Fashion is all about capturing the latest trends and transforming them in an evergreen format. This has widely been entrusted upon a few select designers to execute for generations now. With the help of AI, these decisions are becoming increasingly decentralized, as AI focuses on enhancing the gut feeling. AI is being used across various domains in the fashion industry from demand analysis to new colors launching.
AI is also being seen as a disrupter in the predictive analytics space, wherein it captures sales data month over month to create a more dynamic picture. Fashion forecasters can then analyze the information presented and utilize the insights in the next collection is launched.
This has a holistic impact in the fashion industry, along with significant strides being made in fashion-tech. Guess, the retailer, grew 20% in Asia where it used to struggle for years. This was on the backs of predictive analytics and using AI to strengthen trends forecasting.
Having the right Algorithms, Talent & Innovation
Some of the major fashion houses are hiring a qualified CAO to analyze the vast amount of data present. Along with that, there is major emphasis being given to startup entrepreneurs who work with algorithms in the consumer domain. These companies offer better products to the marketplace, by using AI and Machine Learning to optimize preferences.
The men’s fashion startup Stitch Fix is working on disruptive the fashion industry, in the way that men purchase clothing online. They’re using AI enabled models to run predictive scaling across a variety of domains. From prototyping new collections to introducing new lines, everything runs through an AI lens.
“We noticed gaps in the market and an opportunity to produce something that doesn’t exist but should. We’re uniquely suited to do this. This didn’t exist before because the necessary data didn’t exist. A Nordstrom doesn’t have this type of data because people try things on in the fitting room, and you don’t know what they didn’t buy or why. We have this access to great data, and we can do a lot with it.” – Eric Colson, CAO Stitch Fix.
Insights from the data science community
Scientists from Cornell, Stanford and MIT are working towards creating better prediction models for fashion brands. Certain students are working on creating their own AI solution that runs existing data to predict future trends. The information gets pulled up from a variety of sources, outside the fashion industry, and it’s fed back into the algorithm. Some of these algorithms analyze millions of images online to predict the next color or shade that’s going to be in demand.
“As machine learning gets more sophisticated, it will be able to detect micro trends before they become widely popular. This will be the holy grail of retail. With this, retailers can respond a lot faster to changing preferences. If we can forecast trends fast, it will fundamentally change how designs spread and might open the doors for ‘smaller’ designers to reach larger audiences. A more democratic spread of design ideas can potentially be enabled.” – Kavita Bala, Prof Cornell University.
Ultimately, AI needs to collaborate with human forecasters so that the raw data being entered is of higher quality. It can also strengthen the argument that a forecaster or designer presents to the fashion house. As competition rises, more ideas can come to fruition by being data-backed. AI can enable better information processing to get a true picture of how demand was influenced over the quarters. Industry participants in the fashion space need to work with AI to grow the industry through the digital revolution.