Market analysis and insights
The global market for artificial intelligence (AI) in fashion was initially expected to be worth US$1.3 billion in 2022 and is anticipated to increase to US$16.4 billion by 2030, expanding at a CAGR of 37.4% from 2022 to 2030.
The expansion of AI in the fashion sector is being driven by the expanding impact of social media on the sector. As there are numerous opinions and information from all sources worldwide on social media, it is a major source of information for the fashion business. The major sources of fashion nowadays are brand advertising and social media-savvy fashion influencers who share their thoughts on the latest trends.
AI in Fashion Market Market Scope :
Metrics | Details |
Base Year | 2023 |
Historic Data | 2018-2022 |
Forecast Period | 2024-2030 |
Study Period | 2018-2030 |
Forecast Unit | Value (USD) |
Revenue forecast in 2030 | USD 16.4 Billion |
Growth Rate | CAGR of 37.4% during 2021-2030 |
Segment Covered | By Component, By Application, By Deemployment, By Type, By End User, Regions |
Regions Covered | North America, Europe, Asia Pacific, South America, Middle East and Africa |
Key Players Profiled | SAP SE, Amazon Web Services, Inc., Huawei Technologies Co., Ltd., IBM Corporation, Oracle Corporation, Microsoft Corporation, Adobe, Google LLC, Facebook, Inc., and Heuritech |
Market Definition
Artificial intelligence (AI) and machine learning technologies are used in the fashion industry to improve a number of different parts of the fashion lifecycle.
AI can completely change how clothing is created, sold, and worn. AI can help fashion designers create original and cutting-edge computing designs. AI algorithms may propose new combinations of patterns, colors, and styles by analyzing enormous quantities of historical fashion data and comprehending trends, assisting designers in coming up with original concepts.
Customers receive personalized shopping experiences thanks to AI-powered recommendation systems. In order to make product recommendations that are in line with specific interests, these systems analyze user data such as browsing history, purchasing patterns, and preferences. Customers may view how clothing items might appear on them without physically trying them on, thanks to AI-enabled virtual fitting rooms. This improves the experience of purchasing online and lowers the percentage of returns. By forecasting demand for certain fashion goods, improving inventory management, and lowering overstocking or stockouts, AI may improve the supply chain.
Key Market Segmentation
Insights on Type
The Solution Segment Valued for the Highest Share
The solution segment performs better than the services segment and is predicted to continue to develop more rapidly in the future due to a greater acceptance rate. Modern technology that may simplify their business procedures and help them draw in new clients is being adopted by fashion shops at an increasing rate. Furthermore, it is now difficult for businesses to recognize current trends across various social media channels and to meet all of their customers' needs. Because of this, fashion retailers and brands are gradually using AI-based solutions, including platform and software tools like APIs, SDKs, and ML models.
Insights on Deployment Mode
The cloud-based segment valued for the highest share
The adoption of cloud-based AI solutions in the fashion industry is anticipated to be fueled by advancements in integration and scalability along with ease of deployment, while on-premises AI solutions are more popular due to their advantages in data privacy and security.
Insights on the Region
The APAC region accounted for the highest share.
Asia-Pacific is the area with the fastest economic growth on a global scale because of the expansion of the healthcare industry and the rise in nappy demand brought on by the rising population. As the population in the aforementioned regions is predicted to expand significantly over the next ten years, it is possible that demand for diapers from Oceania, Central and Southern Asia, and other countries may rise. As a result, there has been a rapid increase in the use of ultra-absorbent polymer in the production of baby diapers. Throughout the forecast period, this element is anticipated to fuel the market for super-absorbent polymers.
Key Company Profiles
SAP SE, Amazon Web Services, Inc., Huawei Technologies Co., Ltd., IBM Corporation, Oracle Corporation, Microsoft Corporation, Adobe, Google LLC, Facebook, Inc., and Heuritech are a few significant market players in the market.
COVID-19 Impact and Market Status
Online purchasing increased while physical establishments closed or were subject to limitations as a result of lockdowns and social distancing tactics.
To serve the growing number of digital customers, AI-driven customization and recommendation systems become more urgently necessary.
Global supply networks were interrupted by the epidemic, which delayed production and delivery. Fashion firms now depend on AI tools like demand forecasting and predictive analytics to efficiently manage their inventory and cut waste.
The customer's inability or reluctance to visit actual stores raised the need for virtual try-on and fitting solutions. AI-driven augmented reality (AR) technology and virtual changing rooms have gained popularity to enhance the online shopping experience.
COVID-Fashion shows, events, and exhibitions were canceled or virtualized as a result of 19 limitations. To display their collections, some fashion labels experimented with AI-powered virtual fashion presentations.
Even if the fashion sector was already paying more attention to sustainability, the epidemic brought to light how crucial ethical and environmentally responsible behavior is. It became more important for AI to support sustainable practices like material selection and supply chain optimization.
Latest Trends
1. AI tools were getting more adept at helping fashion designers with their designs. They may produce creative concepts and recommend fresh combinations of patterns, colors, and styles by analyzing enormous volumes of historical data, fashion trends, and consumer preferences.
2. With the help of their cellphones or laptops, shoppers could increasingly ""try on"" garments thanks to virtual try-on technology. Before making a purchase, customers may get a better idea of how clothes will fit and appear thanks to AR-powered experiences.
3. Brands were utilizing AI more and more to give clients individualized purchasing experiences. To provide customized product suggestions, individualized style advice, and targeted marketing initiatives, AI systems analyzed user data.
4. The fashion sector was using AI to promote sustainability. AI was crucial in supporting environmentally friendly behaviors, from streamlining supply chains to minimizing waste through demand forecasting.
5. AI-powered chatbots were used to improve customer assistance and service. These virtual assistants may answer client questions, give product details, and help customers shop.
6. To recognize patterns, brands, and designs in photos, AI models were created. This skill helped with activities like copyright protection, trend detection, and locating fake goods.
Significant Growth Factors
One of the main factors influencing AI adoption in the fashion sector was the rising need for more personalized shopping experiences. Artificial intelligence-powered recommendation engines and virtual stylists suited to specific client tastes increase client pleasure and loyalty.
AI technologies are required to enhance the digital purchasing experience due to the growth of e-commerce and online shopping. Online shops now depend on technologies like virtual try-ons, size suggestions, and shopping assistants.
Fashion firms were able to use AI to benefit from big data and analytics for data-driven decision-making. To make educated decisions regarding designs, manufacturing, and marketing tactics, brands might examine customer behavior, trends, and market knowledge.
The fashion supply chain was optimized using the predictive power of AI. AI streamlined processes and reduced costs by anticipating demand, improving inventory management, and cutting lead times.
The apparel industry's push for sustainability benefited from AI. Brands might choose more eco-friendly options and appeal to consumers who care about the environment by analyzing the environmental effects of materials and processes.
AI technologies became increasingly accessible and economical for fashion firms of all sizes as they continued to improve. This promoted broader adoption throughout the sector.
Restraining Factors
It can be expensive to implement AI solutions, especially for smaller, less resource-rich fashion enterprises. Getting integrated with current systems and procedures might be difficult.
Huge volumes of data, especially information about customers, are used by AI systems. Because of growing legislation like GDPR, fashion firms now have serious concerns about data security and privacy.
AI system development and upkeep require specialized knowledge. Fashion firms trying to use AI efficiently faced a hurdle due to the lack of qualified AI personnel.
Due to worries about accuracy or privacy, some customers can be reluctant to adopt AI-driven technology, including virtual try-ons or personalized suggestions. The use of creativity and human intuition in the fashion business has a long history. It could be difficult to persuade conventional stakeholders to accept AI-driven decision-making.
Recent Developments in the Global AI in Fashion Market: A Snapshot
• Slyce was purchased by Israel-based software development business Syte Business in September 2021 for an unknown sum. By making this acquisition, Syte hopes to service both new and existing customers while growing its market in North America. An American visual search business called Slyce has combined website and app technologies for more than 60 merchants.