“The future is not predetermined. The impact of artificial intelligence (AI) depends entirely on how we use it. If we act consciously, design responsibly and act purposefully, AI can become one of the strongest drivers of sustainability in the coming decade,” said Emma Grace Bailey, Director of Sustainability at trend agency Future Snoops (FS). She made this comment during FS’s recent ‘Sustainability No Filter’ webinar on the climate impact of AI.
Although the environmental footprint of AI remains a legitimate concern, the session focused primarily on where AI is already delivering concrete sustainability benefits. FS presents use cases that show how AI is helping brands design better products, reduce waste, optimize supply chains, and mitigate climate and weather-related risks.
FashionUnited presents some examples relevant to the fashion industry:
From product decisions to sourcing resilience: How AI is already driving sustainability in fashion
1. Product design, including optimized sourcing:
AI is increasingly being used to help brands identify materials with a lower environmental impact. Bailey explains that this is done by “scanning global databases, testing combinations, and predicting performance and impact.” Such processes would traditionally take years. This is particularly important since “86 percent of the fiber mix is cotton and polyester,” she notes. This leaves brands vulnerable to climate fluctuations and supply risks.
An example from fashion is the French company Fairly Made. Its AI-powered eco-design tool shows the environmental impact of fabrics and ingredients in real time. “As users adjust the parameters, the product’s overarching climate change score changes in real time,” says Bailey. This illustrates how decisions impact a product’s environmental footprint and the people in the supply chain throughout its life cycle.
2. Virtual sampling to reduce waste
Sampling remains one of the most wasteful processes in fashion. According to Common Objective, 35 percent of materials are wasted before the products even reach consumers, Bailey explained next. AI-supported virtual sampling is proving to be an effective measure here.
Physical patterns are still necessary – “we still have to feel and touch what we create”. Nevertheless, AI-generated digital prototypes enable designs to be visualized, refined and approved before production begins. This reduces the number of samples sent back and forth worldwide.
For example, designer Theophilio collaborated with Raspberry AI for his SS26 collection. Using the platform’s sketch-to-render tool, he was able to “instantly visualize multiple ideas.” According to Bailey, this “accelerated design workflows by 40 percent” and “reduced the number of physical prototypes by 60 percent.”
3. Improve fit
“Up to 44 percent of all products returned by customers are never used by anyone else again (Source: ReBounc),” says Bailey. The items are often “burned or thrown into landfills.”
One of the main reasons for returns is poor fit, she adds. AI-supported fit tools are increasingly starting at the point of purchase. Nike Fit, for example, uses augmented reality and AI to scan customers’ feet via smartphone. Each foot is recorded using a 13-point measuring system to generate highly precise size recommendations. Bailey notes, “The more people use this app, the more accurate the AI predictions will be.”
“Similarly, Levi’s is expanding its AI-powered outfitting tools to help customers visualize head-to-toe looks,” she continued. This helps buyers to be more confident that what they are buying really suits them.
4. Scaling resale and recycling
According to Wrap, 80 percent of a product’s impact is determined in the design phase. In the words of Future Snoops: “AI is now helping brands improve resale and recycling. It identifies the condition of products, authenticates items, and sorts materials more accurately and efficiently. From detecting signs of wear for pricing to automated separation of textiles or materials, AI optimizes closed-loop systems. This keeps products in use longer and reduces waste volume.”
A notable example is the US outdoor brand Patagonia’s collaboration with Trove. Second-hand items are integrated directly into the brand’s main e-commerce platform. AI supports authentication, inventory management and logistics. This allows customers to purchase new and resold products side by side while ensuring consistent quality and service standards.
5. Supply chain intelligence and climate risk mitigation
According to WEG, over 60 percent of global CO2 emissions come from supply chains, says Bailey. Yet brands often have very little insight into where these emissions originate. AI’s ability to collect and analyze data at a scale and speed impossible for humans is beginning to change this.
Logistics providers such as the German company DHL are already using AI-supported route optimization. This allows you to analyze shipping volumes with a certainty of up to 95 percent. This improves last mile planning, reduces idle time and increases fuel efficiency.
At the same time, AI-powered demand forecasting tools are helping companies like Swedish furniture retailer Ikea predict demand more accurately. This reduces overproduction and unnecessary transport.
According to BCG, climate-related supply chain disruptions are already costing companies an average of $182 million per year. AI can strengthen climate risk management by continuously analyzing weather patterns and disruption risks, Bailey said. This allows brands to anticipate extreme events and adjust sourcing or production before they escalate.
Romanian fashion manufacturer Katty Fashion is developing a digital twin of its supply chain and factory processes. The aim is to analyze suppliers’ weak points in real time. By combining climate, news and weather data, the system can identify future risk zones. It can also suggest adjustments to production lines and work shifts when disruptions occur.
Finally, Bailey highlighted the role of AI in sustainability reporting (ESG). This process can take up to 80 percent of sustainability teams’ time, according to Bain & Company. AI-powered tools like Konica Minolta’s ESG AI and Positive Luxury’s collaboration with Briink simplify data collection and ESG assessments. They improve accuracy while reducing manual labor.
“AI has an environmental cost,” Bailey concluded, “but it also gives us extraordinary new capabilities. If we design responsibly and act purposefully, it can become one of the most powerful drivers of sustainability in the coming decade.”
This article was created using digital tools translated.
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