It is difficult to quantify the pollution caused by the fashion industry – it is considered to be amongst the top polluting industries, and is heavily reliant on the transport, oil and gas, electricity and livestock sectors. Although recent years have seen an increase in self-acclaimed sustainable and ethical fashion brands, there is still a lot of progress to be seen from big retailers, and especially fast-fashion producers. The lack of progress towards more lower impacting production methods begs the question on how should producers be motivated to adopt more sustainable practices?
Artificial intelligence (AI) is predicted to be a revolutionary force in industries ranging from food to financial services. Its data collection and processing capacities and ability to derive insights from copious amounts of data, as well as its proficiency in automating time-consuming tasks that are susceptible to human error, make it an attractive tool for overcoming business limitations. In the fashion sector, AI is expected to streamline supply chains, improve sales forecasting and provide a more personalized shopping experience to customers.
Sales forecasting plays a central role in determining a brand’s success, but according to experts, the quantity of variables involved makes it a very difficult calculation. AI can be used to increase the scope of data – tapping into social media and eCommerce data, provide more reliable insights and make more accurate predictions. More specifically, AI would produce information on ideal markdown periods, stock variety and location. The business advantage of a more optimized and efficient stock management is indisputable and is a sufficient incentive for companies to adopt this technology. However, the side effect of a more efficient sales forecasting system is minimizing waste products by reducing over-production and better allocation of merchandise. With items being stocked and sold more efficiently, excess waste could subside – thus, AI sales forecasting would address the issue of misallocated stock and decrease the number of products that have not been sold.
Supply chain management
A recurring theme in the discussion of sustainability and ethics in the fashion industry is supply chain management. The complexity of the procedures that are necessary for the manufacture of one garment – sourcing different materials, sourcing labor and arranging transportation, to name a few – makes it difficult to keep track of the history of all of the items being produced. Ignorance towards the supply chain decreases the accountability of brands for human and environmental disasters, such as the Rana Plaza disaster in 2013. It also prevents customers from purchasing according to their moral convictions, due to the lack of information about the product or brand that they are consuming. The organizational capabilities of AI and its ability to track and monitor huge amounts of data are ideal to tackle this issue. More transparency in the supply chain would allocate responsibility to the brands over what raw materials they use and where they are sourcing their labor. Better information would also make brands more accountable to the expectations of customers, potentially pushing retailers to alter their sourcing practices to build a good reputation. The pioneering Fashion Revolution movement, which emerged as a response to the Rana Plaza disaster in 2013, works on demanding accountability and transparency and encourages the consumer to do the same with their trending #whomademyclothes campaign. A leading figure in this conversation is also Baroness Lola Young of Hornsey, who as Chair of the All-Party Parliamentary Group on fashion sustainability and ethics (for which Fashion Roundtable’s Anna Fitzpatrick was secretariat), is a leading figure in transparency in the supply chain with her work on amending the Modern Slavery Bill. These are very exciting developments, because recognition of the existence of such practices in the fashion supply chain is the first step to addressing them, and having these conversations in a public platform increase the pressure on brands to respond to concerns. The efficiency of AI can finally provide suppliers with an accessible and effective way of revising their sources. An interesting question would also be the extent to which blockchain technology can be integrated with AI to track the origin of manufactured goods.
Personalized shopping experience
Finally, the natural language processing and capacity to take cues from speech, typing and images would allow for AI to successfully interact with customers. Via chatbots and the collection of data from social media sites and past purchase history, AI systems can gain insights into the preferences and desires of customers. This is beneficial for brands as they would have a greater understanding of what their consumers demand, and beneficial environmentally because the manufacturing and purchasing of products would be better informed. Better insight into the expectations of customers also translates into manufacturing more popular garments, so that companies have to deal with less waste and unsold goods. In interacting with AI systems, customers could be prompted to make purchases according to what they already have and enjoy wearing reducing the number of post-shopping regrets, which can fight the statistic of 235 million clothing items were thrown away in the UK in 2016. Furthermore, Millennials tend to prefer personalized and limited products to popular lines, and if the increasing demand for personalized goods can be satisfied, a fall in mass production could be experienced.
How to tackle sustainability?
In addition to the benefits discussed above, what is interesting about the potential role of AI in directing the fashion industry to a more sustainable framework is that this is not the selling point for brands. Being businesses, the majority of fashion brands prioritize profit maximization over reducing social and environmental impacts. If used in the correct manner, AI technology has the potential to optimize retailers’ business models and consequently, making them less wasteful. Although the use of AI to better understand customer behavior and track supply chain to ensure accountability and transparency addresses urgent problems with the fashion industry, it is necessary to keep in mind that the mentality of ‘the more the merrier’ that underlies the industry is problematic and contradictory to sustainable efforts.