savings from price efficiencies into strategic customer-facing investments that can allow the model to face out in a extremely aggressive market. Study buyer preferences and benchmark towards opponents to prioritise differentiators.
For luxurious manufacturers, make investments additional into clienteling to supply extremely personalised providers to VICs, whereas sustainability-focused manufacturers may channel funding into blockchain traceability to strengthen model values with eco-conscious customers.
This article first appeared in The State of Fashion 2026, an in-depth report on the worldwide style trade, co-published by BoF and McKinsey & Company.