Fashion Has A Waste Problem. Can AI Solve it?


Fast fashion is undeniably one of the biggest contributors to environmental pollution. On average, consumers throw away 60 per cent of their clothes in a year.

In 2020 an estimated 18.6 million tonnes of clothing ended up in landfills. Simultaneously, sustainable fashion, with the help of artificial intelligence (AI), is gaining ground.

A study conducted by IBM in 2020 asked respondents which technologies will have the greatest impact on sustainability in the future, and one third answered AI. But the use of AI in fashion has focused invariably on the potential to better predict trends and guide the design process, which leads to purchase predictions.

Customer Purchase Predictions

eCommerce fashion platforms are using augmented reality technology such as virtual in-store navigation, interactive display screens, virtual try-on, virtual fitting rooms, virtual tailors and virtual makeover to keep track of what kind of products the customer is looking for, including shape, size, colour, and even budget.

Top brands like Topshop, Ralph Lauren, H&M, Zara, Burberry, and others are using augmented reality for clothing not only to improve customer engagement and deliver a personalised shopping experience, but reduce inventory wastage. It also helps to keep a record of the filters a customer uses on the web and applications to sort the product based on its AI’s identification patterns, thus reducing carbon footprint.

AI tools help in searching for products by image. eCommerce platforms offer image search features where the customer can put on an image and the AI-powered system is able to understand the components of the image to give suggestions of similar products to the customers. Flipkart’s AI can look at an image, and identify its properties. It can tell things like the colour, and cut.

This is all a part of speculating the upcoming trends in the fashion market which helps brands in budget estimation and sustainable production.

Trend Prediction

AI can identify the trends, the most sought-after apparel in the market. For example, Heuritech predicted current market trends in fashion, keeping in context of Covid-19, to anticipate the trends for summer and fall 2020. This helped fashion retailers to save on their budgets by cutting off excessive off-track production of clothes.

Trend forecasting also provides a means for creatives to back their intuitions with tangible data. Knowing what trend to follow helps to produce the exact quantity of fabric and the exact type, leading to zero wastage. Predictability of fashion trends saves untimely production and minimise wastage of water, as in the case of denim production. From growing cotton to dyeing it to laundering finished products, producing blue jeans consumes a large amount of water. According to researchers, a pair of jeans requires 7,600 litres of water to make it through the production line.

Inventory Check

However, inventory remains the hardest part of all. But AI can keep an automated record of the inventory of each store and can provide for a stock build-up of a specific kind, based on the sale for a particular store. Shopify and Amazon are known to implement inventory check software leading to zero wastage.

SkuVault, TradeGecko, Skubana, Stocky, Sellbrite are some of the inventory management apps that Shopify uses. Automatic inventory syncing across channels, demand and trend forecasting, SKU-level FIFO profitability, and actionable opportunities are some of the inventory check functions that Shopify uses that are aided by AI to enhance inventory process sustainability.

Logging in details of stores helps the sellers keep a track of their in-house stock and their sales. This enhances sustainability of the workforce in general. While demand forecasting enhances proper production size and lessens wastage both in the manufacturing units and in the stores.


Fashion brands are leveraging deep learning to identify manufacturing defects, colour tolerance, and wrinkles. 3D modelling of yarn patterns that simulates flow and fall on the design is a sustainable alternative to synthetic materials.

H&M and Tommy Hilfiger use AI and predictive technology to understand the environmental nuances of every raw material and input into apparel supply chains, thereby making fashion more sustainable. H&M ‘Conscious’ is one such eco-friendly line of clothing. Zara, too, is known to label garments as ‘Join Life’ to promote sustainability.


AI can help consolidate the required material compositions and identify similar previously sourced items enhancing sustainability. Reinforcement learning can also be leveraged for smarter vendor negotiation. This saves cost since raw materials are procured at the best possible rates, also the exact required quantity of raw fabrics are purchased when a smart vendor negotiation is enabled.


AI in design, used in combination with other technologies, can help reduce time to market and create personalised tailored outfits. By leveraging AI, fashion brands can weave, cut, and pattern all at one go, minimising or eliminating scraps, and accelerating go to market. AI can also help in creating entirely new design combinations based on customer preferences and trending styles, and available material for upcycling.


AI can predict trends based on data and customise it to customer preferences and sizes to ensure retailers buy the right quantities. AI can also estimate the success of the styles in conjunction with the marketing effort to reduce overstocking.

Additionally, AI tools can help to match the fit and style for reused/recycled clothes, providing personalised recommendations to customers. For new apparel, based on the trending patterns, AI can adjust the buy/produce quantities for the next drop preemptively in alignment with the marketing budget and ROI. AI-based stylists can help put the look together based on personal style, body shape, and preferences.

To minimise the carbon footprint of the manufacturing units, some brands have taken steps forward. A new study by USwitch found that the brands with the lowest carbon footprints are Adidas, Marks & Spencer, Louis Vuitton and Mango.

Has Sustainability Been Practically Adopted?

Increasingly, designers and fashion brands are embracing AI to push the limits of design, manufacturing, and production.The rising influence of social media and the growing popularity of personalised experience is the driving factor behind the demand for AI in sustainability.

With evolving trends and a consumer base that demands quality and convenience in equal measure keeping wastage at bay, the fashion industry is rightly turning to AI for a fashion forward future, where there’s a collaboration between creative and AI to protect the environment.

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