AI in Fashion Market Scope
Fashion is a growing industry with economic and social implications worldwide. With the advent of modern cognitive computing technologies such as machine learning, deep learning, virtual reality, and natural language processing for analyzing huge amounts of fashion data, the impact of AI in the fashion industry is transforming. Additionally, fashion brands are using machine learning and AI for maximizing customer shopping experience and enhancing the efficiency of sales systems through intelligent process automation using predictive analytics and well-organized sales processes. Moreover, growth in the fast fashion retail industry expected to fuel the growth of AI in the fashion market during the forecasted period.
According to AMA, the Global AI in Fashion market is expected to see growth rate of 38.19% Research Analyst at AMA estimates that United States Players will contribute to the maximum growth of Global AI in Fashion market throughout the predicted period.
Microsoft (United States), IBM (United States), Google (United States), AWS (United States), SAP (Germany), Facebook (United States), Adobe (United States), Oracle (United States), Catchoom (Spain), Huawei (China), Vue.ai (United States), Heuritech (France), Wide Eyes (Spain), FINDMINE (United States), Intelistyle (England) and Lily AI (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research are Pttrns.ai (Netherlands), Syte (Israel), Mode.ai (United States) and Stitch Fix (United States).
Segmentation Overview
The study have segmented the market of Global AI in Fashion market , by Application (Product Recommendation, Product Search and Discovery, Supply Chain Management and Demand Forecasting, Creative Designing and Trend Forecasting, Customer Relationship Management, Virtual Assistants and Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization]) and Region with country level break-up.
On the basis of geography, the market of AI in Fashion has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico).
Influencing Trend:
Increasing Influence of Social Media on the Fashion Industry and Growing Fast Fashion Retail Industry
Market Growth Drivers:
Rising Customer Demand for Personalized Fashion Experience and Growing Need for Automated Inventory Management in Fashion Industry
Challenges:
Lack of Awareness among End Users
Restraints:
Difficult Integration with Legacy Systems
Opportunities:
Emergence of Technologies Such As Machine Learning, Deep Learning, Natural Language Processing, and Virtual Reality in Fashion Industry and Growing Demand from the Developing Economies
15th October 2019, Amazon Fashion launched a new AI-powered StyleSnap feature integrated with matching learning technology to find style and clothing by analyzing a photo to its application. This tool is currently available in Germany and the United Kingdom for bottoms, tops, dresses, bags, and shoes in menswear and womenswear categories.
Key Target Audience
AI in Fashion Providers, Technology Providers, Potential Investors, Government and Research Organizations, Trade Associations and Industry Bodies and Others
About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a
preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from the total available market.