AI in Fashion Market Analysis by Components, Applications, Deployment Mode, Category & End User (2020 – 2025)
AI in Fashion Market Analysis by Components, Applications, Deployment Mode, Category & End User (2020 – 2025)
The AI in Fashion Market report highlights technological advancements, investment opportunities, and regulatory frameworks shaping the industry landscape through 2030.
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The global AI in fashion market generated revenue of US$ XX.X million in 2020 and is expected to reach US$ XX.X million by 2025 with a CAGR of XX.X% in the forecast period. The study offers a detailed analysis of the global market for AI in fashion. Considering 2019 as the base year, the report provides market information for the 2020 to 2025 forecast period. The study includes information on the current size and projected growth of the overall AI in fashion market and its associated business segments. It outlines the dynamics, the business environment, and emerging developments in the AI in fashion market.
The study contains a chapter that explains the impact of COVID 19 on the global AI in fashion market. The study further discusses the key factors, the business environment, and emerging developments in the AI in fashion market. The AI in fashion market report will help several vendors to make the right investment and development decisions. The research focuses on the global AI in fashion scenario and its proliferation across various market verticals. The descriptions in this report cover factors that currently influence and impede market growth and also accelerate the future dimensions of demand for the AI in fashion market.
The chapters included in the report describe leading players in the AI in fashion market. The study provides landscape analysis, which offers detailed profiles of major players in the AI in fashion market worldwide. The report covers a fine-grained taxonomy of market segmentation in terms of components, applications, deployment mode, category & end user.
By Components
• Solutions
• Services
o Training and Consulting
o System Integration and Testing
o Support and Maintenance
By Applications
• Product Recommendation
• Product Search and Discovery
• Supply Chain Management and Demand Forecasting
• Creative Designing and Trend Forecasting
• Customer Relationship Management
• Virtual Assistants
• Others
By Deployment Mode
• Cloud
• On-premises
By Category
• Apparel
• Accessories
• Footwear
• Beauty and Cosmetics
• Jewelry and Watches
• Others
By End-User
• Fashion Designers
• Fashion Stores
By Region
• North America (U.S. Canada)
• Europe (Germany, U.K., France, Italy, Spain, Rest of Europe)
• Asia Pacific (China, Japan, India, Rest of Asia Pacific)
• Middle East & Africa (GCC, South Africa, Rest of Middle East & Africa)
• Latin America (Brazil, Mexico, Rest of Latin America)
Market Players
Some of the major players in the AI in fashion market are as follows:
• Amazon Web Services, Inc.
• Catchoom Technologies, S.L.
• FindMine, Inc.
• Heuritech
• Huawei Technologies Co., Ltd.
• Intelistyle Ltd.
• International Business Machines Corporation
• Microsoft Corporation
• Syte Visual Conception ltd.
• Wide Eyes Technologies
1. Introduction
2. Market Overview
2.1. Global AI in Fashion Market Introduction
2.2. Macro- Economic Factor
2.3. Market Determinants
2.3.1. Market Driver
2.3.2. Market Restraints
2.3.3. Market Opportunities
2.3.4. Market Challenges
2.4. Technology/Product Roadmap
2.5. Market Growth Opportunity Analysis
3. Market Segmentation
3.1. Global AI in Fashion Market Analysis (US$ Mn), By Components, 2019 - 2025
3.1.1. Solutions
3.1.2. Services
3.1.2.1. Training and Consulting
3.1.2.2. System Integration and Testing
3.1.2.3. Support and Maintenance
3.2. Global AI in Fashion Market Analysis (US$ Mn), By Deployment Mode, 2019 – 2025
3.2.1. Cloud
3.2.2. On-premises
3.3. Global AI in Fashion Market Analysis (US$ Mn), By Category, 2019 – 2025
3.3.1. Apparel
3.3.2. Accessories
3.3.3. Footwear
3.3.4. Beauty and Cosmetics
3.3.5. Jewelry and Watches
3.3.6. Others (eyewear, home decor)
3.4. Global AI in Fashion Market Analysis (US$ Mn), By End-User, 2019 – 2025
3.4.1. Fashion Designers
3.4.2. Fashion Stores
4. Regional Analysis
4.1. North America AI in Fashion Market Analysis (US$ Mn), 2019 - 2025
4.1.1. By Country
4.1.1.1. U.S.
4.1.1.2. Canada
4.1.2. By Components
4.1.2.1. Solutions
4.1.2.2. Services
4.1.2.2.1. Training and Consulting
4.1.2.2.2. System Integration and Testing
4.1.2.2.3. Support and Maintenance
4.1.3. By Applications
4.1.3.1. Product Recommendation
4.1.3.2. Product Search and Discovery
4.1.3.3. Supply Chain Management and Demand Forecasting
4.1.3.4. Creative Designing and Trend Forecasting
4.1.3.5. Customer Relationship Management
4.1.3.6. Virtual Assistants
4.1.3.7. Others
4.1.4. By Deployment Mode
4.1.4.1. Cloud
4.1.4.2. On-premises
4.1.5. By Category
4.1.5.1. Apparel
4.1.5.2. Accessories
4.1.5.3. Footwear
4.1.5.4. Beauty and Cosmetics
4.1.5.5. Jewelry and Watches
4.1.5.6. Others
4.1.6. By End-User
4.1.6.1. Fashion Designers
4.1.6.2. Fashion Stores
4.2. Europe AI in Fashion Market Analysis (US$ Mn), 2019 - 2025
4.2.1. By Country, 2019 – 2025
4.2.1.1. Germany
4.2.1.2. U.K.
4.2.1.3. France
4.2.1.4. Italy
4.2.1.5. Spain
4.2.1.6. Rest of Europe
4.2.2. By Components
4.2.2.1. Solutions
4.2.2.2. Services
4.2.2.2.1. Training and Consulting
4.2.2.2.2. System Integration and Testing
4.2.2.2.3. Support and Maintenance
4.2.3. By Applications
4.2.3.1. Product Recommendation
4.2.3.2. Product Search and Discovery
4.2.3.3. Supply Chain Management and Demand Forecasting
4.2.3.4. Creative Designing and Trend Forecasting
4.2.3.5. Customer Relationship Management
4.2.3.6. Virtual Assistants
4.2.3.7. Others
4.2.4. By Deployment Mode
4.2.4.1. Cloud
4.2.4.2. On-premises
4.2.5. By Category
4.2.5.1. Apparel
4.2.5.2. Accessories
4.2.5.3. Footwear
4.2.5.4. Beauty and Cosmetics
4.2.5.5. Jewelry and Watches
4.2.5.6. Others
4.2.6. By End-User
4.2.6.1. Fashion Designers
4.2.6.2. Fashion Stores
4.3. Asia Pacific AI in Fashion Market Analysis (US$ Mn), 2019 - 2025
4.3.1. By Country, 2019 – 2025
4.3.1.1. China
4.3.1.2. Japan
4.3.1.3. India
4.3.1.4. Rest of Asia Pacific
4.3.2. By Components
4.3.2.1. Solutions
4.3.2.2. Services
4.3.2.2.1. Training and Consulting
4.3.2.2.2. System Integration and Testing
4.3.2.2.3. Support and Maintenance
4.3.3. By Applications
4.3.3.1. Product Recommendation
4.3.3.2. Product Search and Discovery
4.3.3.3. Supply Chain Management and Demand Forecasting
4.3.3.4. Creative Designing and Trend Forecasting
4.3.3.5. Customer Relationship Management
4.3.3.6. Virtual Assistants
4.3.3.7. Others
4.3.4. By Deployment Mode
4.3.4.1. Cloud
4.3.4.2. On-premises
4.3.5. By Category
4.3.5.1. Apparel
4.3.5.2. Accessories
4.3.5.3. Footwear
4.3.5.4. Beauty and Cosmetics
4.3.5.5. Jewelry and Watches
4.3.5.6. Others
4.3.6. By End-User
4.3.6.1. Fashion Designers
4.3.6.2. Fashion Stores
4.4. Middle East & Africa AI in Fashion Market Analysis (US$ Mn), 2019 - 2025
4.4.1. By Country, 2019 – 2025
4.4.1.1. GCC
4.4.1.2. South Africa
4.4.1.3. Rest of Middle East & Africa
4.4.2. By Components
4.4.2.1. Solutions
4.4.2.2. Services
4.4.2.2.1. Training and Consulting
4.4.2.2.2. System Integration and Testing
4.4.2.2.3. Support and Maintenance
4.4.3. By Applications
4.4.3.1. Product Recommendation
4.4.3.2. Product Search and Discovery
4.4.3.3. Supply Chain Management and Demand Forecasting
4.4.3.4. Creative Designing and Trend Forecasting
4.4.3.5. Customer Relationship Management
4.4.3.6. Virtual Assistants
4.4.3.7. Others
4.4.4. By Deployment Mode
4.4.4.1. Cloud
4.4.4.2. On-premises
4.4.5. By Category
4.4.5.1. Apparel
4.4.5.2. Accessories
4.4.5.3. Footwear
4.4.5.4. Beauty and Cosmetics
4.4.5.5. Jewelry and Watches
4.4.5.6. Others
4.4.6. By End-User
4.4.6.1. Fashion Designers
4.4.6.2. Fashion Stores
4.5. Latin America AI in Fashion Market Analysis (US$ Mn), 2019 - 2025
4.5.1. By Country, 2019 – 2025
4.5.1.1. Brazil
4.5.1.2. Mexico
4.5.1.3. Rest of Latin America
4.5.2. By Components
4.5.2.1. Solutions
4.5.2.2. Services
4.5.2.2.1. Training and Consulting
4.5.2.2.2. System Integration and Testing
4.5.2.2.3. Support and Maintenance
4.5.3. By Applications
4.5.3.1. Product Recommendation
4.5.3.2. Product Search and Discovery
4.5.3.3. Supply Chain Management and Demand Forecasting
4.5.3.4. Creative Designing and Trend Forecasting
4.5.3.5. Customer Relationship Management
4.5.3.6. Virtual Assistants
4.5.3.7. Others
4.5.4. By Deployment Mode
4.5.4.1. Cloud
4.5.4.2. On-premises
4.5.5. By Category
4.5.5.1. Apparel
4.5.5.2. Accessories
4.5.5.3. Footwear
4.5.5.4. Beauty and Cosmetics
4.5.5.5. Jewelry and Watches
4.5.5.6. Others
4.5.6. By End-User
4.5.6.1. Fashion Designers
4.5.6.2. Fashion Stores
5. Competitive Analysis
5.1. Company Share Analysis (%) 2019
5.2. List of Acquisition, Merger, Collaboration & New Product Launch
6. Company Profiles
6.1. Amazon Web Services, Inc.
6.2. Catchoom Technologies, S.L.
6.3. FindMine, Inc.
6.4. Heuritech
6.5. Huawei Technologies Co., Ltd.
6.6. Intelistyle Ltd.
6.7. International Business Machines Corporation
6.8. Microsoft Corporation
6.9. Syte Visual Conception ltd.
6.10. Wide Eyes Technologies
Research Methodology:
AI in Fashion Market Size Estimation
To estimate market size and trends, we use a combination of top-down and bottom-up methods. This allows us to evaluate the market from various perspectives—by company, region, product type, and end users.
Our estimates are based on actual sales data, excluding any discounts. Segment breakdowns and market shares are calculated using weighted averages based on usage rates and average prices. Regional insights are determined by how widely a product or service is adopted in each area.
Key companies are identified through secondary sources like industry reports and company filings. We then verify revenue estimates and other key data points through primary research, including interviews with industry experts, company executives, and decision-makers.
We take into account all relevant factors that could influence the market and validate our findings with real-world input. Our final insights combine both qualitative and quantitative data to provide a well-rounded view. Please note, these estimates do not account for unexpected changes such as inflation, economic downturns, or policy shifts.
Data Source
Secondary Sources
This study draws on a wide range of secondary sources, including press releases, annual reports, non-profit organizations, industry associations, government agencies, and customs data. We also referred to reputable databases and directories such as Bloomberg, Wind Info, Hoovers, Factiva, Trading Economics, Statista, and others. Additional references include investor presentations, company filings (e.g., SEC), economic data, and documents from regulatory and industry bodies.
These sources were used to gather technical and market-focused insights, identify key players, analyze market segmentation and classification, and track major trends and developments across industries.
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Primary Sources
As part of our primary research, we interviewed a variety of stakeholders from both the supply and demand sides to gather valuable qualitative and quantitative insights.
On the supply side, we spoke with product manufacturers, competitors, industry experts, research institutions, distributors, traders, and raw material suppliers. On the demand side, we engaged with business leaders, marketing and sales heads, technology and innovation directors, supply chain executives, and end users across key organizations.
These conversations helped us better understand market segmentation, pricing, applications, leading players, supply chains, demand trends, industry outlook, and key market dynamics—including risks, opportunities, barriers, and strategic developments.
Key Data Information from Primary Sources
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