Artificial intelligence (AI) has already begun to revolutionize the fashion industry.
Read this article to find out what fashion professionals can expect from AI in 2022.
Zara, H&M, Dior, Macy’s, and Nike are just a few examples of well-known fashion brands that use AI in their business models. This technology enables companies to attract more customers, cut down expenses, get additional competitive edges, and boost revenues. In this article, you’ll find examples of exactly how fashion brands can benefit from AI. All these cases will be industry-specific and not generic, such as employing chatbots or opening cashless stores.
AI-Generated Product Photos
Fashion is one of the most wasteful industries on a global scale. Every year, it generates roughly 92 million tons of textile waste. More and more businesses are opening their own second-hand marketplaces. Consumers are increasingly turning to companies that produce sustainable clothing collections. Nevertheless, unsold items remain a major issue—and AI might help businesses solve it.
Previously, fashion brands were too prone to overstocking. They lacked tools that enabled them to accurately predict which items will enjoy the highest demand. Companies had to rely on the opinions of their human employees. Now, they can rely on historical product data to carry out predictive analytics and trend forecasting. AI can analyze the color, print, and cut of trending products as well as consumers’ response to them on social media. Besides, AI inventory optimization enables fashion retailers to determine the optimal geographical allocation and market drop calendar for their new product catalogs.
Forward-thinking companies can create realistic images of virtual garments and accessories based on consumer demands and fashion trends. They can share these pictures on social media or e-commerce platforms to check how people react to them. Brands will submit clothing designs to manufacturers—only if consumers approve of the virtual model. AI enables companies to precisely measure the demand and prevent the problem of unsold inventory.
Model shots can boost garment, shoes, and accessories sales by up to 60%. But when the pandemic broke out, brands were typically unable to bring models in for photoshoots safely. Ecommerce platforms were afraid that would affect their sales. But some of them came up with a creative way out: they mapped virtual copies of their products on the bodies of their models, providing consumers with realistic garment images. Obtaining photos of these models remotely enabled brands to boost their sales.
Developers have already released algorithms that can modify the poses of models and the clothes they’re wearing without losing important details. Moreover, brands can generate tailor-made models for themselves. These models look incredibly realistic. When consumers see a photo or video of this boy or girl, they can never guess it’s just an AI-generated image. So far, digital models can’t move as freely as their human counterparts. They can only copy the poses of real people. But in the next few years, the industry should be able to overcome this challenge.
It’s hard to say whether digital models will become commonplace. Right now, brands might want to use them because it’s a fresh concept that can easily attract consumers’ attention. Plus, this technology enables companies to emphasize how eco-conscious they are. Most samples that human models shoot end up in landfills, while digital technologies can help cut down on the environmental waste. Besides, digital models can enable businesses to reduce their expenses.
Stores can use the same body mapping technology in their virtual fitting rooms. Consumers can upload their photos and try on fashion items digitally before the purchase. They should allow retailers to maximize their sales and revenues. Customers should be happy because AI can recommend the products that will suit them best. Clients will only try on those things that make them look stunning and will gladly return to this store over-and-over again.
Fashion NFTs Designed by AI
The NFT acronym stands for non-fungible tokens. These digital assets are stored on a blockchain and can be anything: pictures, videos, songs, texts, or garments. Each NFT is unique. You can’t swap your token for any other one even if it has the same value. This technology caused a sensation in 2021.
Fashion brands already release NFTs in parallel to their physical collections. Such products exist only in virtual reality and customers might be ready to pay huge sums for them—up to several million dollars. After you purchase an NFT, you can wear it on your digital avatar.
AI is just as good at creating NFTs as human professionals—or perhaps even better. It draws inspiration from already existing sneakers, analyzes their parameters, and comes up with innovative models that are released in a single copy. In theory, AI should be able to deliver hyper-customized items much quicker than the most skilled designer.
Blockchain Combats Counterfeit Products
Blockchain is a distributed ledger technology that can be used for various purposes, such as backing up cryptocurrencies or storing records about any type of transaction (marriages, deaths, buying properties, and so on). Fashion retailers can attach a label to each of their products to define its origin and ownership. Thanks to the nature of blockchain, it will be impossible to modify the information on those labels. Any member of the supply chain will be able to check at any moment where the item was produced, who owned it, and when it changed hands. You can find out all the relevant details—from raw material acquisition and factory information—down to how the finished products were packaged and delivered.
Similarly, brands can use near-field communication (NFC) chips to tag their items. By scanning the information from the tag, consumers can get to know everything about the product they want to buy.
Hopefully, this article came in handy and now you understand the benefits of using artificial intelligence in fashion retail better. AI can organize virtual photoshoots and commission digital product photos. AI can design NFTs and blockchain can combat counterfeit products. The sooner a company jumps on board these amazing technological opportunities, the greater competitive edge it will obtain.
Artificial Intelligence in the 4th Industrial Revolution
Artificial intelligence is providing disruptive changes in the 4th industrial revolution (Industry 4.0) by increasing interconnectivity and smart automation.
Industry 4.0 is revolutionizing the way companies manufacture, improve and distribute their products.
What Makes Artificial Intelligence Unique?
Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.
It allows computers to think and behave like humans, but at much faster speeds and with much more processing power than the human brain can produce.
AI offers advantages of new and innovative services, and the potential to improve scale, speed and accuracy.
There are 3 types of artificial intelligence:
Artificial narrow intelligence (ANI), which has a narrow range of abilities.
Artificial general intelligence (AGI), which is on par with human capabilities.
Artificial superintelligence (ASI), which is more capable than a human.
Artificial intelligence can also be classified as weak or strong.
Weak AI refers to systems that are programmed to accomplish a wide range of problems but operate within a predetermined or pre-defined range of functions. Strong AI, on the other hand, refers to machines that exhibit human intelligence.
Artificial intelligence has several subsets:
Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing.
What is the Fourth Industrial Revolution?
The Fourth Industrial Revolution is the current and developing environment in which disruptive technologies and trends such as the Internet of Things (IoT), robotics, virtual reality (VR) and artificial intelligence (AI) are changing the way modern people live and work. The integration of these technologies into manufacturing practices is known as Industry 4.0.
The first industrial revolution used water and steam power to mechanize production.
The second used electric power to create mass production.
The third used electronics and information technology to automate production.
The fourth Industrial revolution is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres, with rising emerging technologies, as real AI, Narrow AI/ML/DL, robotics, automation, materials science, energy storage, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, neurotechnology, cognitive technology, and quantum computing. It implies radical disruptions to everything, industries, jobs, works, technologies, and old human conditions. In its scale, scope, complexity, and impact, the AI transformation will be unlike anything humankind has experienced before.
The Role of Artificial Intelligence in the 4th Industrial Revolution
Artificial intelligence is making companies make the best use of practical experience, even displacing traditional labor and becoming the productive factor itself.
It offers entirely new paths towards growth for manufacturing, service, and other industries, reshaping the world economy and bringing new opportunities for our societal development.
As AI begins to impact the workforce and automation replaces some existing skills, we’re seeing an increased need for emotional intelligence, creativity, and critical thinking.
Zvika Krieger, co-leader of the World Economic Forum’s Center for the Fourth Industrial Revolution.
Deploying AI requires a kind of reboot in the way companies think about privacy and security, As data becomes the currency of our digital lives, companies must ensure the privacy and security of customer information.
Businesses will need to ensure they have the right mix of skills in their workforce to keep pace with changing technology.
How Brands are Investing in Video Marketing On a Budget [2022 Data]
Murdered rapper’s song pulled from YouTube in India
A Simple (But Complete) Guide
The future of commerce is social. 5 brands getting it right.
7 Tips to Grow Your Audience on Every Social Media Platform [Infographic]
Surfer SEO Unveils New Semrush Integration
7 Email Marketing Mistakes Killing Your Mobile Conversion Rate [Infographic]
A Complete Google Search Console Guide For SEO Pros
Aurora Morales Recording Again in A Real Google Studio
New Updates To Google Page Experience Scoring Revealed At SEODay
Why Google Doesn’t Like Some SEO Metrics
Google Bar & Pool Table Room
6 Tactics to Boost Ecommerce Sales [Without Discounting]
How Software Systems Enhance the Performance of Gym Business?
9 Creative Company Profile Examples to Inspire You [Templates]
How to Calculate Your Lead Generation Goals [Free Calculator]
Strategizing Your Instagram Marketing – DigitalMarketer
How To Build A Remote Team For SEO: Planning & Structure
Google Hints That Useful Nofollow Links Won’t Pass Weight (Or Much Of It)
6 New SEO Tools That Predict Google Algorithm Update Impacts
SEARCHENGINES7 days ago
Good Web Sites Are Good For SEO, Says Google
SEARCHENGINES7 days ago
Alcides Aguasvivas On Proper Infrastructure For Sites To Perform Well In Search
SEARCHENGINES7 days ago
Daily Search Forum Recap: June 20, 2022
SEARCHENGINES4 days ago
Google No Longer Lowers Importance Of Content Not Visible On Page