The fashion industry’s upcoming expansion will depend not only on artificial intelligence but also on the infrastructure that enables AI to function effectively. Generative AI has the potential to contribute between $150 billion and $275 billion to operating profits in fashion and luxury over the next ten years, according to McKinsey’s industry analysis. However, this potential can only be realized if businesses first address their fragmented data systems. Jatin Paul, CEO of WFX (World Fashion Exchange), emphasizes that AI delivers real value only when businesses have the right digital foundation—a modern system where product development, costing, sourcing, production, planning, and inventory all work from the same connected data instead of disconnected systems and spreadsheets.
Many companies continue to operate using separate spreadsheets and outdated software. Without integrated data, AI cannot make accurate decisions. As a result, firms like Aditya Birla Fashion, Shahi Exports, and Gokaldas Exports are upgrading their technology before expanding AI applications. Their objective extends beyond simple automation—they aim to create a unified system where production, cost tracking, and inventory operate in real time. Legacy systems were never designed for cloud computing, connected data, or AI, which is why these manufacturers are prioritizing modern infrastructure to strengthen their data foundation before scaling AI investments.
For manufacturers, the benefits of this approach are immediate and substantial. Real-time tracking reduces defects before shipments depart the factory. Predictive maintenance identifies equipment issues before they disrupt operations. Order processing transitions from manual PDF handling to automated workflows that directly pull buyer information. Modern systems also allow managers to monitor production and quality in real time, solving issues while production is still running rather than after products have already been shipped. This reduces maintenance costs, prevents unexpected downtime, and keeps production running smoothly.
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AI reshapes design and demand forecasting
Fashion brands experience comparable advantages, though in distinct ways. AI examines customer searches and sales patterns to replace intuition with evidence-based choices. Demand forecasting becomes more precise, allowing brands to produce only what is necessary, reducing waste and markdowns. Design processes also accelerate. Digital prototypes enable designers to modify garments before physical samples are created, while image recognition retrieves past designs along with associated costing and supplier details instantly. These connected systems create significant efficiency gains—designers can upload an image of a previous style and instantly find similar products, complete with costing, materials, and supplier information.
Inventory management improves further. Brands such as Zivame have streamlined operations by adopting unified platforms, ensuring consistency across online, in-store, and mobile inventory. Shoppers perceive the difference, a cohesive experience whether engaging with a website or visiting a physical location. The same connected data also enables brands to move faster in product development, improve collaboration, and accelerate innovation.
The true benefit emerges when brands and manufacturers operate from the same data foundation. Adidas’s digital guidelines, for instance, transform suppliers like Classic Fashion into enduring partners. Faster approvals, reduced delays, and fewer last-minute adjustments strengthen these relationships. Indian manufacturers may not always be the biggest, but they can become the easiest companies to work with. Fast communication, connected systems, reliable data, and complete visibility can become India’s competitive advantage. Many manufacturers are expanding into production phases to offer buyers shorter lead times and better control over production, creating a significant opportunity for India to position itself as a competitive global supplier.
Sustainability regulations demand flawless data tracking
This integration is increasingly critical as Europe enforces stricter sustainability regulations. Digital product passports will soon demand proof of a garment’s origins and production methods. Without accurate data, companies face exclusion from major markets. Good data will no longer be optional, it will become essential for global trade, ensuring compliance with evolving sustainability standards.
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Outdated systems pose the greatest challenge. Much legacy software was designed for isolated operations rather than cloud-based or AI-driven environments. Integrating AI into these systems often requires stitching together incompatible tools, leaving vulnerabilities where flawed data can enter. The expense of upgrading involves financial costs, employee training, and network security. However, maintaining obsolete workflows carries even greater risks, as modern professionals expect intuitive, mobile-accessible, and collaborative software. Replacing legacy systems is no longer a technical requirement, it is a strategic choice affecting efficiency, innovation, and long-term viability.
Cloud platforms unlock AI’s full potential
WFX exemplifies this shift by offering a cloud-based platform that consolidates ERP, PLM, sourcing, and production planning into a single interface. By linking all functions, it provides AI with the necessary context to generate meaningful insights rather than speculative outcomes. Early adopters, including both global brands and manufacturers, are embedding AI into daily operations, converting data into faster and more informed decisions. The platform’s design ensures that data is connected in one place, giving AI the complete business context it needs to deliver real value.
Current technology investments will shape which companies dominate the industry in the future. Those that prioritize data as a competitive asset, rather than an incidental consideration, will determine the sector’s leadership. Fashion businesses will increasingly need to think and operate like technology companies that happen to make fashion, rather than fashion companies that simply use technology.
