February 2024
AI in Fashion Market (By Component: Solution, Services; By Deployment: Product Recommendation, Product Search and Discovery, Supply Chain Management and Demand Forecasting, Creative Designing and Trend Forecasting, Customer Relationship Management, Virtual Assistants; By Application: Cloud, On-premises; By Type: Apparel, Accessories, Footwear, Beauty and Cosmetics, Jewelry and Watches; By End-User) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2024-2033
The global AI in fashion market size reached USD 1.58 billion in 2023 and is estimated to hit around USD 49.07 billion by 2033 with a CAGR of 41% from 2024 to 2033. The increasing demand for the upcoming fashion trends and the growing fashion industry is driving the growth of AI in fashion market.
AI in Fashion Market Overview
AI (Artificial Intelligence) is the revolutionary technological advancement in the world. AI is used by various industries to enhance operational efficiency, profitability, productivity, etc. In recent eras, AI has been highly appreciated by the fashion industry and it is considered a revolutionary factor in the fashion industry. The global AI in fashion market offers benefits to various functional areas such as marketing, supply chain management, and design. Artificial intelligence could release the access load. Supply chain management is highly impacted by AI in fashion, though the AI model is previously trained with the sales performance and inventory levels for the prediction of future sales and to make more informed decisions regarding the inventory level.
AI is capable of predictive analytics and computer vision in identifying product features. AI helps in analyzing the search behaviors of the consumer and shows frequent results by depending upon the search history and shows results according to the searched color, brand, size, trend, fashion, etc. The increasing use of technology and the fashion retail industry is driving the growth of AI in the fashion market.
Report Coverage | Details |
Growth Rate from 2024 to 2033 | CAGR of 41% |
Global Market Size in 2023 | USD 1.58 Billion |
Global Market Size by 2033 | USD 49.07 Billion |
Largest Market | North America |
Base Year | 2022 |
Forecast Period | 2024 to 2033 |
Segments Covered | By Component, By Deployment, By Application, By Type, and By End-User |
Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Drivers
Product design and development
AI could help in product designing and development, the AI tools are highly combined with the product development and designing process. Artificial intelligence tools optimize patterns for increasing material efficiency, the tools can suggest designs and can make virtual prototypes of the clothing item. Designers can use that prototype design with different fabrics, colors, and materials to make the final product. Thereby, the implementation of artificial intelligence as a generative technology for design and development acts as a driver for the AI in fashion market.
Predictive forecasting and buying
AI also plays an important role in the predictive trends and buying within the fashion industry analyzing the existing data source, social media trends, latest and historical fashion trends, and sales data. Its predictive data analytics helps in predicting upcoming fashion trends by analyzing consumer trends and buying patterns. These tools can help fashion organizations stay tuned with the current fashion insights to make informed decisions for inventory levels. Both of these factors are highly contributing to the growing demand for artificial intelligence in the fashion industry and drive the growth of the AI in fashion market.
Restraint
Lack of skilled professionals
Implementing AI in the fashion industry requires a deep understanding of both fashion and artificial intelligence technologies. Skilled professionals are needed to develop, deploy, and maintain AI algorithms and systems tailored to the specific needs of the fashion sector. Without a sufficient pool of skilled professionals with expertise in both domains, companies may struggle to effectively leverage AI to its full potential. The demand for skilled professionals in AI, data science, and related fields far exceeds the supply, leading to a talent shortage in the job market. Fashion companies may struggle to attract and retain qualified candidates with the necessary technical skills, domain expertise, and creative vision to drive AI initiatives forward.
Opportunity
The rising demand for fashion sustainability
The fashion industry is majorly focusing on sustainability in fashion and responsible sourcing of materials. Artificial intelligence plays a vital role in the selection of sustainable materials for products. AI algorithms analyze several factors ethical sourcing practices, environmental impacts of materials, and cost-effectiveness. Artificial intelligence helps to make informed decisions about the type of material that is used in the products. AI algorithms help to meet the rising demand for sustainable fashion due to the rising environmental concern among consumers. Thereby, the sustainability demand is observed to offer opportunity for the AI in fashion market.
Personalization in fashion
AI also offers a personalized experience to the consumers, it allows the consumers to personalized clothing items as per their choice, brands, colors, etc. AI offers a vast number of customization options to customers like selling their preferred fabric material, color choices, designs, and personal touches like embroidery. Customers can design their apparel with the use of AI applications. The personalization application offered by the AI in fashion industry is enhancing the customer experience and contributing to the demand for personalized fashion. Increasing interest in the personalized fashion experience in the population mainly in the new-age population drives accelerating the growth of the AI in the fashion market.
The solution segment dominated AI in the fashion market in 2023. The growth of the segment is attributed to the rising adoption of software tools and applications and online shopping platforms such as e-commerce and social media applications are driving the demand for the solution segment. The rising penetration of smart technologies such as smartphones, and the rising use of the internet are contributing to the digitization of the fashion industry. AI uses tools such as predictive analytics to analyze consumer behavior by their search history, buying experiences, choices, etc., and shows the results according to that.
The rising use of the internet for promoting the latest fashion trends by celebrities, and influencers on social media is accelerating the growth of the fashion industry. Furthermore, the rising number of e-commerce industries is contributing to the increasing demand for artificial intelligence tools and applications for analyzing consumer behavior and making informed decisions.
The cloud segment had the largest share of the market in 2023. The growth of the segment is attributed to the rising use of cloud technology due to its flexibility and adaptability in the fashion industry. Digital transformation across various regions is driving the demand for additional data security. Many major fashion brands are adopting cloud technology, as brands have decided that cloud technology is more convenient for government rules and regulations. Cloud computing provides more cost-effective operations than on-premise deployment and effectively manages the information and services that contribute to the growth of the market.
The product recommendation segment dominated AI in fashion market in 2023. The growth of the segment is attributed to the rising number of e-commerce platforms driving the growth of the segment. AI recommended products by visual detection and key product attributes show visually similar products on the fashion retailers’ online store or e-commerce platforms. At the stage of the products are unavailable or out of stock or size, AI recommends or redirects the customers to the multiple relevant product pages on the online shopping platform, and the consumer easily finds the products they are looking for without restarting the product search. Product recommendation offers personalized recommendations such as personalization per region, personalization per customer segment, and personalization per individual customer.
Product search and discovery is expected to increase its growth in the market in 2023. Product search and discovery include several factors such as automated product tagging, natural language search, visual search, personalized landing page, and personalized product ranking. Automating manual product tagging in artificial intelligence improves processing times, richer data, lowers cost and increases consistency without human bias. Efficient product search and discovery enhances the customer shopping experience and drives the growth of AI in fashion market.
The apparel segment dominated the market with the largest share in 2023. The growth of the segment is attributed to the continuous demand for the apparel segment across the globe is driving the demand for the segment. The growing population leads to the rising demand for the apparel industry. Artificial intelligence helps in meeting the growing demand for the apparel industry by improving material grading, automated data gathering, and asset management, minimizing errors to the final product inspection. Personalized and sustainable manufacturing is one of the major areas where AI is impacting the most. Thus the growing demand and management of the apparel manufacturing process boost the growth of the market.
The accessories segment is expected to increase its market growth during the forecast period. The increasing demand for accessories in both males and females driving the growth of the segment. Artificial intelligence analyzes consumer preferences, and demand forecasting trends, and recommends customized accessories for enhancing consumer satisfaction and increasing sales.
The fashion designers segment held the largest share of the AI in fashion market in 2023. Artificial intelligence transforms the way fashion products are manufactured, designed, and marketed. By the use of AI tools such as deep learning, machine learning, and computer vision, fashion designers can create and explore the latest opportunities, innovate the latest concepts, and generate personalized products according to the individual's preferences. With the use of AI, designers are allowed to streamline their operations, make more informed decisions, and create stylish designs with sustainability. With the integration of AI into the fashion industry designers can meet the changing demand of consumers and create new opportunities from it.
North America led the AI in the fashion market with the largest market share in 2023. The rising technological advancement in every sector and the early adoption of artificial intelligence in industrial applications are driving the growth of the AI in fashion market. The rising trends in the fashion industry in countries like the United States, and Canada are boosting the demand for AI technology for the management of the growing fashion industry with sustainability, better productivity, and sales. The increasing presence of the major technology giants in the regional countries is also contributing to the growth of the AI in fashion market across the region.
Asia Pacific is expected to witness the fastest growth in the AI in fashion market during the forecast period. The increasing population and the rising demand for the clothing industry are driving the growth of the market. The increasing penetration of technologies such as smartphones, the use of social media, and the growing number of customers in the e-commerce industry are driving the growth of the market. The growing e-commerce industry in countries like China, India, and Japan is accelerating the fashion industry. Additionally, supportive government regulation for digitization is boosting the growth of the AI in fashion market across the region.
Segments Covered in the Report
By Component
By Deployment
By Application
By Type
By End-User
By Geography
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