In a recent pilot study, Artificial intelligence (AI) has demonstrated its potential to track the origins of apparel waste, holding fashion brands accountable for their products’ end-of-life phases.
Conducted by Avfall Norge, a Norwegian organisation representing over 200 waste management and recycling companies, the study took place. Over two weeks, these students analyzed 3,024 pieces of textile waste from various Norwegian municipalities. Utilising AI and machine learning (ML) through a Targeted Producer Responsibility analysis, they successfully identified clothing from 708 different brands.
This development coincides with the UK Fashion and Textiles Association’s announcement of a £ 4 million project aimed at creating an automated sorting and pre-processing plant for waste textiles.
The study revealed that the AI tool could easily identify the brand of the garment in 84.78 per cent of cases. This valuable information can be used to establish feedback channels with brands, potentially encouraging more sustainable production practices. Beyond brand identification, the analysis provided insights into the composition of the textile fibres, garment age, country of production, and potential for reuse. The AI and ML tools relied on product labels to track each brand’s labelling system. Data gathered through AI, has the potential to automate the sorting and recycling of apparel waste, setting the stage for strategies and policies that target waste reduction at its source and address the unchecked growth of fast fashion.
Bharat Tex Special Report 2026 
