Global AI in Fashion Market
Global AI in Fashion Market

AI in Fashion Comprehensive Study by Application (Product Recommendation, Product Search and Discovery, Supply Chain Management and Demand Forecasting, Creative Designing and Trend Forecasting, Customer Relationship Management, Virtual Assistants, Others (Fraud Detection, Fabric Waste Reduction, and Price Optimization)), Deployment Mode (Cloud, On-Premises), Category (Apparel, Accessories, Footwear, Beauty & Cosmetics, Jewelry & Watches, Others (Eyewear, Home Decor)), End-User (Fashion Designers, Fashion Stores), Component (Solution (Software Tools, Platforms), Services (Training and Consulting, System Integration and Testing, Support and Maintenance)) Players and Region - Global Market Outlook to 2024

AI in Fashion Market Segmented into XX Submarkets. | Forecast Years: 2021- 2026 | CAGR: 38.19%  

Dec 2019 Edition 212 Pages 211 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
Global AI in Fashion Market Overview:
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. Some of the key players profiled in the study are 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). According to Market Analyst at AMA, the Global AI in Fashion market may see a growth rate of 38.19%

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). If we see Market by Deployment Mode, the sub-segment i.e. Cloud will boost the AI in Fashion market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Category, the sub-segment i.e. Apparel will boost the AI in Fashion market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by End-User, the sub-segment i.e. Fashion Designers will boost the AI in Fashion market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by Component, the sub-segment i.e. Solution [Software Tools, Platforms] will boost the AI in Fashion market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.

Market Drivers
  • Rising Customer Demand for Personalized Fashion Experience
  • Growing Need for Automated Inventory Management in Fashion Industry

Market Trend
  • Increasing Influence of Social Media on the Fashion Industry
  • Growing Fast Fashion Retail Industry

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
  • Growing Demand from the Developing Economies

Challenges
  • Lack of Awareness among End Users


Major Market Developments:


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.

Target Audience:
AI in Fashion Providers, Technology Providers, Potential Investors, Government and Research Organizations, Trade Associations and Industry Bodies and Others

Major Objectives Focused through this Study
• To define, describe, and forecast the Global AI in Fashion market on the basis of product [] , 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]], key regions and end user
• To provide in-depth information regarding major influencing factors affecting the growth of the market (trends, drivers, restraints, opportunities, and industry-centric and regional challenges)
• To strategically analyse the micro-markets and important business segments with respect to individual growth drivers , market trends and potential, and historical contributions to the total market
• Identifying the opportunities in the market for key stakeholders and detailing the competitive landscape for market leaders
• To provide market size for various segments of the AI in Fashion market with respect to major geographies, namely, 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)
• To strategically profile the key players and analyzing their market shares and core competencies in the AI in Fashion industry
• To track key developments such as product launches, expansions, agreements, partnerships, mergers & acquisitions, and R&D activities that are key factors in shaping the market

Available Customization:
Data related to EXIM [Export- Import], production & consumption by country or regional level break-up can be provided based on client request**. 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).
** Confirmation on availability of data would be informed prior purchase

While framing the research framework, major and emerging players operating in the AI in Fashion market in various regions have been profiled, and their offerings, geographic footprints, and distribution/sales channels have been analysed through in-depth discussions. Top-down and bottom-up approaches have been used to determine the overall market size. Sizes of the other individual markets have been estimated using the percentage splits obtained through secondary sources such as Hoovers, Bloomberg BusinessWeek, and Dow Jones (Factiva), along with primary respondents. The complete methodology includes the study of the annual and financial reports of the key market players and extensive interviews with industry experts such as CEOs, VPs, directors, and marketing executives for key insights (both qualitative and quantitative) related to the market.
Report Objectives / Segmentation Covered
By Application
  • Product Recommendation
  • Product Search and Discovery
  • Supply Chain Management and Demand Forecasting
  • Creative Designing and Trend Forecasting
  • Customer Relationship Management
  • Virtual Assistants
  • Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization]
By Deployment Mode
  • Cloud
  • On-Premises

By Category
  • Apparel
  • Accessories
  • Footwear
  • Beauty & Cosmetics
  • Jewelry & Watches
  • Others [Eyewear, Home Decor]

By End-User
  • Fashion Designers
  • Fashion Stores

By Component
  • Solution [Software Tools, Platforms]
  • Services [Training and Consulting, System Integration and Testing, Support and Maintenance]

By Regions
  • 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
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Rising Customer Demand for Personalized Fashion Experience
      • 3.2.2. Growing Need for Automated Inventory Management in Fashion Industry
    • 3.3. Market Challenges
      • 3.3.1. Lack of Awareness among End Users
    • 3.4. Market Trends
      • 3.4.1. Increasing Influence of Social Media on the Fashion Industry
      • 3.4.2. Growing Fast Fashion Retail Industry
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global AI in Fashion, by Application, Deployment Mode, Category, End-User, Component and Region (value) (2013-2018)
    • 5.1. Introduction
    • 5.2. Global AI in Fashion (Value)
      • 5.2.1. Global AI in Fashion by: Application (Value)
        • 5.2.1.1. Product Recommendation
        • 5.2.1.2. Product Search and Discovery
        • 5.2.1.3. Supply Chain Management and Demand Forecasting
        • 5.2.1.4. Creative Designing and Trend Forecasting
        • 5.2.1.5. Customer Relationship Management
        • 5.2.1.6. Virtual Assistants
        • 5.2.1.7. Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization]
      • 5.2.2. Global AI in Fashion by: Deployment Mode (Value)
        • 5.2.2.1. Cloud
        • 5.2.2.2. On-Premises
      • 5.2.3. Global AI in Fashion by: Category (Value)
        • 5.2.3.1. Apparel
        • 5.2.3.2. Accessories
        • 5.2.3.3. Footwear
        • 5.2.3.4. Beauty & Cosmetics
        • 5.2.3.5. Jewelry & Watches
        • 5.2.3.6. Others [Eyewear, Home Decor]
      • 5.2.4. Global AI in Fashion by: End-User (Value)
        • 5.2.4.1. Fashion Designers
        • 5.2.4.2. Fashion Stores
      • 5.2.5. Global AI in Fashion by: Component (Value)
        • 5.2.5.1. Solution [Software Tools, Platforms]
        • 5.2.5.2. Services [Training and Consulting, System Integration and Testing, Support and Maintenance]
      • 5.2.6. Global AI in Fashion Region
        • 5.2.6.1. South America
          • 5.2.6.1.1. Brazil
          • 5.2.6.1.2. Argentina
          • 5.2.6.1.3. Rest of South America
        • 5.2.6.2. Asia Pacific
          • 5.2.6.2.1. China
          • 5.2.6.2.2. Japan
          • 5.2.6.2.3. India
          • 5.2.6.2.4. South Korea
          • 5.2.6.2.5. Taiwan
          • 5.2.6.2.6. Australia
          • 5.2.6.2.7. Rest of Asia-Pacific
        • 5.2.6.3. Europe
          • 5.2.6.3.1. Germany
          • 5.2.6.3.2. France
          • 5.2.6.3.3. Italy
          • 5.2.6.3.4. United Kingdom
          • 5.2.6.3.5. Netherlands
          • 5.2.6.3.6. Rest of Europe
        • 5.2.6.4. MEA
          • 5.2.6.4.1. Middle East
          • 5.2.6.4.2. Africa
        • 5.2.6.5. North America
          • 5.2.6.5.1. United States
          • 5.2.6.5.2. Canada
          • 5.2.6.5.3. Mexico
  • 6. AI in Fashion: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2018)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Microsoft (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. IBM (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Google (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. AWS (United States)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. SAP (Germany)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Facebook (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Adobe (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Oracle (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Catchoom (Spain)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Huawei (China)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. Vue.ai (United States)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Heuritech (France)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
      • 6.4.13. Wide Eyes (Spain)
        • 6.4.13.1. Business Overview
        • 6.4.13.2. Products/Services Offerings
        • 6.4.13.3. Financial Analysis
        • 6.4.13.4. SWOT Analysis
      • 6.4.14. FINDMINE (United States)
        • 6.4.14.1. Business Overview
        • 6.4.14.2. Products/Services Offerings
        • 6.4.14.3. Financial Analysis
        • 6.4.14.4. SWOT Analysis
      • 6.4.15. Intelistyle (England)
        • 6.4.15.1. Business Overview
        • 6.4.15.2. Products/Services Offerings
        • 6.4.15.3. Financial Analysis
        • 6.4.15.4. SWOT Analysis
      • 6.4.16. Lily AI (United States)
        • 6.4.16.1. Business Overview
        • 6.4.16.2. Products/Services Offerings
        • 6.4.16.3. Financial Analysis
        • 6.4.16.4. SWOT Analysis
  • 7. Global AI in Fashion Sale, by Application, Deployment Mode, Category, End-User, Component and Region (value) (2019-2024)
    • 7.1. Introduction
    • 7.2. Global AI in Fashion (Value)
      • 7.2.1. Global AI in Fashion by: Application (Value)
        • 7.2.1.1. Product Recommendation
        • 7.2.1.2. Product Search and Discovery
        • 7.2.1.3. Supply Chain Management and Demand Forecasting
        • 7.2.1.4. Creative Designing and Trend Forecasting
        • 7.2.1.5. Customer Relationship Management
        • 7.2.1.6. Virtual Assistants
        • 7.2.1.7. Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization]
      • 7.2.2. Global AI in Fashion by: Deployment Mode (Value)
        • 7.2.2.1. Cloud
        • 7.2.2.2. On-Premises
      • 7.2.3. Global AI in Fashion by: Category (Value)
        • 7.2.3.1. Apparel
        • 7.2.3.2. Accessories
        • 7.2.3.3. Footwear
        • 7.2.3.4. Beauty & Cosmetics
        • 7.2.3.5. Jewelry & Watches
        • 7.2.3.6. Others [Eyewear, Home Decor]
      • 7.2.4. Global AI in Fashion by: End-User (Value)
        • 7.2.4.1. Fashion Designers
        • 7.2.4.2. Fashion Stores
      • 7.2.5. Global AI in Fashion by: Component (Value)
        • 7.2.5.1. Solution [Software Tools, Platforms]
        • 7.2.5.2. Services [Training and Consulting, System Integration and Testing, Support and Maintenance]
      • 7.2.6. Global AI in Fashion Region
        • 7.2.6.1. South America
          • 7.2.6.1.1. Brazil
          • 7.2.6.1.2. Argentina
          • 7.2.6.1.3. Rest of South America
        • 7.2.6.2. Asia Pacific
          • 7.2.6.2.1. China
          • 7.2.6.2.2. Japan
          • 7.2.6.2.3. India
          • 7.2.6.2.4. South Korea
          • 7.2.6.2.5. Taiwan
          • 7.2.6.2.6. Australia
          • 7.2.6.2.7. Rest of Asia-Pacific
        • 7.2.6.3. Europe
          • 7.2.6.3.1. Germany
          • 7.2.6.3.2. France
          • 7.2.6.3.3. Italy
          • 7.2.6.3.4. United Kingdom
          • 7.2.6.3.5. Netherlands
          • 7.2.6.3.6. Rest of Europe
        • 7.2.6.4. MEA
          • 7.2.6.4.1. Middle East
          • 7.2.6.4.2. Africa
        • 7.2.6.5. North America
          • 7.2.6.5.1. United States
          • 7.2.6.5.2. Canada
          • 7.2.6.5.3. Mexico
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. AI in Fashion: by Application(USD Million)
  • Table 2. AI in Fashion Product Recommendation , by Region USD Million (2013-2018)
  • Table 3. AI in Fashion Product Search and Discovery , by Region USD Million (2013-2018)
  • Table 4. AI in Fashion Supply Chain Management and Demand Forecasting , by Region USD Million (2013-2018)
  • Table 5. AI in Fashion Creative Designing and Trend Forecasting , by Region USD Million (2013-2018)
  • Table 6. AI in Fashion Customer Relationship Management , by Region USD Million (2013-2018)
  • Table 7. AI in Fashion Virtual Assistants , by Region USD Million (2013-2018)
  • Table 8. AI in Fashion Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization] , by Region USD Million (2013-2018)
  • Table 9. AI in Fashion: by Deployment Mode(USD Million)
  • Table 10. AI in Fashion Cloud , by Region USD Million (2013-2018)
  • Table 11. AI in Fashion On-Premises , by Region USD Million (2013-2018)
  • Table 12. AI in Fashion: by Category(USD Million)
  • Table 13. AI in Fashion Apparel , by Region USD Million (2013-2018)
  • Table 14. AI in Fashion Accessories , by Region USD Million (2013-2018)
  • Table 15. AI in Fashion Footwear , by Region USD Million (2013-2018)
  • Table 16. AI in Fashion Beauty & Cosmetics , by Region USD Million (2013-2018)
  • Table 17. AI in Fashion Jewelry & Watches , by Region USD Million (2013-2018)
  • Table 18. AI in Fashion Others [Eyewear, Home Decor] , by Region USD Million (2013-2018)
  • Table 19. AI in Fashion: by End-User(USD Million)
  • Table 20. AI in Fashion Fashion Designers , by Region USD Million (2013-2018)
  • Table 21. AI in Fashion Fashion Stores , by Region USD Million (2013-2018)
  • Table 22. AI in Fashion: by Component(USD Million)
  • Table 23. AI in Fashion Solution [Software Tools, Platforms] , by Region USD Million (2013-2018)
  • Table 24. AI in Fashion Services [Training and Consulting, System Integration and Testing, Support and Maintenance] , by Region USD Million (2013-2018)
  • Table 25. South America AI in Fashion, by Country USD Million (2013-2018)
  • Table 26. South America AI in Fashion, by Application USD Million (2013-2018)
  • Table 27. South America AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 28. South America AI in Fashion, by Category USD Million (2013-2018)
  • Table 29. South America AI in Fashion, by End-User USD Million (2013-2018)
  • Table 30. South America AI in Fashion, by Component USD Million (2013-2018)
  • Table 31. Brazil AI in Fashion, by Application USD Million (2013-2018)
  • Table 32. Brazil AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 33. Brazil AI in Fashion, by Category USD Million (2013-2018)
  • Table 34. Brazil AI in Fashion, by End-User USD Million (2013-2018)
  • Table 35. Brazil AI in Fashion, by Component USD Million (2013-2018)
  • Table 36. Argentina AI in Fashion, by Application USD Million (2013-2018)
  • Table 37. Argentina AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 38. Argentina AI in Fashion, by Category USD Million (2013-2018)
  • Table 39. Argentina AI in Fashion, by End-User USD Million (2013-2018)
  • Table 40. Argentina AI in Fashion, by Component USD Million (2013-2018)
  • Table 41. Rest of South America AI in Fashion, by Application USD Million (2013-2018)
  • Table 42. Rest of South America AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 43. Rest of South America AI in Fashion, by Category USD Million (2013-2018)
  • Table 44. Rest of South America AI in Fashion, by End-User USD Million (2013-2018)
  • Table 45. Rest of South America AI in Fashion, by Component USD Million (2013-2018)
  • Table 46. Asia Pacific AI in Fashion, by Country USD Million (2013-2018)
  • Table 47. Asia Pacific AI in Fashion, by Application USD Million (2013-2018)
  • Table 48. Asia Pacific AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 49. Asia Pacific AI in Fashion, by Category USD Million (2013-2018)
  • Table 50. Asia Pacific AI in Fashion, by End-User USD Million (2013-2018)
  • Table 51. Asia Pacific AI in Fashion, by Component USD Million (2013-2018)
  • Table 52. China AI in Fashion, by Application USD Million (2013-2018)
  • Table 53. China AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 54. China AI in Fashion, by Category USD Million (2013-2018)
  • Table 55. China AI in Fashion, by End-User USD Million (2013-2018)
  • Table 56. China AI in Fashion, by Component USD Million (2013-2018)
  • Table 57. Japan AI in Fashion, by Application USD Million (2013-2018)
  • Table 58. Japan AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 59. Japan AI in Fashion, by Category USD Million (2013-2018)
  • Table 60. Japan AI in Fashion, by End-User USD Million (2013-2018)
  • Table 61. Japan AI in Fashion, by Component USD Million (2013-2018)
  • Table 62. India AI in Fashion, by Application USD Million (2013-2018)
  • Table 63. India AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 64. India AI in Fashion, by Category USD Million (2013-2018)
  • Table 65. India AI in Fashion, by End-User USD Million (2013-2018)
  • Table 66. India AI in Fashion, by Component USD Million (2013-2018)
  • Table 67. South Korea AI in Fashion, by Application USD Million (2013-2018)
  • Table 68. South Korea AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 69. South Korea AI in Fashion, by Category USD Million (2013-2018)
  • Table 70. South Korea AI in Fashion, by End-User USD Million (2013-2018)
  • Table 71. South Korea AI in Fashion, by Component USD Million (2013-2018)
  • Table 72. Taiwan AI in Fashion, by Application USD Million (2013-2018)
  • Table 73. Taiwan AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 74. Taiwan AI in Fashion, by Category USD Million (2013-2018)
  • Table 75. Taiwan AI in Fashion, by End-User USD Million (2013-2018)
  • Table 76. Taiwan AI in Fashion, by Component USD Million (2013-2018)
  • Table 77. Australia AI in Fashion, by Application USD Million (2013-2018)
  • Table 78. Australia AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 79. Australia AI in Fashion, by Category USD Million (2013-2018)
  • Table 80. Australia AI in Fashion, by End-User USD Million (2013-2018)
  • Table 81. Australia AI in Fashion, by Component USD Million (2013-2018)
  • Table 82. Rest of Asia-Pacific AI in Fashion, by Application USD Million (2013-2018)
  • Table 83. Rest of Asia-Pacific AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 84. Rest of Asia-Pacific AI in Fashion, by Category USD Million (2013-2018)
  • Table 85. Rest of Asia-Pacific AI in Fashion, by End-User USD Million (2013-2018)
  • Table 86. Rest of Asia-Pacific AI in Fashion, by Component USD Million (2013-2018)
  • Table 87. Europe AI in Fashion, by Country USD Million (2013-2018)
  • Table 88. Europe AI in Fashion, by Application USD Million (2013-2018)
  • Table 89. Europe AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 90. Europe AI in Fashion, by Category USD Million (2013-2018)
  • Table 91. Europe AI in Fashion, by End-User USD Million (2013-2018)
  • Table 92. Europe AI in Fashion, by Component USD Million (2013-2018)
  • Table 93. Germany AI in Fashion, by Application USD Million (2013-2018)
  • Table 94. Germany AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 95. Germany AI in Fashion, by Category USD Million (2013-2018)
  • Table 96. Germany AI in Fashion, by End-User USD Million (2013-2018)
  • Table 97. Germany AI in Fashion, by Component USD Million (2013-2018)
  • Table 98. France AI in Fashion, by Application USD Million (2013-2018)
  • Table 99. France AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 100. France AI in Fashion, by Category USD Million (2013-2018)
  • Table 101. France AI in Fashion, by End-User USD Million (2013-2018)
  • Table 102. France AI in Fashion, by Component USD Million (2013-2018)
  • Table 103. Italy AI in Fashion, by Application USD Million (2013-2018)
  • Table 104. Italy AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 105. Italy AI in Fashion, by Category USD Million (2013-2018)
  • Table 106. Italy AI in Fashion, by End-User USD Million (2013-2018)
  • Table 107. Italy AI in Fashion, by Component USD Million (2013-2018)
  • Table 108. United Kingdom AI in Fashion, by Application USD Million (2013-2018)
  • Table 109. United Kingdom AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 110. United Kingdom AI in Fashion, by Category USD Million (2013-2018)
  • Table 111. United Kingdom AI in Fashion, by End-User USD Million (2013-2018)
  • Table 112. United Kingdom AI in Fashion, by Component USD Million (2013-2018)
  • Table 113. Netherlands AI in Fashion, by Application USD Million (2013-2018)
  • Table 114. Netherlands AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 115. Netherlands AI in Fashion, by Category USD Million (2013-2018)
  • Table 116. Netherlands AI in Fashion, by End-User USD Million (2013-2018)
  • Table 117. Netherlands AI in Fashion, by Component USD Million (2013-2018)
  • Table 118. Rest of Europe AI in Fashion, by Application USD Million (2013-2018)
  • Table 119. Rest of Europe AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 120. Rest of Europe AI in Fashion, by Category USD Million (2013-2018)
  • Table 121. Rest of Europe AI in Fashion, by End-User USD Million (2013-2018)
  • Table 122. Rest of Europe AI in Fashion, by Component USD Million (2013-2018)
  • Table 123. MEA AI in Fashion, by Country USD Million (2013-2018)
  • Table 124. MEA AI in Fashion, by Application USD Million (2013-2018)
  • Table 125. MEA AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 126. MEA AI in Fashion, by Category USD Million (2013-2018)
  • Table 127. MEA AI in Fashion, by End-User USD Million (2013-2018)
  • Table 128. MEA AI in Fashion, by Component USD Million (2013-2018)
  • Table 129. Middle East AI in Fashion, by Application USD Million (2013-2018)
  • Table 130. Middle East AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 131. Middle East AI in Fashion, by Category USD Million (2013-2018)
  • Table 132. Middle East AI in Fashion, by End-User USD Million (2013-2018)
  • Table 133. Middle East AI in Fashion, by Component USD Million (2013-2018)
  • Table 134. Africa AI in Fashion, by Application USD Million (2013-2018)
  • Table 135. Africa AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 136. Africa AI in Fashion, by Category USD Million (2013-2018)
  • Table 137. Africa AI in Fashion, by End-User USD Million (2013-2018)
  • Table 138. Africa AI in Fashion, by Component USD Million (2013-2018)
  • Table 139. North America AI in Fashion, by Country USD Million (2013-2018)
  • Table 140. North America AI in Fashion, by Application USD Million (2013-2018)
  • Table 141. North America AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 142. North America AI in Fashion, by Category USD Million (2013-2018)
  • Table 143. North America AI in Fashion, by End-User USD Million (2013-2018)
  • Table 144. North America AI in Fashion, by Component USD Million (2013-2018)
  • Table 145. United States AI in Fashion, by Application USD Million (2013-2018)
  • Table 146. United States AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 147. United States AI in Fashion, by Category USD Million (2013-2018)
  • Table 148. United States AI in Fashion, by End-User USD Million (2013-2018)
  • Table 149. United States AI in Fashion, by Component USD Million (2013-2018)
  • Table 150. Canada AI in Fashion, by Application USD Million (2013-2018)
  • Table 151. Canada AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 152. Canada AI in Fashion, by Category USD Million (2013-2018)
  • Table 153. Canada AI in Fashion, by End-User USD Million (2013-2018)
  • Table 154. Canada AI in Fashion, by Component USD Million (2013-2018)
  • Table 155. Mexico AI in Fashion, by Application USD Million (2013-2018)
  • Table 156. Mexico AI in Fashion, by Deployment Mode USD Million (2013-2018)
  • Table 157. Mexico AI in Fashion, by Category USD Million (2013-2018)
  • Table 158. Mexico AI in Fashion, by End-User USD Million (2013-2018)
  • Table 159. Mexico AI in Fashion, by Component USD Million (2013-2018)
  • Table 160. Company Basic Information, Sales Area and Its Competitors
  • Table 161. Company Basic Information, Sales Area and Its Competitors
  • Table 162. Company Basic Information, Sales Area and Its Competitors
  • Table 163. Company Basic Information, Sales Area and Its Competitors
  • Table 164. Company Basic Information, Sales Area and Its Competitors
  • Table 165. Company Basic Information, Sales Area and Its Competitors
  • Table 166. Company Basic Information, Sales Area and Its Competitors
  • Table 167. Company Basic Information, Sales Area and Its Competitors
  • Table 168. Company Basic Information, Sales Area and Its Competitors
  • Table 169. Company Basic Information, Sales Area and Its Competitors
  • Table 170. Company Basic Information, Sales Area and Its Competitors
  • Table 171. Company Basic Information, Sales Area and Its Competitors
  • Table 172. Company Basic Information, Sales Area and Its Competitors
  • Table 173. Company Basic Information, Sales Area and Its Competitors
  • Table 174. Company Basic Information, Sales Area and Its Competitors
  • Table 175. Company Basic Information, Sales Area and Its Competitors
  • Table 176. AI in Fashion: by Application(USD Million)
  • Table 177. AI in Fashion Product Recommendation , by Region USD Million (2019-2024)
  • Table 178. AI in Fashion Product Search and Discovery , by Region USD Million (2019-2024)
  • Table 179. AI in Fashion Supply Chain Management and Demand Forecasting , by Region USD Million (2019-2024)
  • Table 180. AI in Fashion Creative Designing and Trend Forecasting , by Region USD Million (2019-2024)
  • Table 181. AI in Fashion Customer Relationship Management , by Region USD Million (2019-2024)
  • Table 182. AI in Fashion Virtual Assistants , by Region USD Million (2019-2024)
  • Table 183. AI in Fashion Others [Fraud Detection, Fabric Waste Reduction, and Price Optimization] , by Region USD Million (2019-2024)
  • Table 184. AI in Fashion: by Deployment Mode(USD Million)
  • Table 185. AI in Fashion Cloud , by Region USD Million (2019-2024)
  • Table 186. AI in Fashion On-Premises , by Region USD Million (2019-2024)
  • Table 187. AI in Fashion: by Category(USD Million)
  • Table 188. AI in Fashion Apparel , by Region USD Million (2019-2024)
  • Table 189. AI in Fashion Accessories , by Region USD Million (2019-2024)
  • Table 190. AI in Fashion Footwear , by Region USD Million (2019-2024)
  • Table 191. AI in Fashion Beauty & Cosmetics , by Region USD Million (2019-2024)
  • Table 192. AI in Fashion Jewelry & Watches , by Region USD Million (2019-2024)
  • Table 193. AI in Fashion Others [Eyewear, Home Decor] , by Region USD Million (2019-2024)
  • Table 194. AI in Fashion: by End-User(USD Million)
  • Table 195. AI in Fashion Fashion Designers , by Region USD Million (2019-2024)
  • Table 196. AI in Fashion Fashion Stores , by Region USD Million (2019-2024)
  • Table 197. AI in Fashion: by Component(USD Million)
  • Table 198. AI in Fashion Solution [Software Tools, Platforms] , by Region USD Million (2019-2024)
  • Table 199. AI in Fashion Services [Training and Consulting, System Integration and Testing, Support and Maintenance] , by Region USD Million (2019-2024)
  • Table 200. South America AI in Fashion, by Country USD Million (2019-2024)
  • Table 201. South America AI in Fashion, by Application USD Million (2019-2024)
  • Table 202. South America AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 203. South America AI in Fashion, by Category USD Million (2019-2024)
  • Table 204. South America AI in Fashion, by End-User USD Million (2019-2024)
  • Table 205. South America AI in Fashion, by Component USD Million (2019-2024)
  • Table 206. Brazil AI in Fashion, by Application USD Million (2019-2024)
  • Table 207. Brazil AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 208. Brazil AI in Fashion, by Category USD Million (2019-2024)
  • Table 209. Brazil AI in Fashion, by End-User USD Million (2019-2024)
  • Table 210. Brazil AI in Fashion, by Component USD Million (2019-2024)
  • Table 211. Argentina AI in Fashion, by Application USD Million (2019-2024)
  • Table 212. Argentina AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 213. Argentina AI in Fashion, by Category USD Million (2019-2024)
  • Table 214. Argentina AI in Fashion, by End-User USD Million (2019-2024)
  • Table 215. Argentina AI in Fashion, by Component USD Million (2019-2024)
  • Table 216. Rest of South America AI in Fashion, by Application USD Million (2019-2024)
  • Table 217. Rest of South America AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 218. Rest of South America AI in Fashion, by Category USD Million (2019-2024)
  • Table 219. Rest of South America AI in Fashion, by End-User USD Million (2019-2024)
  • Table 220. Rest of South America AI in Fashion, by Component USD Million (2019-2024)
  • Table 221. Asia Pacific AI in Fashion, by Country USD Million (2019-2024)
  • Table 222. Asia Pacific AI in Fashion, by Application USD Million (2019-2024)
  • Table 223. Asia Pacific AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 224. Asia Pacific AI in Fashion, by Category USD Million (2019-2024)
  • Table 225. Asia Pacific AI in Fashion, by End-User USD Million (2019-2024)
  • Table 226. Asia Pacific AI in Fashion, by Component USD Million (2019-2024)
  • Table 227. China AI in Fashion, by Application USD Million (2019-2024)
  • Table 228. China AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 229. China AI in Fashion, by Category USD Million (2019-2024)
  • Table 230. China AI in Fashion, by End-User USD Million (2019-2024)
  • Table 231. China AI in Fashion, by Component USD Million (2019-2024)
  • Table 232. Japan AI in Fashion, by Application USD Million (2019-2024)
  • Table 233. Japan AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 234. Japan AI in Fashion, by Category USD Million (2019-2024)
  • Table 235. Japan AI in Fashion, by End-User USD Million (2019-2024)
  • Table 236. Japan AI in Fashion, by Component USD Million (2019-2024)
  • Table 237. India AI in Fashion, by Application USD Million (2019-2024)
  • Table 238. India AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 239. India AI in Fashion, by Category USD Million (2019-2024)
  • Table 240. India AI in Fashion, by End-User USD Million (2019-2024)
  • Table 241. India AI in Fashion, by Component USD Million (2019-2024)
  • Table 242. South Korea AI in Fashion, by Application USD Million (2019-2024)
  • Table 243. South Korea AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 244. South Korea AI in Fashion, by Category USD Million (2019-2024)
  • Table 245. South Korea AI in Fashion, by End-User USD Million (2019-2024)
  • Table 246. South Korea AI in Fashion, by Component USD Million (2019-2024)
  • Table 247. Taiwan AI in Fashion, by Application USD Million (2019-2024)
  • Table 248. Taiwan AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 249. Taiwan AI in Fashion, by Category USD Million (2019-2024)
  • Table 250. Taiwan AI in Fashion, by End-User USD Million (2019-2024)
  • Table 251. Taiwan AI in Fashion, by Component USD Million (2019-2024)
  • Table 252. Australia AI in Fashion, by Application USD Million (2019-2024)
  • Table 253. Australia AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 254. Australia AI in Fashion, by Category USD Million (2019-2024)
  • Table 255. Australia AI in Fashion, by End-User USD Million (2019-2024)
  • Table 256. Australia AI in Fashion, by Component USD Million (2019-2024)
  • Table 257. Rest of Asia-Pacific AI in Fashion, by Application USD Million (2019-2024)
  • Table 258. Rest of Asia-Pacific AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 259. Rest of Asia-Pacific AI in Fashion, by Category USD Million (2019-2024)
  • Table 260. Rest of Asia-Pacific AI in Fashion, by End-User USD Million (2019-2024)
  • Table 261. Rest of Asia-Pacific AI in Fashion, by Component USD Million (2019-2024)
  • Table 262. Europe AI in Fashion, by Country USD Million (2019-2024)
  • Table 263. Europe AI in Fashion, by Application USD Million (2019-2024)
  • Table 264. Europe AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 265. Europe AI in Fashion, by Category USD Million (2019-2024)
  • Table 266. Europe AI in Fashion, by End-User USD Million (2019-2024)
  • Table 267. Europe AI in Fashion, by Component USD Million (2019-2024)
  • Table 268. Germany AI in Fashion, by Application USD Million (2019-2024)
  • Table 269. Germany AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 270. Germany AI in Fashion, by Category USD Million (2019-2024)
  • Table 271. Germany AI in Fashion, by End-User USD Million (2019-2024)
  • Table 272. Germany AI in Fashion, by Component USD Million (2019-2024)
  • Table 273. France AI in Fashion, by Application USD Million (2019-2024)
  • Table 274. France AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 275. France AI in Fashion, by Category USD Million (2019-2024)
  • Table 276. France AI in Fashion, by End-User USD Million (2019-2024)
  • Table 277. France AI in Fashion, by Component USD Million (2019-2024)
  • Table 278. Italy AI in Fashion, by Application USD Million (2019-2024)
  • Table 279. Italy AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 280. Italy AI in Fashion, by Category USD Million (2019-2024)
  • Table 281. Italy AI in Fashion, by End-User USD Million (2019-2024)
  • Table 282. Italy AI in Fashion, by Component USD Million (2019-2024)
  • Table 283. United Kingdom AI in Fashion, by Application USD Million (2019-2024)
  • Table 284. United Kingdom AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 285. United Kingdom AI in Fashion, by Category USD Million (2019-2024)
  • Table 286. United Kingdom AI in Fashion, by End-User USD Million (2019-2024)
  • Table 287. United Kingdom AI in Fashion, by Component USD Million (2019-2024)
  • Table 288. Netherlands AI in Fashion, by Application USD Million (2019-2024)
  • Table 289. Netherlands AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 290. Netherlands AI in Fashion, by Category USD Million (2019-2024)
  • Table 291. Netherlands AI in Fashion, by End-User USD Million (2019-2024)
  • Table 292. Netherlands AI in Fashion, by Component USD Million (2019-2024)
  • Table 293. Rest of Europe AI in Fashion, by Application USD Million (2019-2024)
  • Table 294. Rest of Europe AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 295. Rest of Europe AI in Fashion, by Category USD Million (2019-2024)
  • Table 296. Rest of Europe AI in Fashion, by End-User USD Million (2019-2024)
  • Table 297. Rest of Europe AI in Fashion, by Component USD Million (2019-2024)
  • Table 298. MEA AI in Fashion, by Country USD Million (2019-2024)
  • Table 299. MEA AI in Fashion, by Application USD Million (2019-2024)
  • Table 300. MEA AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 301. MEA AI in Fashion, by Category USD Million (2019-2024)
  • Table 302. MEA AI in Fashion, by End-User USD Million (2019-2024)
  • Table 303. MEA AI in Fashion, by Component USD Million (2019-2024)
  • Table 304. Middle East AI in Fashion, by Application USD Million (2019-2024)
  • Table 305. Middle East AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 306. Middle East AI in Fashion, by Category USD Million (2019-2024)
  • Table 307. Middle East AI in Fashion, by End-User USD Million (2019-2024)
  • Table 308. Middle East AI in Fashion, by Component USD Million (2019-2024)
  • Table 309. Africa AI in Fashion, by Application USD Million (2019-2024)
  • Table 310. Africa AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 311. Africa AI in Fashion, by Category USD Million (2019-2024)
  • Table 312. Africa AI in Fashion, by End-User USD Million (2019-2024)
  • Table 313. Africa AI in Fashion, by Component USD Million (2019-2024)
  • Table 314. North America AI in Fashion, by Country USD Million (2019-2024)
  • Table 315. North America AI in Fashion, by Application USD Million (2019-2024)
  • Table 316. North America AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 317. North America AI in Fashion, by Category USD Million (2019-2024)
  • Table 318. North America AI in Fashion, by End-User USD Million (2019-2024)
  • Table 319. North America AI in Fashion, by Component USD Million (2019-2024)
  • Table 320. United States AI in Fashion, by Application USD Million (2019-2024)
  • Table 321. United States AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 322. United States AI in Fashion, by Category USD Million (2019-2024)
  • Table 323. United States AI in Fashion, by End-User USD Million (2019-2024)
  • Table 324. United States AI in Fashion, by Component USD Million (2019-2024)
  • Table 325. Canada AI in Fashion, by Application USD Million (2019-2024)
  • Table 326. Canada AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 327. Canada AI in Fashion, by Category USD Million (2019-2024)
  • Table 328. Canada AI in Fashion, by End-User USD Million (2019-2024)
  • Table 329. Canada AI in Fashion, by Component USD Million (2019-2024)
  • Table 330. Mexico AI in Fashion, by Application USD Million (2019-2024)
  • Table 331. Mexico AI in Fashion, by Deployment Mode USD Million (2019-2024)
  • Table 332. Mexico AI in Fashion, by Category USD Million (2019-2024)
  • Table 333. Mexico AI in Fashion, by End-User USD Million (2019-2024)
  • Table 334. Mexico AI in Fashion, by Component USD Million (2019-2024)
  • Table 335. Research Programs/Design for This Report
  • Table 336. Key Data Information from Secondary Sources
  • Table 337. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global AI in Fashion: by Application USD Million (2013-2018)
  • Figure 5. Global AI in Fashion: by Deployment Mode USD Million (2013-2018)
  • Figure 6. Global AI in Fashion: by Category USD Million (2013-2018)
  • Figure 7. Global AI in Fashion: by End-User USD Million (2013-2018)
  • Figure 8. Global AI in Fashion: by Component USD Million (2013-2018)
  • Figure 9. South America AI in Fashion Share (%), by Country
  • Figure 10. Asia Pacific AI in Fashion Share (%), by Country
  • Figure 11. Europe AI in Fashion Share (%), by Country
  • Figure 12. MEA AI in Fashion Share (%), by Country
  • Figure 13. North America AI in Fashion Share (%), by Country
  • Figure 14. Global AI in Fashion share by Players 2018 (%)
  • Figure 15. Global AI in Fashion share by Players (Top 3) 2018(%)
  • Figure 16. Global AI in Fashion share by Players (Top 5) 2018(%)
  • Figure 17. BCG Matrix for key Companies
  • Figure 18. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 19. Microsoft (United States) Revenue: by Geography 2018
  • Figure 20. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 21. IBM (United States) Revenue: by Geography 2018
  • Figure 22. Google (United States) Revenue, Net Income and Gross profit
  • Figure 23. Google (United States) Revenue: by Geography 2018
  • Figure 24. AWS (United States) Revenue, Net Income and Gross profit
  • Figure 25. AWS (United States) Revenue: by Geography 2018
  • Figure 26. SAP (Germany) Revenue, Net Income and Gross profit
  • Figure 27. SAP (Germany) Revenue: by Geography 2018
  • Figure 28. Facebook (United States) Revenue, Net Income and Gross profit
  • Figure 29. Facebook (United States) Revenue: by Geography 2018
  • Figure 30. Adobe (United States) Revenue, Net Income and Gross profit
  • Figure 31. Adobe (United States) Revenue: by Geography 2018
  • Figure 32. Oracle (United States) Revenue, Net Income and Gross profit
  • Figure 33. Oracle (United States) Revenue: by Geography 2018
  • Figure 34. Catchoom (Spain) Revenue, Net Income and Gross profit
  • Figure 35. Catchoom (Spain) Revenue: by Geography 2018
  • Figure 36. Huawei (China) Revenue, Net Income and Gross profit
  • Figure 37. Huawei (China) Revenue: by Geography 2018
  • Figure 38. Vue.ai (United States) Revenue, Net Income and Gross profit
  • Figure 39. Vue.ai (United States) Revenue: by Geography 2018
  • Figure 40. Heuritech (France) Revenue, Net Income and Gross profit
  • Figure 41. Heuritech (France) Revenue: by Geography 2018
  • Figure 42. Wide Eyes (Spain) Revenue, Net Income and Gross profit
  • Figure 43. Wide Eyes (Spain) Revenue: by Geography 2018
  • Figure 44. FINDMINE (United States) Revenue, Net Income and Gross profit
  • Figure 45. FINDMINE (United States) Revenue: by Geography 2018
  • Figure 46. Intelistyle (England) Revenue, Net Income and Gross profit
  • Figure 47. Intelistyle (England) Revenue: by Geography 2018
  • Figure 48. Lily AI (United States) Revenue, Net Income and Gross profit
  • Figure 49. Lily AI (United States) Revenue: by Geography 2018
  • Figure 50. Global AI in Fashion: by Application USD Million (2019-2024)
  • Figure 51. Global AI in Fashion: by Deployment Mode USD Million (2019-2024)
  • Figure 52. Global AI in Fashion: by Category USD Million (2019-2024)
  • Figure 53. Global AI in Fashion: by End-User USD Million (2019-2024)
  • Figure 54. Global AI in Fashion: by Component USD Million (2019-2024)
  • Figure 55. South America AI in Fashion Share (%), by Country
  • Figure 56. Asia Pacific AI in Fashion Share (%), by Country
  • Figure 57. Europe AI in Fashion Share (%), by Country
  • Figure 58. MEA AI in Fashion Share (%), by Country
  • Figure 59. North America AI in Fashion Share (%), by Country
Some of the key companies/manufacturers profiled in the report
  • 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)
  • Lily AI (United States)
Additional players considered in the study are as follows:
Pttrns.ai (Netherlands) , Syte (Israel) , Mode.ai (United States) , Stitch Fix (United States)
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