According to Gartner Inc. global spending on AI is pegged to reach $2.7 trillion this year, which is a 49.5 percent increase year-over-year. The research firm said in a report that the bulk of these investments will be in AI infrastructure, software and services. The firm also cited retail and consumer goods as a key market for these investments.
For fashion apparel, the deployment of AI cuts across the entire value chain—from product development and sourcing to inventory management and marketing. According to a white paper from French technology firm Lectra released this week, AI is transforming the industry and has crossed a “critical threshold.”
“Many fashion companies have already adopted AI tools, but being early is not the same as being ready,” the report’s authors said. “As AI becomes capable of autonomous, multi-step work, competitive advantage will depend less on access to AI and more on the organizational readiness required to deploy it effectively. This shift comes at a time when fashion leaders are facing volatile demand, supply chain uncertainty, intensifying competition, regulatory requirements and rapidly changing consumer behavior.”
The report noted that despite the sweeping implications impacting AI deployment, many fashion 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.”
The focus of fashion apparel leaders on productivity is also shared across other industries and sectors. Findings from the latest EY-Parthenon CEO Outlook survey reveal an emerging productivity upswing. Almost all the CEOs surveyed reported productivity gains (defined by more output per employee) over the past 12 months, “with nearly half reinvesting to support future growth, innovation and transformation.”
“Yet those gains do not always translate into enterprise performance,” the EY researchers said, adding that 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.”
So, while the “productivity dividend” is emerging, organizations still face challenges converting efficiency gains into growth and profitability as well as long-term value creation.
Despite the challenges, the fashion apparel industry differs from many other sectors in that it has embraced AI. Fashion retailers and brands have also been tactical in deploying AI—and, as a result, are ahead of the curve in many ways. The Lectra research noted that brands such as C.P. Company and Kiko Milano are already using 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.”
The authors of the Lectra report said by integrating AI with connected business data and industry-specific expertise, fashion organizations can build a durable intelligence advantage that enhances decision-making, operational agility and resilience across the entire value chain. The report noted that 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 concluded that as AI reshapes how fashion companies execute workflows and navigate market volatility, leaders who act quickly to establish these foundational technologies will be uniquely positioned to transform their business models and maintain a competitive edge.
Lectra also found that AI-driven sector transformations are rapidly expanding from software engineering into broader knowledge-work industries, including fashion, driven by the speed of AI model evolution. The report cited recent Stanford research showing that frontier models have saturated standard coding benchmarks and reached or even surpassed human baselines on complex scientific, mathematical and reasoning tasks.
This has prompted tight regulatory export restrictions and major enterprise investments by leading AI firms. As AI capabilities mature from semi-competent tools to autonomous, high-performing systems, organizations across non-technical domains must prepare for an inevitable wave of AI-native disruption that will reshape how businesses operate, structure roles and generate value.
While some fashion brands fear that shifting from human-led decision-making to agentic AI could compromise their unique brand identity and heritage, pioneering leaders show that AI can enhance strategic decision-making, the report’s authors said. By leveraging AI-powered market intelligence to analyze pricing, assortments, and competitor behavior quickly and objectively, brands can validate creative instincts and challenge assumptions without replacing human ingenuity.
Applied across every stage of the product journey—from creation and manufacturing to sustainability and marketing—AI protects brand integrity while driving business model transformation in an increasingly dynamic market.
Lectra said fashion companies adopting AI-native processes during early creation already see measurable strategic advantages throughout the product lifecycle. Unifying early creative and planning phases with advanced analytics ensures downstream execution is driven by objective market signals rather than isolated guessing.
As Caterina Ticchio, head of merchandising at C.P. Company, noted, “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.”
For Lectra’s part, Maximilien Abadie, deputy CEO, said the company has always 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 the release of models like Claude Opus 4.6, in February 2026, and the advances in their ability to undertake autonomous, agentic work, demonstrated that AI has quickly become a paradigm shift in its own right.”
Abadie said for fashion companies, 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.”
The report’s authors reiterated that AI is not the end of SaaS, but the beginning of a new chapter for the software industry. AI is creating an opportunity for software companies to reinvent their value proposition and business models. The report said companies that embrace this shift and combine AI with deep industry expertise, proprietary data and proven workflows will create tremendous value for their customers.
But there’s a catch.
In the EY report, analysts said CEOs need to show that AI creates more value than it consumes. “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 of CEOs still face important gaps in their understanding of the costs and returns from AI.”
Gregory Daco, EY-Parthenon chief economist, said, “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.”
