Global AI in Fashion Competitive Landscape Professional Research Report 2025
Description
Research Summary
AI in fashion refers to the application of artificial intelligence technologies in various aspects of the fashion industry, including design, manufacturing, marketing, and retail. AI algorithms and machine learning techniques are being used to analyze vast amounts of data, including consumer preferences, social media trends, and sales data, to inform design decisions, predict fashion trends, and optimize inventory management. In the design process, AI tools can assist designers in generating new concepts, creating virtual prototypes, and even autonomously designing garments. In manufacturing, AI-powered systems are improving efficiency and quality control by optimizing production processes and detecting defects. Additionally, AI is revolutionizing the retail experience through personalized recommendations, virtual try-on solutions, and chatbots for customer service. Overall, AI is transforming the fashion industry, making it more data-driven, efficient, and responsive to consumer needs.
According to DIResearch's in-depth investigation and research, the global AI in Fashion market size was valued at XX Million USD in 2024 and is projected to reach XX Million USD by 2032, with a CAGR of XX% (2025-2032). Notably, the China market has changed rapidly in the past few years. By 2024, China's market size is expected to be XX Million USD, representing approximately XX% of the global market share. By 2032, it is anticipated to grow further to XX Million USD, contributing XX% to the worldwide market share.
The major global manufacturers of AI in Fashion include Microsoft (US), IBM (US), Google (US), AWS (US), SAP (Germany), Facebook (US), Adobe (US), Oracle (US), Vue.ai (US), Lily AI (US), Syte (Israel), mode.ai (US), Stitch Fix (US), Heuritech (France), Wide Eyes (Spain), FINDMINE (US), Catchoom (Spain), Huawei (China), Intelistyle (England), Pttrns.ai (Netherlands) etc. The global players competition landscape in this report is divided into three tiers. The first tier comprises global leading enterprises that command a substantial market share, hold a dominant industry position, possess strong competitiveness and influence, and generate significant revenue. The second tier includes companies with a notable market presence and reputation; these firms actively follow industry leaders in product, service, or technological innovation and maintain a moderate revenue scale. The third tier consists of smaller companies with limited market share and lower brand recognition, primarily focused on local markets and generating comparatively lower revenue.
This report studies the market size, price trends and future development prospects of AI in Fashion. Focus on analysing the market share, product portfolio, prices, sales, revenue and gross profit margin of global major manufacturers, as well as the market status and trends of different product types and applications in the global AI in Fashion market. The report data covers historical data from 2020 to 2024, based year in 2025 and forecast data from 2026 to 2032.
The regions and countries in the report include North America, Europe, China, APAC (excl. China), Latin America and Middle East and Africa, covering the AI in Fashion market conditions and future development trends of key regions and countries, combined with industry-related policies and the latest technological developments, analyze the development characteristics of AI in Fashion industries in various regions and countries, help companies understand the development characteristics of each region, help companies formulate business strategies, and achieve the ultimate goal of the company's global development strategy.
The data sources of this report mainly include the National Bureau of Statistics, customs databases, industry associations, corporate financial reports, third-party databases, etc. Among them, macroeconomic data mainly comes from the National Bureau of Statistics, International Economic Research Organization; industry statistical data mainly come from industry associations; company data mainly comes from interviews, public information collection, third-party reliable databases, and price data mainly comes from various markets monitoring database.
Global Key Manufacturers of AI in Fashion Include:
Microsoft (US)
IBM (US)
Google (US)
AWS (US)
SAP (Germany)
Facebook (US)
Adobe (US)
Oracle (US)
Vue.ai (US)
Lily AI (US)
Syte (Israel)
mode.ai (US)
Stitch Fix (US)
Heuritech (France)
Wide Eyes (Spain)
FINDMINE (US)
Catchoom (Spain)
Huawei (China)
Intelistyle (England)
Pttrns.ai (Netherlands)
AI in Fashion Product Segment Include:
Apparel
Accessories
Footwear
Beauty and Cosmetics
Jewelry and Watches
Others
AI in Fashion Product Application Include:
Fashion Designers
Fashion Stores (Online and Offline Brand Stores)
Chapter Scope
Chapter 1: Product Research Range, Product Types and Applications, Market Overview, Market Situation and Trends
Chapter 2: Global AI in Fashion Industry PESTEL Analysis
Chapter 3: Global AI in Fashion Industry Porter’s Five Forces Analysis
Chapter 4: Global AI in Fashion Major Regional Market Size and Forecast Analysis
Chapter 5: Global AI in Fashion Market Size and Forecast by Type and Application Analysis
Chapter 6: North America Passenger AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 7: Europe AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 8: China AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 9: APAC (Excl. China) AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 10: Latin America AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 11: Middle East and Africa AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 12: Global AI in Fashion Competitive Analysis of Key Manufacturers (Revenue, Market Share, Regional Distribution and Industry Concentration)
Chapter 13: Key Company Profiles (Product Portfolio, Revenue and Gross Margin)
Chapter 14: Industrial Chain Analysis, Include Raw Material Suppliers, Distributors and Customers
Chapter 15: Research Findings and Conclusion
Chapter 16: Methodology and Data Sources
AI in fashion refers to the application of artificial intelligence technologies in various aspects of the fashion industry, including design, manufacturing, marketing, and retail. AI algorithms and machine learning techniques are being used to analyze vast amounts of data, including consumer preferences, social media trends, and sales data, to inform design decisions, predict fashion trends, and optimize inventory management. In the design process, AI tools can assist designers in generating new concepts, creating virtual prototypes, and even autonomously designing garments. In manufacturing, AI-powered systems are improving efficiency and quality control by optimizing production processes and detecting defects. Additionally, AI is revolutionizing the retail experience through personalized recommendations, virtual try-on solutions, and chatbots for customer service. Overall, AI is transforming the fashion industry, making it more data-driven, efficient, and responsive to consumer needs.
According to DIResearch's in-depth investigation and research, the global AI in Fashion market size was valued at XX Million USD in 2024 and is projected to reach XX Million USD by 2032, with a CAGR of XX% (2025-2032). Notably, the China market has changed rapidly in the past few years. By 2024, China's market size is expected to be XX Million USD, representing approximately XX% of the global market share. By 2032, it is anticipated to grow further to XX Million USD, contributing XX% to the worldwide market share.
The major global manufacturers of AI in Fashion include Microsoft (US), IBM (US), Google (US), AWS (US), SAP (Germany), Facebook (US), Adobe (US), Oracle (US), Vue.ai (US), Lily AI (US), Syte (Israel), mode.ai (US), Stitch Fix (US), Heuritech (France), Wide Eyes (Spain), FINDMINE (US), Catchoom (Spain), Huawei (China), Intelistyle (England), Pttrns.ai (Netherlands) etc. The global players competition landscape in this report is divided into three tiers. The first tier comprises global leading enterprises that command a substantial market share, hold a dominant industry position, possess strong competitiveness and influence, and generate significant revenue. The second tier includes companies with a notable market presence and reputation; these firms actively follow industry leaders in product, service, or technological innovation and maintain a moderate revenue scale. The third tier consists of smaller companies with limited market share and lower brand recognition, primarily focused on local markets and generating comparatively lower revenue.
This report studies the market size, price trends and future development prospects of AI in Fashion. Focus on analysing the market share, product portfolio, prices, sales, revenue and gross profit margin of global major manufacturers, as well as the market status and trends of different product types and applications in the global AI in Fashion market. The report data covers historical data from 2020 to 2024, based year in 2025 and forecast data from 2026 to 2032.
The regions and countries in the report include North America, Europe, China, APAC (excl. China), Latin America and Middle East and Africa, covering the AI in Fashion market conditions and future development trends of key regions and countries, combined with industry-related policies and the latest technological developments, analyze the development characteristics of AI in Fashion industries in various regions and countries, help companies understand the development characteristics of each region, help companies formulate business strategies, and achieve the ultimate goal of the company's global development strategy.
The data sources of this report mainly include the National Bureau of Statistics, customs databases, industry associations, corporate financial reports, third-party databases, etc. Among them, macroeconomic data mainly comes from the National Bureau of Statistics, International Economic Research Organization; industry statistical data mainly come from industry associations; company data mainly comes from interviews, public information collection, third-party reliable databases, and price data mainly comes from various markets monitoring database.
Global Key Manufacturers of AI in Fashion Include:
Microsoft (US)
IBM (US)
Google (US)
AWS (US)
SAP (Germany)
Facebook (US)
Adobe (US)
Oracle (US)
Vue.ai (US)
Lily AI (US)
Syte (Israel)
mode.ai (US)
Stitch Fix (US)
Heuritech (France)
Wide Eyes (Spain)
FINDMINE (US)
Catchoom (Spain)
Huawei (China)
Intelistyle (England)
Pttrns.ai (Netherlands)
AI in Fashion Product Segment Include:
Apparel
Accessories
Footwear
Beauty and Cosmetics
Jewelry and Watches
Others
AI in Fashion Product Application Include:
Fashion Designers
Fashion Stores (Online and Offline Brand Stores)
Chapter Scope
Chapter 1: Product Research Range, Product Types and Applications, Market Overview, Market Situation and Trends
Chapter 2: Global AI in Fashion Industry PESTEL Analysis
Chapter 3: Global AI in Fashion Industry Porter’s Five Forces Analysis
Chapter 4: Global AI in Fashion Major Regional Market Size and Forecast Analysis
Chapter 5: Global AI in Fashion Market Size and Forecast by Type and Application Analysis
Chapter 6: North America Passenger AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 7: Europe AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 8: China AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 9: APAC (Excl. China) AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 10: Latin America AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 11: Middle East and Africa AI in Fashion Competitive Analysis (Market Size, Key Players and Market Share, Product Type and Application Segment Analysis, Countries Analysis)
Chapter 12: Global AI in Fashion Competitive Analysis of Key Manufacturers (Revenue, Market Share, Regional Distribution and Industry Concentration)
Chapter 13: Key Company Profiles (Product Portfolio, Revenue and Gross Margin)
Chapter 14: Industrial Chain Analysis, Include Raw Material Suppliers, Distributors and Customers
Chapter 15: Research Findings and Conclusion
Chapter 16: Methodology and Data Sources
Table of Contents
170 Pages
- 1 Gaming Software Market Overview
- 1.1 Product Definition and Statistical Scope
- 1.2 Gaming Software Product by Type
- 1.2.1 Mobile Gaming
- 1.2.2 Console Gaming
- 1.2.3 PC Gaming
- 1.3 Gaming Software Product by Application
- 1.3.1 Amateur Gamer
- 1.3.2 Professional Gamer
- 1.4 Global Gaming Software Market Size Analysis (2020-2032)
- 1.5 Gaming Software Market Development Status and Trends
- 1.5.1 Gaming Software Industry Development Status Analysis
- 1.5.2 Gaming Software Industry Development Trends Analysis
- 2 Gaming Software Market PESTEL Analysis
- 2.1 Political Factors Analysis
- 2.2 Economic Factors Analysis
- 2.3 Social Factors Analysis
- 2.4 Technological Factors Analysis
- 2.5 Environmental Factors Analysis
- 2.6 Legal Factors Analysis
- 3 Gaming Software Market Porter's Five Forces Analysis
- 3.1 Competitive Rivalry
- 3.2 Threat of New Entrants
- 3.3 Bargaining Power of Suppliers
- 3.4 Bargaining Power of Buyers
- 3.5 Threat of Substitutes
- 4 Global Gaming Software Market Analysis by Regions
- 4.1 Global Gaming Software Overall Market: 2024 VS 2025 VS 2032
- 4.2 Global Gaming Software Revenue and Forecast Analysis (2020-2032)
- 4.2.1 Global Gaming Software Revenue and Market Share by Region (2020-2025)
- 4.2.2 Global Gaming Software Revenue Forecast by Region (2026-2032)
- 5 Global Gaming Software Market Size by Type and Application
- 5.1 Global Gaming Software Market Size by Type (2020-2032)
- 5.2 Global Gaming Software Market Size by Application (2020-2032)
- 6 North America
- 6.1 North America Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 6.2 North America Key Manufacturers Analysis
- 6.3 North America Gaming Software Market Size by Type
- 6.4 North America Gaming Software Market Size by Application
- 6.5 North America Gaming Software Market Size by Country
- 6.5.1 US
- 6.5.2 Canada
- 7 Europe
- 7.1 Europe Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 7.2 Europe Key Manufacturers Analysis
- 7.3 Europe Gaming Software Market Size by Type
- 7.4 Europe Gaming Software Market Size by Application
- 7.5 Europe Gaming Software Market Size by Country
- 7.5.1 Germany
- 7.5.2 France
- 7.5.3 United Kingdom
- 7.5.4 Italy
- 7.5.5 Spain
- 7.5.6 Benelux
- 8 China
- 8.1 China Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 8.2 China Key Manufacturers Analysis
- 8.3 China Gaming Software Market Size by Type
- 8.4 China Gaming Software Market Size by Application
- 9 APAC (excl. China)
- 9.1 APAC (excl. China) Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 9.2 APAC (excl. China) Key Manufacturers Analysis
- 9.3 APAC (excl. China) Gaming Software Market Size by Type
- 9.4 APAC (excl. China) Gaming Software Market Size by Application
- 9.5 APAC (excl. China) Gaming Software Market Size by Country
- 9.5.1 Japan
- 9.5.2 South Korea
- 9.5.3 India
- 9.5.4 Australia
- 9.5.5 Southeast Asia
- 10 Latin America
- 10.1 Latin America Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 10.2 Latin America Key Manufacturers Analysis
- 10.3 Latin America Gaming Software Market Size by Type
- 10.4 Latin America Gaming Software Market Size by Application
- 10.5 Latin America Gaming Software Market Size by Country
- 10.5.1 Mexico
- 10.5.2 Brazil
- 11 Middle East & Africa
- 11.1 Middle East & Africa Gaming Software Market Size and Growth Rate Analysis (2020-2032)
- 11.2 Middle East & Africa Key Manufacturers Analysis
- 11.3 Middle East & Africa Gaming Software Market Size by Type
- 11.4 Middle East & Africa Gaming Software Market Size by Application
- 11.5 Middle East & Africa Gaming Software Market Size by Country
- 11.5.1 Saudi Arabia
- 11.5.2 South Africa
- 12 Competition by Manufacturers
- 12.1 Global Gaming Software Market Revenue by Key Manufacturers (2021-2025)
- 12.2 Gaming Software Competitive Landscape Analysis and Market Dynamic
- 12.2.1 Gaming Software Competitive Landscape Analysis
- 12.2.2 Global Key Manufacturers Headquarter Location and Key Area Sales
- 12.2.3 Market Dynamic
- 13 Key Companies Analysis
- 13.1 Activision Blizzard
- 13.1.1 Activision Blizzard Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.1.2 Activision Blizzard Gaming Software Product Portfolio
- 13.1.3 Activision Blizzard Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.2 Electronic Arts
- 13.2.1 Electronic Arts Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.2.2 Electronic Arts Gaming Software Product Portfolio
- 13.2.3 Electronic Arts Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.3 Microsoft
- 13.3.1 Microsoft Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.3.2 Microsoft Gaming Software Product Portfolio
- 13.3.3 Microsoft Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.4 NetEase
- 13.4.1 NetEase Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.4.2 NetEase Gaming Software Product Portfolio
- 13.4.3 NetEase Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.5 Nintendo
- 13.5.1 Nintendo Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.5.2 Nintendo Gaming Software Product Portfolio
- 13.5.3 Nintendo Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.6 Sony
- 13.6.1 Sony Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.6.2 Sony Gaming Software Product Portfolio
- 13.6.3 Sony Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.7 Tencent
- 13.7.1 Tencent Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.7.2 Tencent Gaming Software Product Portfolio
- 13.7.3 Tencent Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.8 ChangYou
- 13.8.1 ChangYou Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.8.2 ChangYou Gaming Software Product Portfolio
- 13.8.3 ChangYou Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.9 DeNA
- 13.9.1 DeNA Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.9.2 DeNA Gaming Software Product Portfolio
- 13.9.3 DeNA Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.10 GungHo
- 13.10.1 GungHo Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.10.2 GungHo Gaming Software Product Portfolio
- 13.10.3 GungHo Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.11 Apple
- 13.11.1 Apple Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.11.2 Apple Gaming Software Product Portfolio
- 13.11.3 Apple Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.12 Google
- 13.12.1 Google Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.12.2 Google Gaming Software Product Portfolio
- 13.12.3 Google Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.13 Nexon
- 13.13.1 Nexon Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.13.2 Nexon Gaming Software Product Portfolio
- 13.13.3 Nexon Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.14 Sega
- 13.14.1 Sega Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.14.2 Sega Gaming Software Product Portfolio
- 13.14.3 Sega Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.15 Warner Bros
- 13.15.1 Warner Bros Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.15.2 Warner Bros Gaming Software Product Portfolio
- 13.15.3 Warner Bros Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.16 Namco Bandai
- 13.16.1 Namco Bandai Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.16.2 Namco Bandai Gaming Software Product Portfolio
- 13.16.3 Namco Bandai Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.17 Ubisoft
- 13.17.1 Ubisoft Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.17.2 Ubisoft Gaming Software Product Portfolio
- 13.17.3 Ubisoft Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.18 Square Enix
- 13.18.1 Square Enix Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.18.2 Square Enix Gaming Software Product Portfolio
- 13.18.3 Square Enix Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 13.19 Take-Two Interactive
- 13.19.1 Take-Two Interactive Basic Company Profile (Employees, Areas Service, Competitors and Contact Information)
- 13.19.2 Take-Two Interactive Gaming Software Product Portfolio
- 13.19.3 Take-Two Interactive Gaming Software Market Data Analysis (Revenue, Gross Margin and Market Share) (2021-2025)
- 14 Industry Chain Analysis
- 14.1 Gaming Software Industry Chain Analysis
- 14.2 Gaming Software Industry Raw Material and Suppliers Analysis
- 14.2.1 Gaming Software Key Raw Material Supply Analysis
- 14.2.2 Raw Material Suppliers and Contact Information
- 14.3 Gaming Software Typical Downstream Customers
- 14.4 Gaming Software Sales Channel Analysis
- 15 Research Findings and Conclusion
- 16 Methodology and Data Source
- 16.1 Methodology/Research Approach
- 16.2 Research Scope
- 16.3 Benchmarks and Assumptions
- 16.4 Date Source
- 16.4.1 Primary Sources
- 16.4.2 Secondary Sources
- 16.5 Data Cross Validation
- 16.6 Disclaimer
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