There is a particular story that fashion’s sustainability sector tells about itself, and it is a convincing one. It involves data. It involves platforms, algorithms, and dashboards. It involves supply chains made transparent, emissions measured at the level of individual SKUs, and carbon footprints tracked across five tiers of manufacturing with the precision previously reserved for aerospace logistics. It is a story of an industry being digitally transformed: made legible, measurable, and, the implication goes, accountable.
The story is true, as far as it goes. The technology it describes is real, it is working, and it represents a genuine improvement on the opacity that characterised fashion supply chains a decade ago. The problem is where the story stops.
Why the Industry’s Digital Revolution Is Solving the Wrong Problem First
Because the technology that has attracted the most capital, the most press attention, and the most enthusiastic brand adoption is technology that makes fashion’s existing processes more visible. What the industry actually needs, to achieve the circularity and sustainability outcomes it has publicly committed to, is technology that makes those processes materially different. Visibility and transformation are not the same thing. And in the gap between them, an enormous amount of fashion’s sustainability credibility is quietly leaking away.
The Terms of the Debate
Fashion for Good, the Amsterdam-based innovation platform whose accelerator programme has backed some of the most significant sustainability technologies in the industry, has developed a framework for thinking about this divide that cuts through a great deal of confusion. It distinguishes between hard tech and soft tech, and the distinction is both technically precise and politically revealing.
Hard tech, in this framework, encompasses technologies that require significant capital investment and long development cycles to bring to market. Textile recycling infrastructure. Bio-material creation. New fibre chemistries. The physical systems required to collect, sort, process, and remanufacture garments at the end of their commercial lives. These technologies are difficult to develop, expensive to deploy, slow to scale, and essential for any version of fashion circularity that involves actual materials returning to actual production rather than simply being described, accurately or not, as capable of doing so.
Soft tech encompasses the digital layer: supply chain traceability platforms, carbon measurement tools, AI-powered demand forecasting, digital product passports, and the range of SaaS solutions that help brands understand, report on, and communicate the environmental profile of what they are making. These technologies are faster to develop, cheaper to deploy, more immediately legible to investors and compliance officers, and genuinely useful within the limits of what they can achieve.
The central tension of fashion’s sustainability technology landscape is that capital flows predominantly toward the second category while the first is what the physical transformation of the industry actually requires. Soft tech is investable in the way that hard tech is not. It is scalable in the way that building a recycling facility is not. It generates recurring software revenue in the way that a bio-material production plant does not. And it can demonstrate results, in the form of dashboards and reports and verified data flows, on a timeline that satisfies the quarterly expectations of commercial partners, while the hard tech that would actually change what happens to a garment at the end of its life is still, in most cases, years from industrial readiness.
This is not an argument against soft tech. It is an argument for honesty about what soft tech can and cannot do, and about the risks of treating the digital transformation of fashion as a proxy for the material transformation that the planet’s chemistry is waiting for.
What the Platforms Are Building
To understand the soft tech field fairly, it helps to look at what its leading companies are actually doing, because the best of them are doing something considerably more sophisticated than the word “software” sometimes implies.
TrusTrace, the Stockholm-based supply chain traceability company founded in 2016, has built what it describes as a market-leading platform for product traceability and compliance across fashion, footwear, and textile supply chains. With over a billion products now tracked through its platform, and clients including Adidas, Asics, Brooks Running, Tapestry, and Primark, TrusTrace has established itself as the infrastructure layer through which global fashion brands are beginning to answer a question that the industry has historically been spectacularly reluctant to ask: where does this garment actually come from?
The platform enables brands to trace materials from fibre manufacturer through spinner, wet processor, fabric manufacturer, and garment maker, inviting suppliers at each tier onto the system to share data and documentation. It provides certifications, production facility information, product sustainability labels, and, through a partnership with life cycle assessment platform PEFTrust, the ability to generate precise Product Environmental Footprint scores that feed directly into emerging regulatory reporting requirements. The result, for a brand that uses it seriously, is a supply chain that is not merely claimed to be traceable but is demonstrably, verifiably so, with data that survives the scrutiny of regulators, auditors, and the increasingly exacting expectations of institutional buyers.
The company raised twenty-two million euros in growth investment in early 2024, a figure that reflects both investor confidence in its commercial trajectory and the broader market recognition that supply chain traceability has shifted from a voluntary sustainability commitment to a business-critical compliance capability.
Made2Flow, a Berlin-based company founded in 2019, operates in the adjacent territory of environmental impact measurement and decarbonisation. Its platform uses machine learning and multi-source data validation to track metrics including water usage, waste, and greenhouse gas emissions at the level of individual SKUs. Crucially, it has solved one of the most persistent practical barriers to supply chain data collection: the requirement for supplier onboarding. Its off-system data-gathering methodology enriches supply chain datasets without requiring each supplier to learn a new platform, removing the friction that has caused many well-intentioned traceability programmes to stall at tier one. The platform identifies impact hotspots at both product and facility levels and generates recommendations with an average payback period of under twenty months, turning sustainability measurement into a commercially defensible investment rather than a cost centre.
Both companies are building infrastructure that the industry genuinely needs. The question is not whether that infrastructure is valuable. It is whether, when a brand has deployed it, the physical reality of how garments are made and what happens to them at end of life has changed. For most brands, in most cases, the honest answer is not yet.
The Digital Product Passport and Its African Problem
The regulatory context for soft tech investment is changing with a speed that has caught many brands in the middle of their digital transformation journeys and compelled a level of urgency that market incentives alone had failed to produce.
The European Union’s Digital Product Passport, being implemented under the Ecodesign for Sustainable Products Regulation, will require every textile product sold on the EU market to carry a verified digital identity containing information on materials, fibre composition, chemical compliance, environmental footprint, supply chain provenance, recyclability, and repairability. The regulatory timeline is specific: delegated acts defining the technical requirements for textiles are expected to be adopted around 2027, with basic DPP requirements phasing in from 2028 and a full circular DPP covering entire lifecycle data required by 2030. Non-compliant products will not be permitted to enter the EU market. The regulation applies based on where products are sold, not where they are made.
This last point carries consequences for African textile producers and fashion brands that are rarely discussed in the European sustainability policy conversation, and deserve considerably more attention than they receive.
An artisan textile producer in Abeokuta, a fashion brand manufacturing in Accra, or a garment factory in Nairobi: if any of these businesses exports to European markets or supplies European brands, the Digital Product Passport requirements apply to them fully. They will need to generate machine-readable data, structured and interoperable with EU technical standards, covering material composition, supplier traceability, and environmental footprint metrics, for every product that enters the European market. The EU regulation does not provide a transitional arrangement for producers in lower-income countries. It provides a compliance deadline.
The compliance infrastructure for meeting these requirements is not equally distributed. The platforms that enable DPP generation are priced for the operational budgets of European and North American brands. The data architecture required to generate interoperable, standards-compliant product passports assumes a level of digital infrastructure in production facilities that does not universally exist across the African manufacturing sector. The auditing and certification processes that underpin supply chain claims have historically been built around Western supply chain geographies and adapted, imperfectly, to others.
This is not an argument against the Digital Product Passport as a policy instrument. Greater transparency in fashion supply chains is genuinely necessary, and a regulatory mechanism that makes it mandatory is more likely to produce it than market incentives alone. The argument is that a transparency requirement designed primarily with European supply chains in mind, implemented on a timeline that assumes existing digital infrastructure, and enforced at the point of market access rather than at the point of production, creates compliance costs that fall disproportionately on the producers who are already least advantaged in the global fashion system.
There is a version of this story in which the DPP, properly supported with technical assistance, access to affordable compliance technology, and realistic implementation timelines, becomes a mechanism for formalising and elevating the visibility of African-made goods in European markets, making their supply chain integrity demonstrable where it was previously merely assumed. There is another version in which it functions as a technical barrier to entry that concentrates the compliance advantages with the brands and producers who already have the data infrastructure to meet it. Which version prevails depends on decisions being made now, largely in Brussels, and largely without the input of the producers most affected.
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What AI Can and Cannot Fix
The role of artificial intelligence in fashion’s sustainability conversation has expanded rapidly, and with it a corresponding tendency to attribute to AI the capacity for systemic change that only physical infrastructure can actually deliver.
Where AI demonstrably works is in waste reduction through demand accuracy. The fashion industry’s overproduction problem is, in economic terms, vast. Estimates suggest that approximately forty percent of clothing produced globally goes unsold, and the Business of Fashion has reported that the industry’s excess stock represented between seventy and one hundred and forty billion dollars in lost sales value in 2023. This is waste generated before a garment reaches a consumer, and it is waste that better demand forecasting could meaningfully reduce.
AI-powered forecasting analyses historical sales data, social media trend signals, search patterns, and regional demand variations to produce production planning inputs that are significantly more accurate than the human buyer intuition and historical-average models that most of the industry still relies on. The scale of improvement is meaningful: an average-sized apparel company that deploys AI-driven planning can reduce remaining fabric rolls by around fifteen percent, while brands that integrate these tools at a system level achieve waste reductions that register in both environmental and commercial terms. Zara works with an AI partner to analyse more than three million social media images daily, using the findings to ensure that eighty-five percent of its production takes place in-season, sharply reducing the static inventory that has historically been destroyed, discounted, or shipped to secondary markets in the Global South.
AI also contributes to textile-to-textile recycling readiness, by identifying fibre composition in mixed-material garments that traditional sorting processes cannot disaggregate. Technologies like Refiberd, which combines hyperspectral imaging with AI to detect and separate fibre composition, make chemical recycling of blended textiles technically feasible in ways that manual sorting cannot achieve. This is AI operating in the service of hard tech: the digital intelligence is not the solution by itself, but it enables the physical recycling infrastructure to work on materials it previously could not process.
The limitation appears at the boundary between prediction and production. AI can tell a brand how many units to make, and, increasingly, how to make them with less waste. What it cannot do is create the physical systems required to ensure that the materials in those units can be recovered, recycled, and returned to production at the end of the garment’s life. That requires infrastructure: sorting facilities, chemical recycling plants, bio-material production at scale, collection systems, and the logistics that connect them. None of this is software. None of it is cheap. And none of it is moving at the pace that the industry’s public commitments imply.
Where the Capital Isn’t Going
Fashion for Good’s analysis is direct about this asymmetry. Hard tech, with its capital-intensive requirements and long development cycles, enables the fundamental shifts, such as material recycling and advanced manufacturing, that support a genuinely circular economy. Soft tech offers scalable digital solutions that deliver quicker efficiency gains. Balancing investment in both is essential. The current investment playing field is not balanced.
The reasons for the imbalance are structural, not conspiratorial. Venture capital moves toward returns on predictable timelines. A SaaS platform with recurring revenue and a clear path to scale is fundable in ways that a chemical recycling facility with a ten-year development timeline and uncertain off-take agreements is not. The regulatory environment that would make hard tech investment commercially necessary has only recently begun to materialise. The brands that would need to commit to purchasing recycled materials at volume have mostly declined to make the contractual commitments that would de-risk the investment.
The result is a technology ecosystem that is, at the soft tech end, genuinely impressive and, at the hard tech end, critically underfunded relative to what the industry’s scale requires. Less than one percent of recycled materials on the market are currently made from old clothes. The textile-to-textile recycling infrastructure to change this does not yet exist at anything close to the scale needed. The bio-material technologies that could replace virgin synthetic fibres are, in many cases, proven at laboratory scale and stalled at industrial transition.
Fashion’s sustainability sector is, in this sense, facing a version of a problem familiar from other industries where the digital and the physical operate at different tempos. The digital transformation is proceeding. The physical transformation is waiting for the conditions that would make it viable, conditions that depend partly on capital, partly on regulation, and partly on the willingness of the industry’s largest players to make commitments that cost something in the near term in exchange for outcomes that benefit everyone in the longer one.
The Honest Accounting
There is a number that provides useful context for this entire conversation. The McKinsey State of Fashion 2025 report found that only eighteen percent of fashion executives rank sustainability as a top-three business risk. The European Commission’s Green Claims Directive found that fifty-nine percent of sustainability claims made by brands in 2024 were vague, misleading, or unverifiable. The 2024 Fashion Transparency Index found that no major brand has yet achieved full supply chain traceability.
These numbers do not negate the genuine progress being made by the companies described in this article, or by the broader ecosystem of innovators working on both the soft and hard tech problems. They provide the context within which that progress is occurring, and they suggest that the gap between what the industry says about its technology investments and what those investments are actually delivering remains, by any honest measure, very wide.
The platforms are real. The data is improving. The regulatory pressure is building and will not reduce. But the circularity that fashion has promised requires garments to be recovered, sorted, recycled, and returned to production, not merely tracked and measured on their way to the same endpoints they have always reached. Soft tech is essential infrastructure for a sustainable fashion industry. It is not a substitute for building one.
