Artificial intelligence (AI) has swept across various industries, potentially disrupting businesses via creative technologies, more effective operational procedures, and access to consumer and industry insights that provide a prospective competitive edge. Artificial intelligence is fast evolving and has many uses across different industries, including fashion.
WHAT IS ARTIFICIAL INTELLIGENCE, AND HOW DOES IT WORK?
Artificial intelligence (AI) refers to computers and machines that mimic humans’ problem-solving and decision-making capabilities. AI is designed to perform tasks that typically require human intelligence, such as recognizing patterns, making decisions, and understanding natural language.
There are several types of AI systems, but one of the most common is machine learning, which involves training a machine learning algorithm on a large dataset of examples to learn to make predictions or decisions based on new input data. As the algorithm learns from the errors it makes in the training data, it adjusts its internal parameters to improve its predictions.
There are four main types of Artificial Intelligence, including:
Reactive AI: Reactive AI is a type of AI that can react to new situations and learn from them without having been explicitly programmed to do so. Examples of reactive AI within the fashion industry include visual search, personalized product recommendations and price optimization.
Limited Memory AI: Limited memory AI systems can learn from experience and use this knowledge to improve their performance in the future. Examples of little memory AI within the fashion industry include customer service chatbots, trend forecasting and inventory management.
Theory of Mind AI: Theory of mind AI, the most advanced type of AI, can understand human emotions and motivations and respond in a human-like manner. This type of AI is not widely used in the fashion industry, but some emerging applications exist, such as virtual styling assistants and interactive shopping experiences.
Self-Aware AI: Self-aware AI, also known as reflective AI, is a more advanced form of artificial intelligence capable of understanding and interpreting data, reflecting on its internal processes, and improving its performance over time. This type of AI does not currently exist.
From designing clothes to predicting consumer preferences, AI transforms how fashion is produced, marketed, and consumed. With its ability to analyze vast amounts of data and learn from patterns, AI is opening up new possibilities for designers, retailers, and consumers alike. We ask how AI will affect the marketing fashion of the future.
Initially, AI automation needed to be more appealing for fashion executives to utilize in an industry founded on creative ability and expression. However, as we enter the hyper-digital age, these applications can transform businesses and generate significant industry growth and revenues compared to competitors using traditional methods.
Despite the fashion industry’s established nature, AI fundamentally alters the sector, from how fashion businesses make their items to how they are promoted and sold. As a result, AI technologies are revolutionizing the fashion industry, including design, production, shipping, marketing, and sales.
Consequently, the fashion and retail industries’ worldwide investment in AI technology will reach $7.3 billion annually.
AI IN THE FASHION INDUSTRY
Artificial Intelligence is already being used in various ways across the fashion industry to enhance processes for customers and increase the speed of manufacturing and business operations. Some of the ways AI is being used in the fashion industry are:
AI In Fashion Business Operations
- Trend forecasting and buying
- Merchandising and analysis
- Design and product development
- Styling and visual merchandising
Many of us have a closet full of items we never wear because they are gauche, look cheap, don’t suit our body type anymore, or match the rest of our wardrobe. It’s unavoidable when so many online businesses utilize photographs that entice us to buy yet don’t necessarily provide a true-to-life depiction of a garment.
AI-enabled technologies like augmented reality (AR) and virtual reality (VR) are now trying to solve the problem above by bridging the gap between online and in-store purchase experiences.
AI solutions for fashion design have yet to be addressed. Still, they have enormous potential for an industry rapidly automating its design and presentation processes during the post-pandemic. So what are the new opportunities for designers and businesses, and why is creative AI underutilized? Initially, AI implementations have focused on measurable business demands.
However, creativity is significantly more challenging to quantify and far more prone to lag. Engineers and Fashion Tech entrepreneurs develop new models for creativity, and the technology’s potential becomes more evident. AI models could become fashion designers’ best friends very soon.
The AI models that have been employed to generate novel apparel design are generative adversarial networks (GANs), a type of Machine Learning (ML) in which two negative models are trained concurrently: a generator (“the designer”) that learns to create images that look real and a discriminator (“the design critic”) that learns to distinguish between real and fake photos.
But AI can aid with more than just generating new designs. By gathering more sophisticated data, fashion manufacturers use technology to understand consumer desires better and make better garments. For example, in collaboration with Google, Zalando, a German fashion marketplace, pioneered AI-powered fashion design based on the customer’s favourite colours, textures, and other style preferences.
Synflux is another company blending fashion and AI. They’re collaborating on a project called Algorithmic Couture. Synflux uses ML to create optimal fashion pattern modules modelled using computer-aided design tools.
AI In Fashion E-commerce
- Product recommendations
- Product search and discovery
- Customer service
AI In Fashion Retail
- Shop floor time optimization optimization
- Omnichannel shopping
- Virtual reality
AI In Fashion Marketing and CRM
- Retargeting Campaigns
- Loyalty Programs
- Content Generation
AI plays an increasingly important role in the fashion industry, helping companies streamline processes, reduce costs, and improve the customer experience.
As an AI enthusiast, artificial intelligence is quickly becoming a game-changer in the fashion industry. From design to marketing and sales, AI affects everything, offering businesses new opportunities to streamline operations and reach new heights. But, like with any technology, the impact of AI in Fashion has its challenges.
AI in Fashion & What It Means to the Fashion Industry
According to some analysts, the pandemic pushed the shift to online shopping by five years. However, it is doubtful that fashion will become completely touch-free: people still want to go to malls and boutiques to explore and try on real clothes. Therefore, retailers may appeal to this kinesthetic demographic by utilizing in-store AR VR solutions and continuing with the experience of Fashion cafés of the future.
These technologies enhance the shopping experience by making it more immersive and pleasant. Fashion businesses use AR technology to provide new features to traditional and online purchasing. As a consumer, you may experiment with different styles, textures, colours, shoes, purses, and jewellery items to complete your appearance.
An example of this technology is the Wanna app, which employs augmented reality to allow you to try on several pairs of sneakers. Simply select a pair of shoes from the collection of 3D models, point your camera at your feet, and presto — you’re virtually wearing your selected footwear.
Consider the following example: You see a Fashion Influencer wearing a dress. Naturally, you want the same, but you need to know what brand they’re wearing or where you can get it. Sites like StyleSearch StyleSearch: Find the outfit that fits you | Fashion search engine has you covered.
Of course, you can search online, but you’ll get a few, primarily irrelevant, results, and you’ll be far from finding your new favourite dress. Good Luck.
In this example, visual search, like text-based search, scans and recognizes user-input photographs and delivers the most relevant search results. As a result, customers can search for what they want without explaining it, making purchasing online more straightforward and gratifying.
Some AI-enabled apps allow users to take screenshots of online clothes, detect shoppable gear and accessories in the image, and then discover the same outfit and shop for similar fashions.
Apps like Pinterest or Google Photos implement a visual search feature. Still, only a few specialize in apparel and help users find more target items. One example is, Lykdat, a reverse image tool to find fashion goods using photographs. Consider it the Shazam of clothing. The customers simply submit a photo of the apparel items. The algorithm will return a list of online retailers that sell these goods.
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Improved customer personalization personalization
PersonalizationPersonalization is essential for business success. Because of considerable data innovation, there is an amount of customer data available to be accessed and studied. When integrated with business data, deep learning technologies such as AI and ML enable fashion firms to follow individual client buying behaviour.
Marketers increasingly leverage growing technology knowledge and computational skills to comprehend shoppers’ expectations and influence their experience based on purchases, favourite colours, textures, and other style preferences.
In a crowded arena, one-of-a-kind, personalized advertisements cut through the clutter, and customers are willing to give personal information for a more customized experience. Product suggestions based on such algorithms account for 35% of what people buy on Amazon.
One of the world’s leading athletic footwear and athleisure businesses, Nike is not surpassed in the personalization game. Instead, Nike has pushed personalization to the next level by allowing customers to design their sneakers with the Nike By You platform, which they define as a co-creation service.
Computer Vision powered by ML also detects fashion forgeries and counterfeit items. Detecting fakes formerly required professional customs or other law enforcement personnel’s trained eye.
AI algorithms can now monitor counterfeit items, becoming more similar to the real thing. For example, customs and border officials are employing AI technology to help determine the authenticity of high-end products that are frequently counterfeited, such as handbags and sunglasses.
While browsing enormous internet marketplaces, ordinary customers may need to help recognize counterfeit items from a third-party seller. When a buyer buys a product that appears legitimate but performs poorly, it can leave a bad taste and harm their opinion of the brand.
Some organizations use AI to examine and identify potentially counterfeit products by relying on massive datasets and pictures from numerous online marketplaces.
Entrupy has created artificial intelligence-powered authentication solutions for firms that acquire and sell high-value commodities. Their cutting-edge authentication solutions are powered by a mix of ML and Computer Vision and a proprietary database containing millions of photographs of genuine and counterfeit items collected worldwide.
Its technology is used to authenticate handbags and accessories from luxury brands such as Louis Vuitton, Chanel, and Hermès by major resellers and professional buyers of luxury goods.
Trend forecasting is a field that focuses on projecting a market’s future. Thus, fashion forecasting is the branch of the fashion business concerned with projecting new fashion trends—colours, styling techniques, fabric textures, and so on—that will pique consumer interest.
Fashion forecasters generate trend forecasts, which product developers utilize to design new garments and accessories for businesses.
But an individual fashion trend forecaster would never be able to examine that quantity of data in time for the following season, so utilizing AI to perform the heavy work frees up forecasters to search for emerging trends in less traditional sectors, such as movies, television, or even politics.
To foresee trend evolutions, Heuritech created an in-house deep-learning technique that detects what is known as early signals. Early indicators include slight shifts in the activity among edgy influencers, who frequently give trends life.
Heuritech helps companies to anticipate demand and trends more precisely, manufacture more sustainably, and gain exceptional competitive advantage by leveraging powerful AI to transform real-world photographs posted on social media into relevant information.
Social media isn’t the only thing that’s changed how trend forecasters make their forecasts; many businesses also use artificial intelligence to find new trends. Fashion Snoops, for example, employs artificial intelligence to scour the internet for buzzwords and new terminology that have the potential to evolve into something stylish.
What are the benefits?
Supply Chain Management
One of the most significant impacts of AI in fashion is in the area of supply chain management. With AI models capable of being trained by historical inventory levels and sales performance to predict future sales, businesses can make more informed decisions about what to stock and when. This can help reduce waste, improve customer satisfaction, and increase profits. This is one of the most significant benefits of AI in fashion, as it has the potential to streamline the entire supply chain process.
AI is also changing the way fashion businesses market their products. With AI-powered marketing tools, companies can analyze data to determine the best marketing strategies, target the right customers, and maximize the impact of their advertising. This saves time and money and helps businesses get ahead of the competition by identifying new trends and emerging markets. This is an exciting development for the fashion industry, as it means companies can now reach new customers and generate more sales.
Another area where AI is having a significant impact is in the design process. With AI algorithms predicting trends and analyzing customer preferences, fashion businesses can create designs more likely to be popular with their target market and reduce the risk of producing designs that don’t sell. This is particularly exciting, as it opens up new opportunities for businesses to create innovative and market-driven designs.
However, despite these benefits, there are also challenges to consider regarding AI in fashion.
What are the challenges?
Effects On The Human Workforce
One of the biggest concerns is the potential for AI to replace human labour. With AI algorithms capable of doing the jobs of designers, marketers and other fashion professionals, there is a risk that some jobs will be lost. This could have a significant impact on the fashion industry as a whole, as well as on the broader economy. This is a valid concern, and businesses must approach AI responsibly and ethically.
Another challenge is the potential for AI to make fashion more homogenized. With AI algorithms driving design and marketing decisions, there is a risk that fashion will become less individual and less creative. This could lead to a decline in the quality of fashion products and a decrease in the popularity of the overall industry. This is a genuine concern, and it’s up to the industry as a whole to ensure that AI is used in a way that promotes creativity and diversity.
Despite these challenges, much of the fashion industry embraces AI with open arms. With its ability to analyze data and make predictions, AI offers businesses new opportunities to streamline operations and reach new heights. From improving supply chain management to revolutionizing the design process, AI is transforming the fashion industry and changing how businesses operate.
So, what’s the verdict? Is AI in fashion a love or a hate relationship? The truth is, it’s both. While AI has the potential to revolutionize the fashion industry, it also poses new challenges that businesses will need to address. However, as with any technology, the benefits and drawbacks of AI in fashion are all a matter of perspective. And with the right approach, businesses can use AI to drive growth and improve their bottom line.
Hot or not?
For fashion brands, AI and ML can be game-changers. It will allow for faster customer service, better user experiences in the store environment, and more sustainable business practices. The future of fashion is looking bright!
Helpful or Not? Did you learn something new?
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