Gartner Pegs Global AI Spend at $2.7 Trillion as Fashion Dividend Slips

Global spending on AI will reach $2.7 trillion this year, a 49.5 percent increase year-over-year, according to Gartner Inc. The research firm said the bulk of that money will go to AI infrastructure, software and services, and named retail and consumer goods as a key market for the investment.

For fashion apparel, the spending arrives at a moment of tension. A white paper released this week by French technology firm Lectra argues that AI has crossed a "critical threshold" in the industry, cutting across the entire value chain — product development, sourcing, inventory management and marketing. Yet most brands, the authors said, still deploy it too narrowly.

What does the Lectra report actually claim?

"Many fashion companies have already adopted AI tools, but being early is not the same as being ready," the report's authors said. They argued that as AI takes on autonomous, multi-step work, "competitive advantage will depend less on access to AI and more on the organizational readiness required to deploy it effectively."

The timing matters. Fashion leaders face volatile demand, supply chain uncertainty, intensifying competition, regulatory requirements and rapidly changing consumer behavior — pressures that reward faster, data-driven decisions.

The report found that many brands "still view AI primarily as a productivity tool rather than a force that could fundamentally reshape how products are designed, manufactured, marketed and managed."

That productivity focus is not unique to fashion. The latest EY-Parthenon CEO Outlook survey found almost all CEOs reported productivity gains — more output per employee — over the past 12 months, with nearly half reinvesting to support growth, innovation and transformation.

But the gains do not automatically become profit. Nearly a quarter of CEOs polled said productivity gains "are offset by the need to manage operational complexity, regulatory obligations, risk management requirements and increasing work demands, driven by the changes that are boosting productivity itself."

Who is already deploying AI in fashion?

Fashion has moved faster than many sectors, and Lectra named two confirmed adopters: C.P. Company and Kiko Milano. Both use AI to improve assortment planning, market intelligence and decision-making.

"Across fashion, companies are already using AI to identify emerging trends, improve assortment planning, optimize manufacturing, enhance traceability and strengthen competitive analysis," the report stated. "Early adopters report gains in productivity, transparency, responsiveness and decision quality, while market leaders increasingly rely on AI-powered intelligence to validate assumptions, detect risks earlier and react faster to changing conditions."

Caterina Ticchio, head of merchandising at C.P. Company, described how the technology connects planning functions: "Forecasting, pricing, merchandising and inventory management are all deeply interconnected, and the strongest downstream outcomes come when the planning and creative stages of the product journey are managed as one decision system rather than as separate disciplines."

Why agentic workflows change the requirements

Lectra said moving beyond simple automation to autonomous, multi-step agentic workflows — spanning product creation, development, manufacturing and marketing — requires strong data governance, connected systems and a continuous digital thread.

The report cited Stanford research showing frontier AI models have saturated standard coding benchmarks and reached or surpassed human baselines on complex scientific, mathematical and reasoning tasks. That capability jump has triggered regulatory export restrictions and major enterprise investments by leading AI firms.

Maximilien Abadie, deputy CEO of Lectra, said the company has long seen AI "as one of several strategic pillars that the future of fashion would be built on, alongside big data, the cloud and the internet of things (IoT)." But, he said, the release of models like Claude Opus 4.6 in February 2026 and their ability to undertake autonomous, agentic work "demonstrated that AI has quickly become a paradigm shift in its own right."

For fashion companies, Abadie said, implementing AI "represents a real step-change — not just in the individual tasks such technology can accomplish within well-defined business areas, but in its ability to improve and unlock multi-step workflows, collaborative working relationships and far more comprehensive transformations that felt out of reach as recently as the end of last year."

Some fashion brands fear that shifting from human-led decision-making to agentic AI could compromise brand identity and heritage. The report's authors countered that pioneers use AI-powered market intelligence to analyze pricing, assortments and competitor behavior quickly and objectively — validating creative instincts without replacing human ingenuity.

Lectra also framed the shift as an opening for software vendors rather than their demise: AI is "not the end of SaaS, but the beginning of a new chapter," and companies that combine AI with deep industry expertise, proprietary data and proven workflows will create the most value.

What is the catch for sourcing and planning teams?

The EY report quantified the gap. "Only 16 percent of CEOs have detailed, real-time visibility into AI costs and high confidence in assessing return on investment," the report said. A further 56 percent have reliable visibility into most costs and reasonable confidence in returns, while a significant number still face important gaps in understanding AI costs and returns.

Gregory Daco, EY-Parthenon chief economist, put the decision plainly: "The pace of adoption will depend not only on what the technology can do, but whether the value created by each token exceeds its cost."

For sourcing and product leaders, the implication is concrete: auditable data governance and connected systems — not tool purchases — now determine whether AI investment converts into margin, speed and resilience.