The Missing Intelligence Layer in Circular Fashion: CIRQUEL's Afterthoughts on Fashion for Good's 'AI in Fashion Supply Chain 2036'
In April 2026, Fashion for Good published one of the most thought-provoking future-facing pieces the industry has seen this year: “AI in Fashion Supply Chain 2036: How Artificial Intelligence Is Transforming Every Step.”
The article imagines what an AI-native fashion industry could look like ten years from now - from programmable raw materials and predictive manufacturing to autonomous logistics and recycling systems. The piece positions AI not as an “extra tool,” but as the invisible operating system of the entire fashion value chain. And importantly, it is not pure science fiction. Fashion for Good grounds this future in technologies and startups already emerging today, mentioning innovators such as Solena Materials, Avalo AI, and Osium AI, while building on years of research and ecosystem work across circularity, traceability, material science, and supply chain transformation.
Fashion for Good itself has become one of the most influential global platforms for sustainable fashion innovation, backed by partners including Laudes Foundation and inspired by the Cradle-to-Cradle philosophy of co-founder William McDonough. Through collaborations with brands like adidas, Zalando, Target, C&A, and Kering, the organisation has consistently pushed the industry toward systemic circularity rather than isolated sustainability initiatives.
The AI-native supply chain is already emerging
One of the strongest messages from the Fashion for Good article is that the supply chain of 2036 will no longer react - it will anticipate.
AI systems will increasingly predict demand, optimise production allocation, simulate material performance before manufacturing, and dynamically route inventory in real time. The article describes a future where designing a material “looks less like farming and more like pharmaceutical discovery,” with biodegradability, tensile strength, and carbon footprint engineered before anything is physically produced.
This aligns with broader industry forecasts. According to research cited by DataArt, the global AI supply chain market could exceed $157 billion by 2033, while Generative AI applications in supply chains are projected to grow at over 45% CAGR. Meanwhile, publications such as Vogue Business and McKinsey & Company continue highlighting that AI is becoming foundational in areas such as inventory forecasting, compliance, sourcing, and operational resilience.
The logic is clear: fashion’s future competitive advantage will not come only from creativity or branding, but from intelligence embedded into operational infrastructure.
But one critical layer is still missing: Reverse Logistics Intelligence
What Fashion for Good’s vision indirectly reveals - perhaps without fully naming it - is that the industry is still largely focused on intelligence before the sale.
Yet one of fashion’s biggest economic and environmental problems begins after the purchase.
Even in a highly optimised AI-native future, products will still come back. Consumers will still change their minds. Sizing issues will still exist. Rental, resale, subscription wardrobes, and AI-assisted shopping will likely create even more dynamic product movement across ecosystems rather than less. The rise of autonomous purchasing agents may actually increase returns because the person receiving the product may not be the one who selected it in the first place.
And this is where reverse logistics becomes one of the most strategic blind spots of the next decade.
The industry already loses billions annually through returns, overstock, and unsold inventory. According to multiple analyses referenced by Vogue and BCG, fashion overproduction and excess stock remain among the sector’s largest structural inefficiencies. Yet most brands still process returns with surprisingly limited structured intelligence.
A returned garment often generates more operational complexity than manufacturing the item itself, but the data extracted from that moment remains extremely poor.
The future of fashion needs post-purchase intelligence
At CIRQUEL, we believe the next frontier of AI in fashion is not only predictive manufacturing, it is predictive post-purchase infrastructure. While many companies are redesigning the front end of the supply chain, CIRQUEL focuses on the intelligence layer after the item leaves the warehouse: understanding product condition, anomaly detection, return reasoning, repurposing pathways, and optimal next routing.
Today, in 2026, CIRQUEL already enables brands to assess returned products using AI-driven visual intelligence and structured return data. Through image recognition, condition analysis, and customer-generated signals, including vocal or written return explanations, brands can begin understanding not only what came back, but why it came back and what should happen next.
That matters because every return is more than an operational event. It is a dataset.
A damaged zipper may indicate a manufacturing issue. Repeated complaints about fabric feel may expose sourcing inconsistencies. High return concentration from a specific demographic or climate region may suggest product-market mismatch. At scale, reverse logistics becomes one of the richest feedback systems in the entire fashion ecosystem. And unlike speculative AI futures, this infrastructure can already be implemented today.
From circularity as theory to circularity as infrastructure
Fashion for Good’s article paints an exciting picture of a future where AI coordinates materials, production, logistics, and recycling in near real time. But circularity only works if products continue generating value after disruption- not only before purchase.
The reality is that circularity cannot depend solely on better materials or smarter manufacturing. It also depends on how intelligently brands manage uncertainty once products are already moving through the market.
That means:
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detecting condition before unnecessary transport,
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forecasting resale or refurbishment potential,
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reducing landfill outcomes,
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automating routing decisions,
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and continuously learning from every returned item.
This is precisely where CIRQUEL positions itself: as an AI returns intelligence platform helping brands transform reverse logistics from a cost centre into a circular value system.
In many ways, the future imagined by Fashion for Good is already beginning. The question now is not whether AI will transform fashion, it is whether brands are building intelligence across the entire lifecycle of the product.
Because in the next decade, the brands that win will not simply manufacture smarter. They will learn faster from what comes back.
Sources & References:
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Cloudflare Radar
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Vogue Business coverage on AI, circularity, and supply chains
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McKinsey & Company reports on AI and fashion operations
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Boston Consulting Group analyses on inventory and overproduction
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Academic references on AI in fashion and supply chain optimisation
Anna Warchalowska is CEO and co-founder of Cirquel. If you are a brand, investor or partner interested in circular fashion, sustainable returns, or commercial partnerships, we would love to connect at cirquel.co.