New supply chain regulations push retailers toward AI traceability
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Fashion retailers are using artificial intelligence to map complex supply chains as regulators demand more information about where products come from, how they are made and the environmental and labor risks involved.
Companies including Gap, H&M and ASOS are using AI-supported supply chain technology to trace suppliers and identify risks that can be difficult to detect through conventional systems.
The investment comes as regulators in the US and Europe place more responsibility on companies to document their products and supply chains. Traceability, once closely associated with corporate sustainability programs, is becoming a compliance and operational requirement.
For apparel companies, the task is particularly difficult. A single garment may pass through several countries before reaching a store. Cotton can be grown in one market, processed in another and turned into a finished garment somewhere else. Buttons, labels and packaging can involve additional suppliers and locations.
Each stage produces information that companies may need to collect, verify and connect to the finished product. AI is increasingly being used to process that information.
Supply chain compliance is becoming a data problem
Supply chain visibility has long been difficult for fashion companies because direct suppliers represent only one part of a production network.
A retailer might know the factory responsible for assembling a shirt but have less visibility into the mill that produced its fabric or the farm that supplied its cotton.
Business Insider reported that ASOS has used AI-supported traceability to reach the farm level in parts of its supply chain. Fashion consultant Kenchen Bharwani told the publication that this degree of visibility remains uncommon across the industry.
Pressure to close those information gaps is increasing. In the US, companies face requirements including the Uyghur Forced Labor Prevention Act, which restricts the importation of goods made wholly or partly in China’s Xinjiang Uyghur Autonomous Region or by certain identified entities unless importers meet applicable evidentiary requirements.
Extended producer responsibility policies are adding another set of obligations, with requirements varying by jurisdiction. Europe is developing its Digital Product Passport system under the Ecodesign for Sustainable Products Regulation. The system is designed to provide structured digital information about products and improve supply chain transparency.
The European Commission launched the Digital Product Passport Registry and a testing environment July 20. Economic operators will be required to register passports for products covered by applicable rules.
Depending on the product category and legislation, a Digital Product Passport can contain information about materials and components, environmental impacts, durability, repairability, recyclability and other product characteristics.
Consumers may eventually access this information through a data carrier, such as a QR code attached or linked to a product. Textiles are among the priority product categories in the EU’s first Ecodesign for Sustainable Products Regulation working plan, with an indicative 2027 timeline. Businesses will have a transition period of at least 18 months after the relevant delegated acts are adopted.
For retailers operating across several markets, the rules create a practical challenge. Product and supplier information must be collected from systems that were not necessarily designed to communicate with one another. Spreadsheets become difficult to manage when hundreds or thousands of suppliers are involved.
AI cuts the time needed to process compliance records
The potential value of AI goes beyond generating documents faster. The technology can connect information held across supplier records, purchase orders, audit reports and compliance systems.
Inspectorio, a supply chain software company whose customers include Gap and Mango, told Business Insider that a manual compliance workflow can take at least 30 hours for each purchase order.
The work can involve determining which regulations apply, organizing product information, contacting suppliers for missing records, checking the information and preparing regulatory reports.
Inspectorio said its AI agents can build a chain of custody, collect documents and prepare reports for specific regulations. The company estimates that the process can be reduced to about one hour, including human review.
If replicated across large volumes of purchase orders, that reduction could materially change the cost and speed of compliance work.
The information collected for compliance can serve another purpose. Retailers can use supply chain systems to identify disruptions before they affect customers.
AI tools can analyze information associated with factory delays, weather exposure, sourcing problems and human rights risks.
Business Insider reported that H&M has used AI to identify flood risks and factory closures in Bangladesh, allowing the retailer to reduce some production exposure in the country.
According to the report, Adidas has used the TrusTrace platform alongside the World Resources Institute’s Aqueduct tool to identify mills exposed to flooding. Vera Bradley has used TrusTrace technology to screen US Customs and Border Protection risk databases for forced labor concerns.
Smaller companies can apply the same principle without deploying a large enterprise platform. OMJ Clothing, a custom suit maker in Charlotte, North Carolina, used Anthropic’s Claude to develop a dashboard for monitoring factory orders. The company can source from 10 factories at once and previously might not discover a production delay until a customer asked about an order.
The dashboard brings factory information into one place, giving the company an opportunity to spot delays earlier. The examples show how compliance technology and supply chain management are beginning to overlap. Information collected to document where a product came from can help a company identify where its next disruption may occur.
AI cannot compensate for missing supplier information
AI faces a basic constraint. It can process supply chain information, but reliable traceability still depends on credible source data. Tracing a product to a direct factory is different from establishing visibility across several tiers of suppliers.
ASOS reaching the farm level shows what deeper traceability can look like, but Business Insider’s reporting indicates that this degree of visibility remains unusual across the wider industry.
That gap matters as regulatory requirements push companies toward more structured product records.
Under the EU system, responsibility for creating an accurate Digital Product Passport rests with the economic operator placing the relevant product on the market. Product information must remain accurate across its lifecycle, although specific requirements will depend on the rules governing each product category.
The European Commission’s registry provides infrastructure for registering unique product identifiers and associated metadata, while the underlying product information remains decentralized. Registration can be handled through a user interface or an API, allowing businesses to connect the registry with existing digital systems.
The structure points toward a supply chain in which product information is increasingly machine-readable and exchanged among businesses, regulators and consumers.
AI can make that information faster to process. It does not remove the need for suppliers to provide accurate records. That distinction could put more pressure on retailers and manufacturers to improve data collection deeper in their supplier networks.
For retailers, the business case extends beyond demonstrating environmental credentials. Detailed supplier information can support customs compliance, regulatory reporting, risk detection and production decisions. As textile-specific Digital Product Passport requirements move closer, companies selling into Europe will have more reason to connect those functions.
The next phase of supply chain technology may depend less on which company has the most sophisticated AI model and more on which company can establish the most reliable chain of product and supplier information. For an industry accustomed to managing global production networks through fragmented records and supplier spreadsheets, better data could prove more consequential than faster AI.
Source:
Business Insider