Will AI make our lives–and the fashion industry–better?

Will AI make our lives–and the fashion industry–better?

Artificial Intelligence (AI), a machine’s ability to mimic and reproduce the cognitive functions associated with human minds, is starting to invade many different fields in these days, from most mechanical and apparently neutral processes of the industry and generally of our lives, to more complex, creative and ingenious-related aspects.
Different reactions that have started to arouse in most different fields–a mix of fear and attraction toward this new tool and its potentialities of this tool and the various applications in most different industries­–should make us stop and reflect about this topic.

A mix of feelings
The use of AI entails a vast amount of risks such as injury to privacy and data security, as well as discrimination, loss of jobs, environmental impact, to the automation of warfare, and many more including superintelligences that can escape all forms of control. An apparent harmeless example of this are some funky images showing Pope Francis wearing a cool puffy jacket à-la-rapper style or short videos showing him dancing on global social media. Despite these specific examples appear as an overt joke, other risks can be just around the corner. Though more most different and contrasting approaches to this matter are already widespread.

Despite entrepreneur Elon Musk had first urged not to over-exploit AI whose consequences might be unpredictable and potentially catastrophic, according to more recent rumors he is said to have now started building an AI expert and engineer team to further investigate on this tool’s abilities.

Hollywood stars and studios’ unions have started protesting on the risks AI could mean for the ability to recreate video images, voice tones, cloning acting abilities and face expressions, along with the substitution of machines to expressing genuine human emotions, and, not less important, how some stereotypes and prejudices could be eventually amplified
Despite actor Tom Hanks underlined the importance of how teams of authors can build up fantastic stories based upon genuine emotions, he will soon play in the “Metaphysic Live in Here” movie where he will appear in different ages of live, obviously rejuvenated thanks to AI…

Looking at the fashion industry
Fashion is not immune either by the use of AI for a mix of helpful but also critical elements that should be taken into consideration when it comes to careful evaluation about the use of such tools.

Brands like G-Star and denim specialists like Soorty have started to create their own generative AI-designed collections, along with other players that have started creating their own digital showrooms and collections during the pandemic, along with the creation of metaverse art pieces and fashion weeks already taking place for the second year in March 2023, have now become a much discussed topic not everyone approves.

Increased efficiency and customer service has been hyped and bettered thanks to most advanced technology enhancements, as recently announced by global groups including Prada, Zegna and Zalando. Though, can all these innovations truly help the business, better our lives and be truly effective in the aims they want to pursue?

Discovering Artificial Intelligence
AI is a machine’s ability to perform cognitive functions that are normally associated with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem-solving, and even exercising creativity.Voice assistants like Siri and Alexa are founded on AI technology, as are some customer service chatbots that pop up to help us navigate websites.
The use of AI can potentially help companies to become more efficient and productive thanks to most complex systems of machine learning.

Where can AI be applied?
A survey by McKinsey & Company, a global consulting company, collated more than 400 use cases of machine learning and deep learning across 19 industries and nine business functions.

Apparently, nearly all industries can benefit from machine and deep learning as they have the capacity to analyze large amounts of different data, which can increase the precision of predictive analysis.

Using AI could help optimise logistics and reduce costs through real-time forecasts and behavioral coaching.

 Getting more into deep Generative AI are specific systems using tools like ChatGPT and DALL-E, a tool for making AI-generated art, which have the potential to change how specific jobs are performed.

Within fashion, as previously mentioned, a brand can design a collection through generative Artificial Intelligence, by taking inspiration from specific information and images from the web, exactly as it can happen for creating a text. Even if what has been produced until now in terms of collections are hyped examples of creativity, it is still unknown how such collections could further progress.

Offering a better customer service
Key players in the fashion industry have started explaining how AI could become an ally meant to increase efficiency and better customer experience.

Prada has recently signed an agreement with Adobe in order to offer its customers more enhanced customer service.
Zegna has recently showcased a new solution–Zegna X–that integrates Microsoft Azure services and aims to allow customers to have a truly unique shopping experience.

By combining the best back-end data and tools combined with high quality and most realistic configurator, Zegna wants to elevate the future of retail based on a high-level one-on-one service, using new technologies to provide a highly personalised experience.
Zegna has already collaborated with Microsoft in the past in communication projects and helped its staff productivity increase by 5%. Through its newest applications, it aims to deliver even more catered and effective customer experiences.
The new Zegna X full experience went live in April 2023, at its Milan Flagship store in an exclusive room that will be available by appointment only. Though, it will be soon available in select stores worldwide as part of an exclusive roadshow.
Initially, the new tool will be able to deliver 49 billion potential combinations of clothes and styles that can be custom-made and delivered worldwide in less than four weeks. In 2024 Zegna X configurator will land on Zegna.com, allowing consumers to customise any look of the collection online using their personal devices.

Zalando , a case history to be analysed
A different example is a Zalando’s case about predictive analisys of its returned items.

A recent survey published by the German newspaper Die Zeit highlighted how the German e-commerce platform is keen about helping the fashion industry pollute less and reduce its impact in different ways, including a more rationalized return system.

The two authors of the article, Carmen Maiwald and Vanessa Materla, by trying to discover more about the group’s impact, have tried to investigate about that.

Zalando says that 97% of the returned articles are put back on the market and less than 0.05% are destroyed, though in Germany in 2021 out of the 440 million of returned apparel items one third can be considered belonging to Zalando’s traffic.

In order to clarify what happens to many of the returned garments, the journalists ordered ten different clothing items on Zalando and sewed small GPS transmitters inside each of them before returning them to the e-commerce group to track which path each garment followed after being returned. Through tracking, they noticed that the items moved following a sort of zigzag lines through various parts of Europe.

Considering the movements generated by the ten returned garments, the sensors found out that many of the garments continued to move traveling considerable distances between Sweden, Denmark, Poland, and Germany, by sea and land and, in total, the ten garments traveled for 28,822 kilometers, a distance that is not surely in-keeping with the company’s aim to reduce fashion’s impact.


 As Die Zeit’s thought that probably returned items are constantly traveling via truck or boat until they are resold, The SPIN OFF asked Zalando for a comment. “We certainly do not use trucks as mobile warehouses. From an economic point of view, this does not make sense – every kilometer traveled is linked to costs and, apart from that, we have sufficient storage capacity within our European logistics network. We transport the goods from our returns centers across Europe to our 12 logistics centers that are close to the region with the highest resale probability to enable the reuse of returned items,” the company explained.

“Our goal is to enable the resale of returned items, therefore we make the transport of returned goods as efficient as possible. This means that we collect the returns near the source, process them in one of our special returns centers and send them back sorted and grouped to one of our nearest logistics centers. This distribution process is supported by a customized algorithm that we have developed ourselves. The calculations support the most optimal distribution to increase the probability of reselling the corresponding items,” continued Zalando explaining that they calculate to ship the returned goods where there is a higher potential to sell it, according to predictive analysis, another AI-generated calculation system.

“Within our system, the sales numbers of the past few weeks are taken into account for the respective item and, in a second step, combined with the stock numbers of this item in the logistics centers. We ship the returned item to the location with the highest resale probability for it. As we have developed our algorithm in-house, we can also ensure that we continuously improve it to ensure more accurate predictions,” the company assured.

How AI can help reduce returns
In order to help reduce returns, Zalando has started helping customers by giving them specific size-related advice and also introduced a specific AI tool, a virtual fitting room where customers can see how an item of clothing fits their personal 3D avatar.

“We have already been able to reduce the size-related return rate by 10% for items for which we offer size-related advice. This is not an annual comparison, but a comparison of items with size advice and items in the same category and season without size advice. Size-related returns are highly dependent on the category – for example, it is easier to find a matching T-shirt than a matching pair of jeans,” they explained referring to the size-related advice.

Through the pilot virtual 3D changing rooms, customers can create a 3D avatar by entering their height, weight, and gender. For a selected range of 22 jeans, which is one of the most challenging categories in terms of finding the right size due to the lack of sizing standards, customers can see how different sizes from various brands would fit them, with a heatmap indicating where the item sits tight or loose on the avatar they created.

More than 30,000 Zalando customers have tried out this technology launched by the company together with Puma and Zalando’s private label Anna Field and probably returns have also lowered thanks to it, though no figure is available yet.

AI can surely help the fashion industry significantly, though its performance needs to be checked and adjusted carefully according to real life’s feedback. Numbers and algorithms can cannot be left working alone, as (luckily) reality bites.

AI in Fashion Marketing

Artificial Intelligence is bringing about a paradigm shift in the field of fashion marketing, enabling a new level of personalization and efficiency that was previously unimaginable. Here are a few use cases that illustrate the transformative power of AI in fashion marketing:

  1. Personalized Marketing: AI can analyze customer data including past purchases, browsing history, and social media activity to create highly targeted marketing campaigns. These personalized recommendations increase customer engagement and boost sales.
  2. Predictive Analysis: AI can predict future customer behavior based on past data. This allows brands to anticipate customer needs and market their products accordingly, optimizing sales and improving customer satisfaction.
  3. Automated Ad Buying: AI can manage programmatic advertising, wherein it automatically purchases ad space in real-time, targeting specific customer segments and optimizing ad spend.
  4. Chatbots: AI-powered chatbots can interact with customers, answering queries and providing personalized recommendations, thus enhancing the shopping experience and customer engagement.

curated by ozzie small

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