As responsibility in fashion becomes increasingly shaped by shared frameworks, standardized metrics, and system-level requirements, brands are no longer operating in purely self-defined value spaces.
What emerges is a model where governance is embedded into the product itself, and where data becomes the foundation for compliance, comparability, and long-term value.
Responsibility as governance, not brand positioning
The transition currently happening in the field of fashion due to the EU Green Deal is particularly pronounced with regards to sustainability reporting moving from a voluntary “brand value narrative” approach to mandatory governance frameworks.
This transition is structural across the entire industry. However, its impact is most visible in Small and Medium-Sized Enterprises (SMEs), which constitute the vast majority of the global fashion ecosystem. While multinational corporations possess the capital to absorb compliance costs, SMEs reveal more clearly the operational challenges of navigating this shift toward responsibility as an embedded condition of doing business.
The Resource Gap in Governance
For a small brand, the shift from brand value narrative to governance is not merely a marketing adjustment; it is a fundamental restructuring of operations. Unlike larger entities with dedicated ESG departments, SMEs often operate with lean teams where the founder or a small production manager oversees the entire supply chain.
The primary challenge lies in data acquisition and verification. Accountability frameworks require granular, standardized data that many tier-2 and tier-3 suppliers (spinning mills, dye houses, and farms) are not yet equipped to provide.
While this challenge exists across the industry, it becomes particularly visible for smaller brands, where lower order volumes reduce the leverage to demand transparency from suppliers. As a result, brands risk being constrained not by intent, but by their ability to access and structure the data required by emerging governance systems.
The transition from brand-led reporting to governance is therefore not only a question of compliance, but of infrastructure. It represents one of the most significant structural changes the fashion industry has faced in decades.
Two emerging systems are beginning to address this shift: Digital Product Passports and AI-driven data infrastructure.
Digital Product Passports (DPP)
The introduction of the Digital Product Passport is often viewed as a compliance burden. In reality, it represents a foundational system for structuring and validating product-level data.
The DPP functions as a standardized data layer that follows a garment throughout its lifecycle, connecting product information, supply chain data, and verification mechanisms into a single framework.
For brands, this enables a shift from narrative to verifiable data.
It allows:
- validation of product-specific claims, particularly in areas where smaller brands often lead, such as material innovation or craftsmanship
- participation in circular systems through standardized, product-level information without requiring proprietary infrastructure
Rather than adding complexity, the DPP establishes a shared system through which data becomes usable, comparable, and actionable.
Artificial Intelligence (AI) as a Data Infrastructure Layer
While the shift to governance introduces significant operational complexity, AI is emerging as a critical enabler in managing this transition.
Within accountability frameworks, AI is no longer a peripheral tool. It is becoming part of the infrastructure required to process and structure large volumes of supply chain data.
One of the core challenges across the industry is the “data gap” beyond direct suppliers. AI-driven systems, particularly those leveraging Natural Language Processing (NLP), can absorb and standardize unstructured data from supplier documentation, certifications, and audits across multiple tiers.
This transforms what has traditionally been a manual and reactive process into a more structured and proactive system.
It also enables earlier identification of risks, such as non-compliant sourcing regions or outdated certifications, supporting alignment with emerging regulations such as the EU’s CSDDD.
DPP and AI as Complementary Systems
The scale of data required for product-level reporting, particularly within Digital Product Passports, makes manual processes unfeasible.
AI provides the necessary scalability.
It enables:
- automated impact assessments, including the potential to support real-time Life Cycle Assessments (LCA)
- predictive compliance, allowing brands to anticipate regulatory impacts and adjust before production decisions are finalized
Together, DPP and AI shift compliance from a retrospective reporting exercise to a forward-looking, operational system.
Conclusion
For the fashion industry, the move toward embedded governance is a structural shift rather than a temporary requirement.
While it demands a significant upgrade in how data is managed and integrated, it also establishes a system where product-level information becomes the basis for credibility, comparability, and participation in the market.
What is emerging is a model where value is increasingly tied not only to brand positioning, but to the ability to structure, verify, and activate product data across systems.
How Renoon supports this transition
Renoon provides the infrastructure to operationalize this shift from narrative to governance.
By connecting product, supply chain, certification, and environmental data into a structured system, brands can generate and manage Digital Product Passports at scale while ensuring data remains consistent, verifiable, and usable across compliance, operations, and customer touchpoints.
Through integrations with existing systems such as ERP, PLM, and CRM, Renoon enables brands to move from fragmented data and manual reporting to a continuous, product-level data flow that supports both regulatory requirements and business use.
Rather than treating compliance as a separate process, brands can embed it directly into their product architecture, turning structured data into a foundation for transparency, efficiency, and long-term value.
👉 Explore our Advisory Program to start structuring your product data and implement Digital Product Passports or book a demo.
About Stine Hedegaard
Dr Stine Hedegaard is a sustainability strategist with over 15 years of experience in fashion sustainability. Currently serving as the Course Leader in MA Fashion Marketing & Sustainability at London College of Fashion, her career spans roles at H&M Group, Pangaia and Global Fashion Summit, leveraging a PhD in Organization and Management to bridge industry and academic approaches to sustainability.
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