AI’s $908bn opportunity
Clothing suppliers could benefit significantly from the adoption of artificial intelligence (AI) in their businesses, if it is applied correctly. Hannah Abdulla reports.
Artificial intelligence is one of the themes that will have a significant impact on apparel companies. Credit: Shutterstock.
Many more names in the global clothing sector are adopting AI, either to improve operational efficiencies or customer engagement, including UK fashion retailers Marks & Spencer and Next, German online retailer Zalando, US sports brand Nike and Swedish fashion retailer H&M.
But clothing makers stand to benefit the most from the adoption of AI and generative AI according to a new report from GlobalData.
GlobalData’s Artificial Intelligence in Retail and Apparel report says the market will be worth $908.7bn by 2030 and within the apparel sector, apparel manufacturers have the biggest opportunities to capitalise on that growth, depending on where they choose to apply the technology.
GlobalData encourages clothing manufacturers and processors to apply AI technology in the areas of human-AI interaction, decision making and creation. Meanwhile, clothing brands should look to leverage the benefits of human-AI interaction in retail stores while online could benefit from human-AI interaction, decision making and creation.
Several retailers have adopted generative AI to create a personalised shopping experience and support AI-powered chatbots and virtual assistants that provide instant customer support and can guide customers through the purchasing process.
Overall, AI can increase speed, efficiency, and accuracy across every branch of a retail business. With advanced data and predictive analytics systems and AI product design, retailers can make data-driven business decisions.
The mine’s concentrator can produce around 240,000 tonnes of ore, including around 26,500 tonnes of rare earth oxides.
Navigating macroeconomic challenges for clothing firms
With concerns around sustainability continuing to grow, AI can help with ESG wins, the report suggests, contributing to improving personalised shopping, inventory management, and logistics. But the jury remains out over whether the tech is a good or a bad thing when it comes to the sustainability of the sector. There are ethical challenges to consider including privacy concerns and algorithm bias.
Earlier this week a pilot study suggested AI could identify the source of apparel waste and make fashion brands accountable for the end-of-life of their products.
But also this week, details emerged about Chinese ultra-fast fashion retailer Shein being presented with a lawsuit over its algorithmic fashion design with allegations it could facilitate industrial-scale copying, while compounding overproduction and overconsumption.
In July, three independent US fashion designers, Krista Perry, Larissa Martinez, and Jay Baron, filed a lawsuit against Shein for engaging in AI-led “systematic criminal intellectual property infringement”.
The designers claim the fast-fashion brand uses “secretive” AI algorithms to identify and reproduce carbon copies of independent designers’ work – with a tendency to appropriate pieces with the greatest commercial potential.
“Retailers must address these challenges when implementing AI solutions. Moreover, retailers must also consider the environmental impact of AI. The technology requires significant amounts of water and electricity to work, with researchers suggesting that OpenAI’s GPT-3 emitted more than 500 metric tons of carbon dioxide during training,” reads the report.
2. Inflation and supply chain disruption
With inflation at record highs over the last year, costs for apparel brands and retailers saw a sharp rise.
GlobalData’s report suggests AI can help retailers optimise their supply chains by analysing data and identifying cost-saving opportunities. AI algorithms can help optimise transportation routes, streamline procurement processes, and identify alternative suppliers or sourcing options to mitigate the impact of inflation on supply chain costs. Demand forecasting and inventory management through AI are other ways brands can manage supply chain cost hikes.
3. Marketing and shopping experience improvement
AI algorithms can be used to analyse customer data, including browsing history, purchase behaviour, and preferences, to provide personalised product recommendations. By understanding individual customer preferences, AI can suggest relevant products or services, increasing the likelihood of conversion and enhancing the customer experience. AI is also being used to increase consumer personalisation, facilitating a more efficient and accessible shopping experience.
Mines in Bayan Obo in Inner Mongolia, China, extract one the largest deposits of rare earth metals found in the world. Credit: Bert van Dijk/Getty images