TL;DR
Get beauty and skincare favorites delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
Gartner forecasts global AI spending will reach $2.7 trillion this year, while a new Lectra report says fashion companies need more than early adoption to gain a lasting advantage. The report points to connected data, governance and organizational readiness as requirements for moving from productivity tools to broader, autonomous workflows.
A Lectra white paper released this week says fashion companies will need connected data, strong governance and organizational readiness—not simply early access to AI—to turn adoption into a lasting competitive advantage. The report comes as Gartner forecasts global AI spending of $2.7 trillion this year, up 49.5 percent year over year, with retail and consumer goods among the markets investing in the technology.
Gartner expects much of the spending to go toward AI infrastructure, software and services. In fashion apparel, AI applications span product development and sourcing through inventory management and marketing. Lectra, a French technology company, says the industry has reached what its report describes as a “critical threshold” as AI moves beyond support for isolated tasks.
The report says many brands already use AI, but often treat it mainly as a productivity tool. It argues that increasingly capable systems could take on autonomous, multi-step work across product creation, development, manufacturing and marketing. To deploy those workflows, Lectra identifies data governance, connected systems and a continuous digital thread as necessary foundations.
Lectra cited C.P. Company and Kiko Milano as examples of brands using AI for assortment planning, market intelligence and decision-making. Its report says fashion companies also use the technology to identify trends, improve manufacturing, strengthen traceability and analyze competitors. These are examples presented by Lectra; the supplied material does not provide independent measurements of the brands’ results.
From Productivity to Business Advantage
The distinction matters because adopting a tool does not by itself show that a company can use it reliably across its business or convert efficiency into growth. Fashion operations link creative choices to sourcing, production, inventory and marketing; disconnected information or unclear oversight could limit how much value AI systems deliver across those stages.
Lectra argues that AI can support rather than replace human judgment, including by analyzing pricing, assortments and competitor behavior so teams can test assumptions. That may be particularly relevant to brands concerned that automated decisions could weaken brand identity and heritage. The report frames AI-powered analysis as a way to inform creative work, not a substitute for it.
A separate EY-Parthenon CEO Outlook survey provides a broader business comparison. Nearly all surveyed CEOs reported productivity gains—defined as more output per employee—over the previous 12 months, and nearly half said they were reinvesting to support future growth, innovation and transformation. EY researchers also said nearly a quarter of respondents reported that operational complexity, regulatory obligations, risk management and rising work demands offset productivity gains. The survey suggests efficiency does not automatically translate into enterprise performance; it does not establish a fashion-specific outcome.
Popular right now
Roborock F25 GT Set Cordless Wet Dry Vacuum Cleaner and Mop with 2 Brushes
KitchenAid Classic Series 4.5 Quart Tilt-Head Stand Mixer K45SS, Onyx Black
Ninja Flip Toaster Oven and Air Fryer, 8-in-1, Stainless Steel, SP151
As an affiliate, we earn on qualifying purchases.
Fashion’s AI Adoption and Its Limits
The report describes fashion as a sector that has embraced AI and deployed it tactically, giving some brands experience with uses such as trend identification and assortment planning. But Lectra’s central point is that early adoption and organizational readiness are different: the former means using tools, while the latter involves the data, systems and processes needed to use them across workflows.
Lectra also points to the pace of AI development beyond fashion. Its report cites Stanford research that says leading models have reached or exceeded human baselines on some complex scientific, mathematical and reasoning tasks, alongside saturation of standard coding benchmarks. Those claims are relayed through the Lectra report; the supplied material does not identify the specific benchmarks or provide details that would allow a separate assessment here.
The report’s proposed direction is to connect AI with business data and fashion-specific expertise. It says that foundation could help companies make decisions, respond to market shifts and manage risks across the product lifecycle. The material supplied also ends mid-sentence while discussing early creative and planning processes, so no further finding from that passage can be confirmed.
“Many fashion companies have already adopted AI tools, but being early is not the same as being ready.”
— Lectra report authors
Evidence Behind the Reported Gains
The source material does not give company-level metrics, study methods or comparison baselines for the reported gains among fashion AI adopters. It also does not quantify how many brands have the connected systems or governance Lectra says are needed, or how quickly agentic workflows are being adopted across the sector.
The $2.7 trillion figure is a Gartner forecast for global AI spending this year, not a fashion-industry spending total. The supplied information does not break out fashion’s share, the precise investment by retail and consumer goods, or how that spending will translate into financial returns. The report’s discussion of regulatory restrictions and business investment is not accompanied here by specific measures or timelines.
Building Foundations for Wider AI Use
The report points toward companies connecting data and systems, establishing governance and linking early creative and planning decisions with later stages of the product lifecycle. Those measures, Lectra says, would help fashion businesses move from isolated automation toward multi-step AI workflows. The source does not announce a formal implementation schedule, regulatory deadline or next report milestone.
For now, the key test is whether brands can demonstrate that AI-supported decisions improve operations without undermining creative judgment or brand identity. Further information about adoption rates, measured financial results and how companies oversee autonomous systems would help clarify whether the readiness Lectra calls for is producing durable advantages.
Key Questions
How much is global AI spending expected to reach?
Gartner forecasts $2.7 trillion in global AI spending this year, a 49.5 percent increase year over year. The figure covers AI spending globally, not fashion alone.
What does Lectra say fashion companies need beyond AI adoption?
The report identifies strong data governance, connected systems and a continuous digital thread as foundations for deploying AI across multiple stages of fashion work.
Which fashion brands does the report cite?
Lectra names C.P. Company and Kiko Milano as brands using AI for areas including assortment planning, market intelligence and decision-making. The supplied report summary does not provide independent performance figures for either company.
Does the report say AI will replace fashion designers?
No. Lectra’s authors say AI-powered market intelligence can help brands test assumptions and inform strategic decisions while retaining human ingenuity. The report also acknowledges concerns about preserving brand identity and heritage.
Are the reported productivity gains proven for the fashion sector?
The supplied material does not establish that. EY’s survey describes productivity gains among CEOs across sectors, while Lectra reports gains among early AI adopters in fashion without providing measurement methods or detailed comparative data.
Source: wwd.com
