AI can reduce fast fashion's carbon footprint: UNSW Research

AI-driven technologies can be harnessed for climate action and significantly advance environmental and market performance, according to the findings of a new study, co-authored by the UNSW Institute for Climate Risk & Response.

The fast fashion industry is one of the world’s biggest polluters. Employing some 75 million people and valued at over $2.5 trillion (A$3.8 trillion), it is responsible for about 10 per cent of global carbon emissions.

The study, ‘Unleashing the Power of Artificial Intelligence for Climate Action in Industrial Markets’, was co-authored by an international team of researchers, including lead author professor Shahriar Akter, associate dean (research) at the faculty of business & law, University of Wollongong, and professor David Grant, senior deputy director at the UNSW Institute for Climate Risk & Response.

“Due to AI's unique capacity to collect, integrate, and interpret big data sets, our proposed AI framework provides a data-driven approach to address climate risks, focusing on the environment, infrastructure, and market in an actionable and systematic manner,” explained Akter.

“Our study’s findings have shown enormous potential for helping companies achieve emissions-related targets and meet their reporting and assurance obligations related to Scope 1, 2, and 3 emissions as defined under the World Resources Institute and World Business Council for Sustainable Development Greenhouse Gas Protocol (2004),” said Grant.

Bangladeshi manufacturers are recognised for their worldwide exports. They produce most of the apparel for leading fast-fashion brands such as Primark, Nike, H&M, and others in 150 countries. In recent years, consumers and governments have pressured these brands to reduce emissions and the environmental impact of their global supply chains.

“H&M has committed to a 56 per cent reduction in emissions and 100 per cent renewable electricity in its supply chain and operations by 2030. A larger number of clothing brands, such as Calvin Klein, Tommy Hilfiger, and Next, also require their supplying factories to be green, complying with environmental and safety regulations,” said Grant.

“AI-powered climate service solutions are technologies like big data and machine learning that can reduce routine, repetitive, simple, and standardised tasks,” explained Professor Grant. “These include emission measurement, calculating individual products' carbon footprint, identifying risk factors, forecasting demand to reduce waste, and climate education."

In their study, the researchers surveyed 211 managers at manufacturing companies in Bangladesh with at least one year of experience using basic AI-powered climate service solutions. The findings showed that businesses employing AI-powered climate service innovation models improved energy efficiency, reduced emissions, and increased renewable energy sources.

“AI-powered climate service innovations can enable firms to adopt innovations that reduce the environmental impact of their business activities while improving energy and material efficiency and managing climate-related risks and opportunities,” added Grant.

Emissions from the global fast fashion industry are estimated to skyrocket by 60 per cent by 2030. “AI-powered climate service innovation can improve environmental performance in terms of energy efficiency, reduction of wastage, optimum consumption of natural resources, and sustainable eco-design. An improved environmental performance can also enhance market performance by enabling firms to access new markets, secure new sales leads, and generate more revenues,” Akter added.

In the paper, ‘environmental performance’ refers to an organisation’s performance related to pollution control, and market performance refers to the degree to which AI-powered climate solutions enhance profitability and competitive advantage.

“We show the significant impact of AI-powered climate innovations in the fast-fashion industry on two key indicators of firm performance: environmental and market performance. We demonstrate that environmental performance can substantially impact market performance when a firm has robust AI-powered climate service innovation capabilities. We also found that focusing solely on environmental orientation is insufficient, and researchers must explore various technological and market dynamics to understand what constitutes more sustainable innovations in this area,” Akter explained.

“A key feature of the model discussed in the paper is that it points to how AI can enhance the firm's environmental, social, and governance (ESG) performance and credentials as well as market performance in terms of productivity, efficiency, quality assurance, and overall competitiveness. AI can improve a business's long-term sustainability, growth, and profitability. In short, investment in AI makes business sense,” Grant concluded.