Artificial intelligence is a buzzword right now, yet how has it been used to transform one of the world's most significant industries? AI is being used to improve productivity in the textile sector as well as in market administration. Modern and innovative technology may be used to promote sustainability and deliver a tailored, individual consumer experience.
How fashion industry is using AI?
In the fashion industry, artificial intelligence is being used in many various forms. The first application of AI in fashion is as an advisor. Customers receive fashion tips based on their height, weight, and current size via artificially intelligent digital assistants. Users are then provided detailed sizing depending on the data they submitted into the application. The precision of sizing is dependent on input from other users. On average around 30% of online purchases are returned that's why the use of AI in customer advisory is important as it allows for greater customer satisfaction and a reduction in the number of returns.
For simplicity and efficiency inside shops and online shopping, AI may also be used. Retailers can keep track of the inventory and determine which retailers require which products by tracking orders, returns, and internet transactions. Artificial intelligence could help retailers save billions annually by enhancing productivity in numerous processes and operations. This is a big amount, so it's obvious that many companies want to integrate emerging technology like AI into their operations.
How AI can boost sustainability?
The fashion industry is still one of the largest polluters. It accounts for 10 % of global carbon dioxide emissions, 20% of the world's industrial wastewater, and 25% of all insecticides used in the industry. It is unrealistic to believe that this sector would be able to follow up with fast fashion by producing more and more clothes. Artificial intelligence, though, may be used to combat this problem at several levels of production, like decreasing inventory levels. AI presents a long-term alternative to the fashion industry, minimizing operational inventory volumes by 20–50 percent while simultaneously enhancing working standards. The implementation of Artificial Intelligence in addition to Computer Learning, Deep Learning, Natural Language Processing, Visual Recognition, and Data Analytics may be utilized to decrease errors in trend forecasting more specifically, decreasing the amount of clothing manufactured and then unused.
Benefits of AI for Fashion Industry
Reinforced customer service
Intelligent chatbots and other assistive technologies have revolutionized customer service and how consumers communicate with fashion brands. Chatbots also enriched conversions and the overall brand experience by analyzing sales leads and recommending products.
Improved tracking of inventories
Predictive analytics focused on AI enable fashion retailers to learn from prevailing consumer behavior and appropriately schedule their product stocks. AI-powered software will assist the fashion industry to reliably determine their best (and worst) selling products and prepare their inventories.
Another main advantage of AI and ML technology is that fashion houses can simplify routine or mundane activities traditionally done by employees. AI can now perform tasks such as data entry and customer care, enabling human agents to concentrate on more strategic operations.
Decrease of returns
Returns of sold goods are a big problem for the fashion business, as they can push up operating costs. Today's retail consumers are more aware and less likely to purchase the wrong clothing item thanks to AI-enabled personalization and product description. As a consequence, fewer items are returned, and consumer loyalty increases.
There are several ways in which AI and machine learning technologies affect the global fashion industry like product personalization or better design. The increasing investments by leading fashion brands in these technologies are showing their tremendous business potential. AI and deep learning applications have helped a variety of businesses get the best out of their investments in these technologies.