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Global AI spending is forecast by Gartner to reach $2.7 trillion this year, while fashion companies are already applying AI across planning, sourcing and other parts of the value chain. A new Lectra report argues that early adoption alone will not secure an advantage as AI systems take on more complex tasks; connected data, governance and organizational readiness will matter.
Fashion companies are adopting AI, but being early may not be enough to gain a lasting advantage, according to a Lectra white paper released this week. The French technology firm says brands will need connected business data, strong governance and organizational readiness as AI expands from productivity tools toward autonomous, multi-step workflows.
The report comes amid rapid growth in expected AI investment. Gartner forecasts global AI spending will reach $2.7 trillion this year, a 49.5 percent increase year over year. The research firm expects much of the spending to go to AI infrastructure, software and services, and identifies retail and consumer goods as an important market. The figure is a forecast, not a reported total of fashion-industry spending.
In fashion apparel, AI is being applied across the value chain, including product development, sourcing, inventory management and marketing. Lectra says brands such as C.P. Company and Kiko Milano are using AI for assortment planning, market intelligence and decision-making. Its report also describes applications in trend identification, manufacturing optimization, traceability and competitive analysis.
Lectra’s authors say the next stage will require more than adding standalone tools. Moving toward agentic systems that can carry out linked tasks in areas such as product creation, development, manufacturing and marketing depends on connected systems, data governance and a continuous digital thread, the report says. These are the conditions it identifies for AI to support decisions across a business rather than isolated tasks.
From AI Tools to Business Readiness
The distinction matters because adopting software does not automatically improve a company’s overall performance. The Lectra report says many fashion brands still treat AI mainly as a productivity tool, even as the technology could alter how products are designed, made, marketed and managed. Whether efficiency gains become stronger business results depends on how companies connect the tools to decisions and operations.
Research cited in the source report suggests that this challenge extends beyond fashion. The latest EY-Parthenon CEO Outlook survey found that almost all surveyed CEOs reported productivity gains, defined as more output per employee, over the previous 12 months. Nearly half said they were reinvesting gains to support growth, innovation and transformation. At the same time, nearly a quarter said gains were offset by operational complexity, regulatory obligations, risk management and increased work demands.
For fashion businesses facing volatile demand and supply-chain uncertainty, AI could help teams identify risks sooner and respond faster, Lectra argues. But that is the report’s assessment of potential benefits; the supplied material does not quantify returns across the industry or establish that AI adoption alone causes improved performance.
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Fashion’s Existing AI Uses
Fashion companies have taken a tactical approach to AI, according to the Lectra report, with use cases already spanning commercial planning and operational work. The firm says early adopters report gains in productivity, transparency, responsiveness and decision quality. It also says market leaders use AI-powered intelligence to check assumptions, spot risks and react to changing conditions. These findings are reported by Lectra; the supplied material does not provide detailed measurement methods or comparable results for individual brands.
The report frames the shift as part of AI’s wider movement beyond software engineering and into knowledge-work sectors such as fashion. It cites Stanford research saying frontier models have reached or surpassed human baselines on some complex scientific, mathematical and reasoning tasks, while standard coding benchmarks have been saturated. The source material does not identify the specific benchmarks or give further detail on the research methods, so those claims should be understood as Lectra’s account of the research.
Lectra also addresses concerns that AI could weaken a brand’s identity or heritage. Its authors argue that market intelligence can support human judgment rather than replace creative work, by helping teams review pricing, assortments and competitors. The report’s view is that AI can inform decisions while people remain responsible for the brand’s creative direction.
“Many fashion companies have already adopted AI tools, but being early is not the same as being ready.”
— Lectra white paper authors
Returns and Readiness Still Unmeasured
The supplied report material does not give a common set of financial results, adoption rates or comparison data showing how much AI improves fashion companies’ performance. It also does not specify how many companies were assessed for the reported early-adopter gains, how those gains were measured, or how they compare with businesses that have not adopted AI.
It remains unclear how quickly fashion companies can connect their systems and data, and what costs or operational changes that work will require. The report identifies data governance and connected systems as prerequisites for more autonomous workflows, but the supplied material does not set out a timeline, implementation standard or quantified return on investment. It also does not establish how widely agentic AI is already being used in fashion.
Building the Systems Behind AI
The development to watch is whether fashion companies move from isolated AI applications toward connected workflows across the product lifecycle. Lectra’s report says businesses seeking that shift will need to build data governance, link systems and maintain a digital thread connecting work from product creation through manufacturing and marketing.
The source material does not announce a specific deadline, new industry rule or next milestone. For now, the evidence presented is a forecast of expanding AI investment, examples of existing fashion use and a report arguing that preparation will shape the results. Further company-level data would be needed to show whether these investments deliver sustained gains in growth, profitability or resilience.
Key Questions
What is the main finding of the Lectra report?
The report says early AI adoption is not enough on its own. Fashion businesses need connected data, sound governance and organizational readiness to use AI effectively, particularly as systems take on linked tasks.
How much is global AI spending expected to reach?
Gartner forecasts $2.7 trillion in global AI spending this year, up 49.5 percent year over year. That is a global forecast, not a figure for fashion alone.
How are fashion companies using AI now?
Lectra describes uses in trend identification, assortment planning, market intelligence, manufacturing optimization, traceability and competitive analysis. The report names C.P. Company and Kiko Milano as companies using AI for planning and decision-making.
Does the report show that AI is already improving fashion-company profits?
No. Lectra reports gains such as productivity and responsiveness among early adopters, but the supplied material does not provide comparable financial measurements or show that AI adoption directly caused higher profits.
Source: wwd.com
