AI In The Fashion Industry: 6 Game-Changing Technologies

 

· Insights

Innovative technology, more efficient operational methods, and access to consumer and industry insights that give a possible competitive advantage have all been swept across numerous sectors by artificial intelligence (AI), which has the potential to disrupt enterprises.

As an industry built on individuality and individual expression, artificial intelligence (AI) did not initially appeal to fashion executives. 

When compared to rivals that still use conventional techniques in this hyper-digital age, these apps have the potential to revolutionize enterprises and produce considerable growth and profits for the industry.

Despite the established structure of the fashion industry, AI substantially transforms the sector. From how fashion enterprises produce their products to how they advertise and sell them. 

Design, manufacturing, shipping, marketing, and sales are just a few of the areas where artificial intelligence is having a profound impact on the fashion business.

Artificial Intelligence (AI) has become so commonplace in the fashion industry by 2020 that many fashion shops that have not adopted AI are now in danger of bankruptcy. 

There will be a $7.3 billion-a-year investment into AI technology by 2022 in the fashion and retail sectors globally.

Take a closer look at some of this artificial intelligence (AI) applications and how businesses are enhancing their business models in new ways.

6 Game-Changing Technologies:

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1. Apparel Designing:

The use of artificial intelligence (AI) in fashion design has been overlooked. 

There is huge potential for an industry to automate its design and presentation processes during the pandemic as well as thereafter in the event that this virus spreads far and swiftly. 

When it comes to creative AI, what are the new possibilities for designers and businesses?

The first AI applications have focused on quantifiable business needs. Quantifying creativity is far more difficult, and as a result, the results tend to lag. 

However, as more scientists do research into new forms of creative thinking, the technology's potential benefits become more apparent. Designers of fashion may soon have a new best friend in AI models.

There are generative adversarial networks, a type of Machine Learning (ML) in which two adversarial models gets training concurrently.

A generator ("the designer") learns to create images that look real, and a discriminator ("the design critic") learns to distinguish between real and fake photos. These models have been used to generate novel apparel designs.

Generators and discriminators are both trained to get better at producing authentic pictures. 

Because of the inventive use of technology, computer-generated pictures and motions might look credible (and even aesthetically pleasant) to the observer.

There is more to AI than just creating new designs. In order to better understand customer preferences and produce better clothing, fashion firms employ technology to obtain more complex data. 

With the help of Google, Zalando pioneered the use of AI-powered fashion design based on the preferences of the client, such as their preferred colors, textures, and other design elements.

Synflex is a startup that combines fashion with artificial intelligence. Algorithmic Couture is the name of their joint venture. 

Computer-aided design technologies are used by Synflux to model ideal fashion pattern modules.

2. Virtual Merchandising:

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A lot of us have a closet full of stuff that we never wear. It might be because they're too tight or uncomfortable or don't match our other clothing. 

When so many online shops use photos that persuade us to purchase. However, they don't always present a true-to-life portrayal of a garment, it's inevitable.

It's now possible to bridge the gap between online and in-store shopping experiences with AI-enabled technologies such as augmented reality (AR) or virtual reality (VR).

Online shopping would take five years less time to take off as a result of the epidemic, according to some experts. 

Even said, it's unlikely that fashion will ever be fully touch-free: many people still prefer to shop in person and try on genuine clothing at malls. 

With the help of in-store AR and VR technologies, retailers can target this kinesthetic population. By making the shopping experience more immersive and pleasurable, these technologies improve it.

AR technology is being used in the fashion industry to enhance both online and brick-and-mortar shopping experiences. 

Style, texture, and color are just a few of the variables you may play with as a customer when it comes to your own style.

You may try on many pairs of shoes using the Wanna app, which uses augmented reality. 

From the selection of 3D models, pick a pair of shoes that you want to wear and take a picture of your feet.

3. Visual Search:

Take this as an example: A woman in the most stunning outfit that you've ever seen catches your eye when you're out for a stroll. 

What you want is exactly the same. However, you don't know what brand they're wearing or where you can acquire it. 

To locate your new favorite dress, all you have to do is type in "dress" into a search engine. However, you'll only receive a few, mostly unrelated, results.

Examples of the visual search may be seen in this example, in which images are scanned, and suitable results are returned depending on user input. 

Customers don't have to describe what they're looking for in order to get what they're looking for, making internet shopping easier and more satisfying.

With the use of artificial intelligence (AI)-enabled applications, customers may capture screenshots of online outfits, find shoppable gear and accessories in the picture, and then shop for comparable outfits.

Pinterest and Google Photos, for example, have included a visual search function. The number of clothing-specific search engines is still limited. Lykdat is one such example of a reverse image search engine for fashion items using pictures. 

It's like the Shazam of apparel, except better. Customers just take a picture of their clothing and send it in. 

The algorithm will produce a list of online merchants selling these products that are available.

4. Improved Customer Personalization:

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For a firm to be successful, it must cater to its customers on an individual basis. Now businesses can access and analyze a large quantity of client data. 

Deep learning technologies like AI and ML allow fashion companies to track the purchasing habits of specific customers. Therefore, they are used in conjunction with business data.

Technology's rising knowledge and computational abilities are increasingly being used. It is to understand and impact the expectations of consumers based on their purchases. 

Moreover, it is ideal to know their preferred colors and textures, and other personal style preferences.

Customers are eager to provide personal information for a more tailored experience when faced with a congested marketplace and one-of-a-kind, personalized marketing. 

Product recommendations based on such algorithms now account for 35% of Amazon purchases.

When it comes to customization, Nike is unrivaled in the world of sports footwear and athleisure. 

Nike's Nike By You platform, which they describe as a "co-creation service," allows users to create their own footwear.

4. Automated Authentication:

You may detect fashion forgeries and counterfeits with the use of ML-enabled computer vision. In the past, customs officers or other law enforcement employees had to get training to spot fakes.

It is now possible to detect counterfeit goods that are getting more identical to the genuine thing thanks to AI. 

Customs and border agents use Artificial intelligence (AI) to verify the authenticity of high-end goods. It includes handbags and sunglasses, which are easy to copy.

Third-party sellers may be difficult to distinguish from authentic third-party sellers on the internet. It might tarnish the buyers' perceptions of the brand if they purchase a product that seems trustworthy but fails to live up to expectations.

Many online marketplaces include large datasets and images that are in use of certain businesses to investigate and detect possible counterfeit items.

Firms involved in the acquisition and sale of high-value commodities may now use Entrupy's AI-powered authentication solutions. 

A combination of ML and Computer Vision drives this company's cutting-edge authentication solutions, as well as a proprietary database comprising millions of images of genuine and counterfeit products gathered from across the globe.

Major luxury goods resellers and professional purchasers utilize its technology to verify Louis Vuitton, Chanel, and Hermè's handbags and accessories.

6. Trend Forecasting:

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Forecasting a market's future is what trend forecasting is all about. This is why fashion forecasting, as a sector of the fashion industry, is about predicting future fashion trends. 

Also, it predicts colors and styling methods, as well as fabric textures and so on that, which will excite the attention of the general public.

Fashion forecasters provide trend projections that product developers use to create new clothing and accessories for commercial use.

However, a human fashion trend forecaster would never be able to analyze that much data in time for the next season.

So, using AI to conduct the hard work frees up forecasters to seek developing trends in less conventional areas.

Heuritech has developed an in-house deep-learning approach that can identify early signals in order to predict future trends. 

Edgy influencers, who often give trends life, show early signs of shifting activity patterns.

With Heuritech's sophisticated AI, organizations can better predict demand and trends. 

Moreover, they can produce more sustainably, and obtain an amazing competitive edge by analyzing social media images.

Many firms now employ artificial intelligence to discover new trends in addition to social media's influence on trend forecasters. 

Using artificial intelligence, Fashion Snoops, for example, searches for new buzzwords and terms with the potential to become fashionable.

Conclusion:

AI and ML may be game-changer for fashion businesses. Customers will appreciate the improved service, as well as the more environmentally friendly company practices that will result. 

The fashion industry's future seems promising!