AI is transforming the end-to-end fashion supply chain from speed of production to sustainability with experts telling Just Style its importance can no longer be ignored.

Technology has always played a role in the fashion supply chain albeit a much more dominant one as the years have gone on. But as the fashion industry gets familiar with the intricacies of AI, one thing is clear: it is going to be game changing.

Previously, technology was mostly used to automate manual processes, create greater efficiencies and weave speed into businesses that trade across the world and are reliant on overseas suppliers. 

Max Easton, the vice president of partnerships at Smartex.ai, which specialises in AI for the textile and apparel industry, points out these efficiency gains helped fashion brands and retailers to drive profit. 

Now, in the era of ultrafast fashion, he says you have players like Shein which achieve higher revenues and higher inventory turnover compared to legacy fast fashion brands.

“A lot of this comes from supply chain innovation – from data collection, communication and utilisation – as well as better processes. So it has to be a priority for the leading textile factories to stay competitive and attract the best and highest orders,” he explains.

Many fashion companies are also turning to technology for assistance as the pressure to align with global sustainability agendas mounts.

Global Fashion Agenda (GFA)’s director of impact Christina Iskov tells Just Style: “For brands, the likes of blockchain and AI-powered tracking can improve supply chain traceability. 3D design tools and AI insights can reduce material waste and speed up production and on-demand and automated production can minimise overproduction and waste. 

“By harnessing consumer data, AI can analyse distinct body types, fine-tuning fit and offering virtual try-ons to reduce return rates. This is crucial for customer experiences but also sustainability, as we know that in Europe, on average, one in every five garments sold online is returned and approximately one third of returned clothing ends up being destroyed.”

In 2025 and beyond, the demand for technology and its integration within the fashion supply chain is unlikely to wane. If anything, it is evolving, and at an accelerated pace. 

While technologies like 3D design and printing will continue to be heavily leveraged, there is one particular technology that is driving the evolution of its predecessors and will feature in a much bigger way across the fashion supply chain  — Artificial Intelligence (AI).

How influential will AI be across the fashion supply chain?

A report from GlobalData suggests AI will be worth $1tn in 2030, having grown at a compound annual growth rate (CAGR) of 39% from $103bn in 2023.

The report says: “AI is becoming a critical component for improving sustainability for retail and apparel companies and ensuring compliance with global regulations. With companies requiring intensive due diligence to identify and locate supplies within supply chains, manual tracing is a task alleviated by AI in cases where thousands of suppliers are used. 

“As legislation surrounding due diligence in supply chains becomes more common, AI can help retailers track and manage supply chains more effectively, ensuring they meet legal and ethical standards. This is pertinent after recent legislation requiring greater transparency in supply chains, with countries such as Canada and the UK requiring fashion companies to publicise their supply chain reports.”

How is AI transforming the way the fashion supply chain operates?

GFA has introduced the Innovation Forum which presents a curated community of the world’s leading sustainable solutions. One of those pioneers is Hakio, an AI-powered platform to help companies make more accurate predictions about their future sales to optimise inventory levels.

Maxime Patte, CEO and co-founder of AI-driven virtual try-on platform Veesual, points to Autone, a start-up focused on allocation optimisation which he says is a great example of improving the supply chain. 

Powered by AI, Autone enhances garment distribution across stores and e-commerce warehouses, ensuring inventory aligns with real-time demand.

Further, he notes AI is already transforming how brands design and plan collections. Instead of relying solely on intuition, they can now analyse trends, predict demand, and even generate designs. This will reduce waste and speed up production. Virtual prototyping will also cut down the need for physical samples.

In manufacturing, automation and AI-powered forecasting will help brands produce more efficiently and avoid overstock, adds Patte.

“The fashion supply chain of the past was wasteful and slow, which led to excess inventory, ethical concerns, and rising production costs. AI, for example, has had a huge impact on a brand’s ability to forecast demand and therefore reduce overproduction.”

Iskov agrees, stating: “AI-driven analytics can predict trends more accurately, helping brands reduce overproduction and waste.

“It also holds the power to quickly suggest more sustainable materials, thereby making the sourcing process easier. Crucially, AI can support brands to optimise inventory, reduce returns, and implement circular fashion models. All of these measures are not just beneficial for sustainability efforts but vital for overall brand resilience,” she says.

Beyond this, and at a retail level, Patte says he sees AI-driven product visualisation as a game-changer, though it is one area that is at present, overlooked.

“While personalisation and demand forecasting are widely discussed, AI’s potential to reinvent how products are presented online is just beginning to be tapped. Moving beyond static imagery to dynamic, on-demand visualisation opens entirely new ways to engage with shoppers,” he says.

“Until now, brands were constrained by photoshoots, limiting how they could showcase products online. With AI, the possibilities have expanded dramatically — brands can generate far more visual content to inspire shoppers and help them buy with confidence. The business impact is huge: Higher conversions, increased basket size, reduced returns and stronger customer loyalty.”

Who is leading the way with AI fashion solutions?

AI solutions targeting the fashion and textile industries are aimed at contributing to a more efficient, sustainable and profitable industry and are constantly being developed and adopted.

Ekoten Tekstil, a subsidiary of Sun Tekstil, recently introduced AI-powered defect detection. The company’s real-time AI monitoring system improves precision, minimises waste, and significantly reduces the environmental impact of textile production.

“Our AI-driven systems allow us to detect and correct textile defects before they lead to unnecessary reprocessing, reducing waste and optimising resource use,” explains Sabri Ünlütürk, vice chairman of the board of Sun Tekstil and Ekoten Tekstil. “This technology strengthens both efficiency and sustainability in our manufacturing processes.”

Meanwhile, UK-based fashion and textile manufacturer, Fashion Enter, has devised a solution to navigate the common bugbear of customers still wanting to see a physical sample while trying to lower waste.

Fashion Enter has set up a knitwear sampling service that combines AI with a physical form.

“AI needs to embrace both digital and physical form combined in one software/hardware package then have the speed of response that buyers have,” explains Fashion Enter’s CEO Jenny Holloway. 

The system Fashion Enter is introducing will allow samples to be produced for an AI sign off with a physical sample then produced at Fashion Enter. The design can be sent to all major knitwear manufacturers around the globe allowing manufacturers to go straight into production.”

Elsewhere, AI is also influencing sizing and-fit tech. With the cost to retailers of returns each year, it’s not hard to see why.

According to a National Retail Federation (NRF) report, in 2023, for every $1bn in US sales, the average retailer incurred $145m in merchandise returns with shoppers taking advantage of policy, process and system gaps.

The report titled ‘2023 Consumer Returns in the Retail Industry,’ explains total returns for the US retail industry amounted to $743bn in merchandise and the total returns rate as a percentage of sales was 14.5%

Sizing and fit has been cited as one of the primary reasons for returns and over the years numerous innovators have developed platforms for online retailers to help navigate the issue.

According to GlobalData UK survey, 89.8% of respondents rated fit at least a seven out of 10 in terms of importance coming just slightly ahead of comfort at 89.6%. 

Surprisingly, it also ranked ahead of both value for money, quality and price, which were rated important to 89.5% and 83.4% of respondents, respectively. 

Investing in fit technology and ensuring consistent sizing across ranges will help clothing brands enhance customer loyalty.

Veesual has rolled out two new product personalisation features to improve the online fashion shopping experience while lowering buyer friction.

The new additions, Switch Model and Multi-Sizing, are designed to address common e-commerce challenges related to fit predictions and customer confidence.

The Switch Model feature is designed to allow online shoppers to choose a model that mirrors their own body shape. With Switch Model, customers can view products on their selected model from various perspectives, including front and back views. This gives shoppers a realistic sense of how clothes will look and fit on their bodies.

While its Multi-Sizing tool is designed to enhance customisation by displaying a garment on a chosen model in three different sizes: The recommended size, one size up, and one size down. This feature enables customers to better visualise how various fits may align with their personal style preferences.

What are the primary barriers to adopting AI for fashion companies?

Cost is a key barrier to adopting or scaling tech solutions, asserts Iskov.

Iskov points out: “Implementing AI, AR, or Blockchain can require significant upfront investment in hardware, software, and expertise. Small and medium-sized brands may struggle to afford the high costs associated with adoption, limiting their ability to compete with larger players. 

“However, the evolving regulatory landscape highlights the urgency of such technological innovations with impending legislations set to mandate sustainability practices from brands. Just as much as innovators need targeted investment from those who understand the complexities of the landscape, brands need to be supported in implementing innovations at scale and meeting legislative demands.”

It’s something she believes can be addressed through industry collaboration and her organisation’s recently introduced Trailblazer Programme with global end-to-end sourcing and manufacturing platform PDS, is a great example of this in action.

She explains: “We leverage the shared network and expertise of both PDS and GFA so that innovators gain invaluable insight into industry dynamics. The Trailblazer Programme provides an opportunity for early-stage innovators to receive not only financial support but also invaluable mentorship and guidance from industry experts, equipping them to navigate the evolving landscape and ensuring they are prepared for the changes ahead.”

Holloway also argues the continual investment in software and hardware can’t be left to manufacturers alone, particularly when there is no stability of orders.

She states: “I 100% agree that this integration of tech in the supply chain is the only way forward but I also think it’s about trust and investment in the supply chain for the retailer. What we now need is government procurement contracts that will allow factories the stability to invest in new machinery. I absolutely believe this is on the horizon too.”

Another such barrier to adoption is change hesitancy. Patte says he sees some of the biggest resistance from creative and artistic direction teams.

“Until now, they have been the gatekeepers of brand imagery, ensuring every visual aligns with their aesthetic and identity. The idea of shifting to AI-generated images can raise concerns about losing creative control or compromising brand integrity. The key is demonstrating that AI is not replacing creative direction but expanding its possibilities — allowing teams to generate more content while maintaining full control over the visual output,” he asserts. 

He also describes scalability as a further issue, stating: “While AI can generate unlimited visual assets, ensuring consistency and quality at scale is key. Brands need to trust that AI-generated images will accurately represent their products, especially in fashion, where fabric texture, draping, and fit are crucial. AI alone isn’t enough —quality control processes and expert oversight are essential to validate each image. This is why working with partners who specialise in quality assurance, including sizing accuracy and visual consistency, is critical to ensuring a seamless transition to AI-driven imagery.”

But, he concludes, whatever the obstacles are, they will need to be overcome since AI looks here to stay for the foreseeable future.

He concludes: “In my opinion, AI will be the most transformative technology in the industry, influencing everything from inventory management to customer experience. Brands that embrace it early will gain a real competitive edge.”