Global AI in Fashion Market- Industry Analysis and Forecast (2020-2027) – by Components, Applications, Deployment Mode, Category, End-User and Region.

Global AI in Fashion Market size is expected to grow at 40.5% throughout the forecast period, reaching nearly US$ 3.33 Bn by 2027. To know about the Research Methodology :- Request Free Sample Report

Role of AI (Artificial Intelligence) and its Impact on the Fashion Industry:

AI in fashion is changing the fashion industry by playing a vital role in the many key divisions. From design to manufacturing, marketing, and logistic supply chain, AI in fashion is playing a big role in transforming this industry. Artificial Intelligence-enabled applications and systems are enhancing the consumer’s experience that goes beyond personalized ads, notification alerts on chatbot assistance or cost drops.

Global AI in Fashion Market Trends of AI in the Fashion industry:

The report covers all the trends and technologies playing a major role in the growth of the AI in the fashion market during 2020-2027. The patterns and designs with a suitable color combination are the key point to design a costume to make it attractive among the clients. AI can detect the new trends with demand in projecting the new trend reducing the estimating error. Trends in the fashion industry change rapidly with new patterns or designs come every day in the market. Designers must keep pacing with new styles. And AI algorithms can study designs through images to copying popular styles. The report study has analyzed revenue impact of covid-19 pandemic on the sales revenue of market leaders, market followers and disrupters in the report and same is reflected in our analysis.

Global AI in Fashion Market Dynamics:

The MMR report contains a detailed list of factors that will drive and restrain the growth of the AI in fashion market. The fashion industry has implemented the newest AI (Artificial Intelligence) technology which enhances the consumer experience and upsurges the sales in the industry by growing customization by signifying related clothing patterns according to client needs. Similarly, the use of AI has transported in automatic operations in ordinary tasks such as calculations, data entry, and many more. Also, clients demand a personalized experience, a growing need for inventory management and the rising influence of social media in the fashion industry has led to the adoption of AI in Fashion during the forecast period. However, data security and privacy concerns through the sector would pose a stern challenge to the growth of the global market for AI in fashion during the forecast period. Despite these restrictions, the introduction of NPL (Natural Language Programming) to the fashion industry is a huge opportunity for Artificial Intelligence in fashion vendors are anticipated to provide ample growth opportunities for the companies operating in the AI in fashion market during the forecast period.

Global AI in Fashion Market Manufacturing process:

Fashion brands using AI (Artificial Intelligence) and ML (Machine Learning) tools are now able to find fast-changing fashion trends and supply the latest fashion accessories to retail defers faster than the “traditional” fashion retailer. Consequently, prominent fashion brands such as Top Shop, Zara, and H&M are faster in providing instant satisfaction to retail customers by recognizing seasonal demands and developed the right supply of modern clothing.

Global AI in Fashion Market segmentation:

The report provides an in-depth segment analysis of the Global AI in Fashion Market, thereby providing valuable insights at the macro as well as micro levels. Based on end-users, fashion stores segment held the largest market share of XX% in 2019 and is projected to grow at the highest CAGR of XX% to reach US$ XX Mn by 2027. Fashion stores contain offline fashion stores and online fashion stores that have started deploying Artificial Intelligence technologies into their operations. Growing deployment of cloud-based AI-powered solution by fashion retailers has aided brands to gain a competitive benefit over other players.

AI helping to promote and sell fashion goods:

The fashion industry is just as much about making demand and brand awareness as it is about the manufacturing of fashion products. Clothing and apparel brands are always looking for new ways to get their goods in front of buyers and generate awareness and demand in the market. Progressively, fashion brands are using AI and ML to exploit users’ shopping experience, improve the efficiency of sales systems through intelligent automation, and boost the sales processes using predictive analytics and conducted sales processes.

Global AI in Fashion Market Regional Analysis:

North America AI in fashion market was valued at US$ XX million in 2019 and is expected to reach a value of US$ XX million by 2027, with a CAGR of XX% during the forecast period. The North American economies are developing many policies and outlining best practices to implement AI for helping innovation in various industry sectors. AI technologies like self-adapting machine learning, deep learning or Natural language processing(NLA) are expected to transform the way businesses work. Governments of several North American economies are working on drafting a robust and comprehensive set of regulations and policies for the holistic development of AI in this region. Besides, the inclination of the Asia Pacific economies toward emerging technologies like 3G and 4G is also expected to drive the growth of the AI in the fashion market. However, privacy issues, the lack of technological awareness, and limited technical expertise in advanced technologies remain major hurdles in the AI in fashion adoption across the APAC. The objective of the report is to present a comprehensive analysis of the Global AI in Fashion Market including all the stakeholders of the industry. The past and current status of the industry with forecasted market size and trends are presented in the report with the analysis of complicated data in simple language. The report covers all the aspects of the industry with a dedicated study of key players that includes market leaders, followers and new entrants by region. PORTER, SVOR, PESTEL analysis with the potential impact of micro-economic factors by region on the market have been presented in the report. External as well as internal factors that are supposed to affect the business positively or negatively have been analyzed, which will give a clear futuristic view of the industry to the decision-makers. The report also helps in understanding Global AI in Fashion Market dynamics, structure by analyzing the market segments and project the Global AI in Fashion Market size. Clear representation of competitive analysis of key players by Application, price, financial position, Product portfolio, growth strategies, and regional presence in the Global AI in Fashion Market make the report investor’s guide.

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Global AI in Fashion Market, by Components

• Solution Software Tools Platforms • Services Training and Consulting System Integration and Testing Support and Maintenance

Global AI in Fashion Market, 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 (Fraud detection, fabric waste reduction, and price optimization)

Global AI in Fashion Market, by Deployment Mode

• Cloud • On-premises

Global AI in Fashion Market, by Category

• Apparel • Accessories • Footwear • Beauty and Cosmetics • Jewelry and Watches • Others (eyewear, home decor)

Global AI in Fashion Market, by End-User

• Fashion Designers • Fashion Stores

Global AI in Fashion Market, by Region

• North America • Europe • Asia Pacific • Middle East & Africa • South America

Key players operating in the Global AI in Fashion Market

• Microsoft • IBM • Google • AWS • SAP • Facebook • Adobe • Oracle • Catchoom • Huawei • Vue.AI • Heuritech • Wide Eyes • Findmine • Intelistyle • Lily AI • Pttrns.AI • Syte • Mode.AI • Stitch Fix • Alibaba. • Amazon. • H&M. • Tommy Hilfiger. • ASOS.
Global AI in Fashion Market 1. Preface 1.1. Report Scope and Market Segmentation 1.2. Research Highlights 1.3. Research Objectives 2. Assumptions and Research Methodology 2.1. Report Assumptions 2.2. Abbreviations 2.3. Research Methodology 2.3.1. Secondary Research 2.3.1.1. Secondary data 2.3.1.2. Secondary Sources 2.3.2. Primary Research 2.3.2.1. Data from Primary Sources 2.3.2.2. Breakdown of Primary Sources 3. Executive Summary: Global AI in Fashion Market Size, by Market Value (US$ Mn) 4. Market Overview 4.1. Introduction 4.2. Market Indicator 4.2.1. Drivers 4.2.2. Restraints 4.2.3. Opportunities 4.2.4. Challenges 4.3. Porter’s Analysis 4.4. Value Chain Analysis 4.5. Market Risk Analysis 4.6. SWOT Analysis 4.7. Industry Trends and Emerging Technologies 5. Supply Side and Demand Side Indicators 6. Global AI in Fashion Market Analysis and Forecast 6.1. Global AI in Fashion Market Size & Y-o-Y Growth Analysis 6.1.1. North America 6.1.2. Europe 6.1.3. Asia Pacific 6.1.4. Middle East & Africa 6.1.5. South America 7. Global AI in Fashion Market Analysis and Forecast, By Components 7.1. Introduction and Definition 7.2. Key Findings 7.3. Global AI in Fashion Market Value Share Analysis, By Components 7.4. Global AI in Fashion Market Size (US$ Mn) Forecast, By Components 7.5. Global AI in Fashion Market Analysis, By Components 7.6. Global AI in Fashion Market Attractiveness Analysis, By Components 8. Global AI in Fashion Market Analysis and Forecast, By Applications 8.1. Introduction and Definition 8.2. Key Findings 8.3. Global AI in Fashion Market Value Share Analysis, By Applications 8.4. Global AI in Fashion Market Size (US$ Mn) Forecast, By Applications 8.5. Global AI in Fashion Market Analysis, By Applications 8.6. Global AI in Fashion Market Attractiveness Analysis, By Applications 9. Global AI in Fashion Market Analysis and Forecast, By Deployment Mode 9.1. Introduction and Definition 9.2. Key Findings 9.3. Global AI in Fashion Market Value Share Analysis, By Deployment Mode 9.4. Global AI in Fashion Market Size (US$ Mn) Forecast, By Deployment Mode 9.5. Global AI in Fashion Market Analysis, By Deployment Mode 9.6. Global AI in Fashion Market Attractiveness Analysis, By Deployment Mode 10. Global AI in Fashion Market Analysis and Forecast, By Category 10.1. Introduction and Definition 10.2. Key Findings 10.3. Global AI in Fashion Market Value Share Analysis, By Category 10.4. Global AI in Fashion Market Size (US$ Mn) Forecast, By Category 10.5. Global AI in Fashion Market Analysis, By Category 10.6. Global AI in Fashion Market Attractiveness Analysis, By Category 11. Global AI in Fashion Market Analysis and Forecast, By End-User 11.1. Introduction and Definition 11.2. Key Findings 11.3. Global AI in Fashion Market Value Share Analysis, By End-User 11.4. Global AI in Fashion Market Size (US$ Mn) Forecast, By End-User 11.5. Global AI in Fashion Market Analysis, By End-User 11.6. Global AI in Fashion Market Attractiveness Analysis, By End-User 12. Global AI in Fashion Market Analysis, by Region 12.1. Global AI in Fashion Market Value Share Analysis, by Region 12.2. Global AI in Fashion Market Size (US$ Mn) Forecast, by Region 12.3. Global AI in Fashion Market Attractiveness Analysis, by Region 13. North America AI in Fashion Market Analysis 13.1. Key Findings 13.2. North America AI in Fashion Market Overview 13.3. North America AI in Fashion Market Value Share Analysis, By Components 13.4. North America AI in Fashion Market Forecast, By Components 13.4.1. Solution 13.4.1.1. Software Tools 13.4.1.2. Platforms 13.4.2. Services 13.4.2.1. Training and Consulting 13.4.2.2. System Integration and Testing 13.4.2.3. Support and Maintenance 13.5. North America AI in Fashion Market Value Share Analysis, By Applications 13.6. North America AI in Fashion Market Forecast, By Applications 13.6.1. Product Recommendation 13.6.2. Product Search and Discovery 13.6.3. Supply Chain Management and Demand Forecasting 13.6.4. Creative Designing and Trend Forecasting 13.6.5. Customer Relationship Management 13.6.6. Virtual Assistants 13.6.7. Others (Fraud detection, fabric waste reduction, and price optimization) 13.7. North America AI in Fashion Market Value Share Analysis, By Deployment Mode 13.8. North America AI in Fashion Market Forecast, By Deployment Mode 13.8.1. Cloud 13.8.2. On-premises 13.9. North America AI in Fashion Market Value Share Analysis, By Category 13.10. North America AI in Fashion Market Forecast, By Category 13.10.1. Apparel 13.10.2. Accessories 13.10.3. Footwear 13.10.4. Beauty and Cosmetics 13.10.5. Jewelry and Watches 13.10.6. Others (eyewear, home decor) 13.11. North America AI in Fashion Market Value Share Analysis, By End-User 13.12. North America AI in Fashion Market Forecast, By End-User 13.12.1. Fashion Designers 13.12.2. Fashion Stores 13.13. North America AI in Fashion Market Value Share Analysis, by Country 13.14. North America AI in Fashion Market Forecast, by Country 13.14.1. U.S. 13.14.2. Canada 13.15. North America AI in Fashion Market Analysis, by Country 13.16. U.S. AI in Fashion Market Forecast, By Components 13.16.1. Solution 13.16.1.1. Software Tools 13.16.1.2. Platforms 13.16.2. Services 13.16.2.1. Training and Consulting 13.16.2.2. System Integration and Testing 13.16.2.3. Support and Maintenance 13.17. U.S. AI in Fashion Market Forecast, By Applications 13.17.1. Product Recommendation 13.17.2. Product Search and Discovery 13.17.3. Supply Chain Management and Demand Forecasting 13.17.4. Creative Designing and Trend Forecasting 13.17.5. Customer Relationship Management 13.17.6. Virtual Assistants 13.17.7. Others (Fraud detection, fabric waste reduction, and price optimization) 13.18. U.S. AI in Fashion Market Forecast, By Deployment Mode 13.18.1. Cloud 13.18.2. On-premises 13.19. U.S. AI in Fashion Market Forecast, By Category 13.19.1. Apparel 13.19.2. Accessories 13.19.3. Footwear 13.19.4. Beauty and Cosmetics 13.19.5. Jewelry and Watches 13.19.6. Others (eyewear, home decor) 13.20. U.S. AI in Fashion Market Forecast, By End-User 13.20.1. Fashion Designers 13.20.2. Fashion Stores 13.21. Canada AI in Fashion Market Forecast, By Components 13.21.1. Solution 13.21.1.1. Software Tools 13.21.1.2. Platforms 13.21.2. Services 13.21.2.1. Training and Consulting 13.21.2.2. System Integration and Testing 13.21.2.3. Support and Maintenance 13.22. Canada AI in Fashion Market Forecast, By Applications 13.22.1. Product Recommendation 13.22.2. Product Search and Discovery 13.22.3. Supply Chain Management and Demand Forecasting 13.22.4. Creative Designing and Trend Forecasting 13.22.5. Customer Relationship Management 13.22.6. Virtual Assistants 13.22.7. Others (Fraud detection, fabric waste reduction, and price optimization) 13.23. Canada AI in Fashion Market Forecast, By Deployment Mode 13.23.1. Cloud 13.23.2. On-premises 13.24. Canada AI in Fashion Market Forecast, By Category 13.24.1. Apparel 13.24.2. Accessories 13.24.3. Footwear 13.24.4. Beauty and Cosmetics 13.24.5. Jewelry and Watches 13.24.6. Others (eyewear, home decor) 13.25. Canada AI in Fashion Market Forecast, By End-User 13.25.1. Fashion Designers 13.25.2. Fashion Stores 13.26. North America AI in Fashion Market Attractiveness Analysis 13.26.1. By Components 13.26.2. By Applications 13.26.3. By Deployment Mode 13.26.4. By Category 13.26.5. By End-User 13.27. PEST Analysis 13.28. Key Trends 13.29. Key Developments 14. Europe AI in Fashion Market Analysis 14.1. Key Findings 14.2. Europe AI in Fashion Market Overview 14.3. Europe AI in Fashion Market Value Share Analysis, By Components 14.4. Europe AI in Fashion Market Forecast, By Components 14.4.1. Solution 14.4.1.1. Software Tools 14.4.1.2. Platforms 14.4.2. Services 14.4.2.1. Training and Consulting 14.4.2.2. System Integration and Testing 14.4.2.3. Support and Maintenance 14.5. Europe AI in Fashion Market Value Share Analysis, By Applications 14.6. Europe AI in Fashion Market Forecast, By Applications 14.6.1. Product Recommendation 14.6.2. Product Search and Discovery 14.6.3. Supply Chain Management and Demand Forecasting 14.6.4. Creative Designing and Trend Forecasting 14.6.5. Customer Relationship Management 14.6.6. Virtual Assistants 14.6.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.7. Europe AI in Fashion Market Value Share Analysis, By Deployment Mode 14.8. Europe AI in Fashion Market Forecast, By Deployment Mode 14.8.1. Cloud 14.8.2. On-premises 14.9. Europe AI in Fashion Market Value Share Analysis, By Category 14.10. Europe AI in Fashion Market Forecast, By Category 14.10.1. Apparel 14.10.2. Accessories 14.10.3. Footwear 14.10.4. Beauty and Cosmetics 14.10.5. Jewelry and Watches 14.10.6. Others (eyewear, home decor) 14.11. Europe AI in Fashion Market Value Share Analysis, By End-User 14.12. Europe AI in Fashion Market Forecast, By End-User 14.12.1. Fashion Designers 14.12.2. Fashion Stores 14.13. Europe AI in Fashion Market Value Share Analysis, by Country 14.14. Europe AI in Fashion Market Forecast, by Country 14.14.1. Germany 14.14.2. U.K. 14.14.3. France 14.14.4. Italy 14.14.5. Spain 14.14.6. Rest of Europe 14.15. Europe AI in Fashion Market Analysis, by Country 14.16. Germany AI in Fashion Market Forecast, By Components 14.16.1. Solution 14.16.1.1. Software Tools 14.16.1.2. Platforms 14.16.2. Services 14.16.2.1. Training and Consulting 14.16.2.2. System Integration and Testing 14.16.2.3. Support and Maintenance 14.17. Germany AI in Fashion Market Forecast, By Applications 14.17.1. Product Recommendation 14.17.2. Product Search and Discovery 14.17.3. Supply Chain Management and Demand Forecasting 14.17.4. Creative Designing and Trend Forecasting 14.17.5. Customer Relationship Management 14.17.6. Virtual Assistants 14.17.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.18. Germany AI in Fashion Market Forecast, By Deployment Mode 14.18.1. Cloud 14.18.2. On-premises 14.19. Germany AI in Fashion Market Forecast, By Category 14.19.1. Apparel 14.19.2. Accessories 14.19.3. Footwear 14.19.4. Beauty and Cosmetics 14.19.5. Jewelry and Watches 14.19.6. Others (eyewear, home decor) 14.20. Germany AI in Fashion Market Forecast, By End-User 14.20.1. Fashion Designers 14.20.2. Fashion Stores 14.21. U.K. AI in Fashion Market Forecast, By Components 14.21.1. Solution 14.21.1.1. Software Tools 14.21.1.2. Platforms 14.21.2. Services 14.21.2.1. Training and Consulting 14.21.2.2. System Integration and Testing 14.21.2.3. Support and Maintenance 14.22. U.K. AI in Fashion Market Forecast, By Applications 14.22.1. Product Recommendation 14.22.2. Product Search and Discovery 14.22.3. Supply Chain Management and Demand Forecasting 14.22.4. Creative Designing and Trend Forecasting 14.22.5. Customer Relationship Management 14.22.6. Virtual Assistants 14.22.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.23. U.K. AI in Fashion Market Forecast, By Deployment Mode 14.23.1. Cloud 14.23.2. On-premises 14.24. U.K. AI in Fashion Market Forecast, By Category 14.24.1. Apparel 14.24.2. Accessories 14.24.3. Footwear 14.24.4. Beauty and Cosmetics 14.24.5. Jewelry and Watches 14.24.6. Others (eyewear, home decor) 14.25. U.K. AI in Fashion Market Forecast, By End-User 14.25.1. Fashion Designers 14.25.2. Fashion Stores 14.26. France AI in Fashion Market Forecast, By Components 14.26.1. Solution 14.26.1.1. Software Tools 14.26.1.2. Platforms 14.26.2. Services 14.26.2.1. Training and Consulting 14.26.2.2. System Integration and Testing 14.26.2.3. Support and Maintenance 14.27. France AI in Fashion Market Forecast, By Applications 14.27.1. Product Recommendation 14.27.2. Product Search and Discovery 14.27.3. Supply Chain Management and Demand Forecasting 14.27.4. Creative Designing and Trend Forecasting 14.27.5. Customer Relationship Management 14.27.6. Virtual Assistants 14.27.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.28. France AI in Fashion Market Forecast, By Deployment Mode 14.28.1. Cloud 14.28.2. On-premises 14.29. France AI in Fashion Market Forecast, By Category 14.29.1. Apparel 14.29.2. Accessories 14.29.3. Footwear 14.29.4. Beauty and Cosmetics 14.29.5. Jewelry and Watches 14.29.6. Others (eyewear, home decor) 14.30. France AI in Fashion Market Forecast, By End-User 14.30.1. Fashion Designers 14.30.2. Fashion Stores 14.31. Italy AI in Fashion Market Forecast, By Components 14.31.1. Solution 14.31.1.1. Software Tools 14.31.1.2. Platforms 14.31.2. Services 14.31.2.1. Training and Consulting 14.31.2.2. System Integration and Testing 14.31.2.3. Support and Maintenance 14.32. Italy AI in Fashion Market Forecast, By Applications 14.32.1. Product Recommendation 14.32.2. Product Search and Discovery 14.32.3. Supply Chain Management and Demand Forecasting 14.32.4. Creative Designing and Trend Forecasting 14.32.5. Customer Relationship Management 14.32.6. Virtual Assistants 14.32.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.33. Italy AI in Fashion Market Forecast, By Deployment Mode 14.33.1. Cloud 14.33.2. On-premises 14.34. Italy AI in Fashion Market Forecast, By Category 14.34.1. Apparel 14.34.2. Accessories 14.34.3. Footwear 14.34.4. Beauty and Cosmetics 14.34.5. Jewelry and Watches 14.34.6. Others (eyewear, home decor) 14.35. Italy AI in Fashion Market Forecast, By End-User 14.35.1. Fashion Designers 14.35.2. Fashion Stores 14.36. Spain AI in Fashion Market Forecast, By Components 14.36.1. Solution 14.36.1.1. Software Tools 14.36.1.2. Platforms 14.36.2. Services 14.36.2.1. Training and Consulting 14.36.2.2. System Integration and Testing 14.36.2.3. Support and Maintenance 14.37. Spain AI in Fashion Market Forecast, By Applications 14.37.1. Product Recommendation 14.37.2. Product Search and Discovery 14.37.3. Supply Chain Management and Demand Forecasting 14.37.4. Creative Designing and Trend Forecasting 14.37.5. Customer Relationship Management 14.37.6. Virtual Assistants 14.37.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.38. Spain AI in Fashion Market Forecast, By Deployment Mode 14.38.1. Cloud 14.38.2. On-premises 14.39. Spain AI in Fashion Market Forecast, By Category 14.39.1. Apparel 14.39.2. Accessories 14.39.3. Footwear 14.39.4. Beauty and Cosmetics 14.39.5. Jewelry and Watches 14.39.6. Others (eyewear, home decor) 14.40. Spain AI in Fashion Market Forecast, By End-User 14.40.1. Fashion Designers 14.40.2. Fashion Stores 14.41. Rest of Europe AI in Fashion Market Forecast, By Components 14.41.1. Solution 14.41.1.1. Software Tools 14.41.1.2. Platforms 14.41.2. Services 14.41.2.1. Training and Consulting 14.41.2.2. System Integration and Testing 14.41.2.3. Support and Maintenance 14.42. Rest of Europe AI in Fashion Market Forecast, By Applications 14.42.1. Product Recommendation 14.42.2. Product Search and Discovery 14.42.3. Supply Chain Management and Demand Forecasting 14.42.4. Creative Designing and Trend Forecasting 14.42.5. Customer Relationship Management 14.42.6. Virtual Assistants 14.42.7. Others (Fraud detection, fabric waste reduction, and price optimization) 14.43. Rest of Europe AI in Fashion Market Forecast, By Deployment Mode 14.43.1. Cloud 14.43.2. On-premises 14.44. Rest Of Europe AI in Fashion Market Forecast, By Category 14.44.1. Apparel 14.44.2. Accessories 14.44.3. Footwear 14.44.4. Beauty and Cosmetics 14.44.5. Jewelry and Watches 14.44.6. Others (eyewear, home decor) 14.45. Rest Of Europe AI in Fashion Market Forecast, By End-User 14.45.1. Fashion Designers 14.45.2. Fashion Stores 14.46. Europe AI in Fashion Market Attractiveness Analysis 14.46.1. By Components 14.46.2. By Applications 14.46.3. By Deployment Mode 14.46.4. By Category 14.46.5. By End-User 14.47. PEST Analysis 14.48. Key Trends 14.49. Key Developments 15. Asia Pacific AI in Fashion Market Analysis 15.1. Key Findings 15.2. Asia Pacific AI in Fashion Market Overview 15.3. Asia Pacific AI in Fashion Market Value Share Analysis, By Components 15.4. Asia Pacific AI in Fashion Market Forecast, By Components 15.4.1. Solution 15.4.1.1. Software Tools 15.4.1.2. Platforms 15.4.2. Services 15.4.2.1. Training and Consulting 15.4.2.2. System Integration and Testing 15.4.2.3. Support and Maintenance 15.5. Asia Pacific AI in Fashion Market Value Share Analysis, By Applications 15.6. Asia Pacific AI in Fashion Market Forecast, By Applications 15.6.1. Product Recommendation 15.6.2. Product Search and Discovery 15.6.3. Supply Chain Management and Demand Forecasting 15.6.4. Creative Designing and Trend Forecasting 15.6.5. Customer Relationship Management 15.6.6. Virtual Assistants 15.6.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.7. Asia Pacific AI in Fashion Market Value Share Analysis, By Deployment Mode 15.8. Asia Pacific AI in Fashion Market Forecast, By Deployment Mode 15.8.1. Cloud 15.8.2. On-premises 15.9. Asia Pacific AI in Fashion Market Value Share Analysis, By Category 15.10. Asia Pacific AI in Fashion Market Forecast, By Category 15.10.1. Apparel 15.10.2. Accessories 15.10.3. Footwear 15.10.4. Beauty and Cosmetics 15.10.5. Jewelry and Watches 15.10.6. Others (eyewear, home decor) 15.11. Asia Pacific AI in Fashion Market Value Share Analysis, By End-User 15.12. Asia Pacific AI in Fashion Market Forecast, By End-User 15.12.1. Fashion Designers 15.12.2. Fashion Stores 15.13. Asia Pacific AI in Fashion Market Value Share Analysis, by Country 15.14. Asia Pacific AI in Fashion Market Forecast, by Country 15.14.1. China 15.14.2. India 15.14.3. Japan 15.14.4. ASEAN 15.14.5. Rest of Asia Pacific 15.15. Asia Pacific AI in Fashion Market Analysis, by Country 15.16. China AI in Fashion Market Forecast, By Components 15.16.1. Solution 15.16.1.1. Software Tools 15.16.1.2. Platforms 15.16.2. Services 15.16.2.1. Training and Consulting 15.16.2.2. System Integration and Testing 15.16.2.3. Support and Maintenance 15.17. China AI in Fashion Market Forecast, By Applications 15.17.1. Product Recommendation 15.17.2. Product Search and Discovery 15.17.3. Supply Chain Management and Demand Forecasting 15.17.4. Creative Designing and Trend Forecasting 15.17.5. Customer Relationship Management 15.17.6. Virtual Assistants 15.17.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.18. China AI in Fashion Market Forecast, By Deployment Mode 15.18.1. Cloud 15.18.2. On-premises 15.19. China AI in Fashion Market Forecast, By Category 15.19.1. Apparel 15.19.2. Accessories 15.19.3. Footwear 15.19.4. Beauty and Cosmetics 15.19.5. Jewelry and Watches 15.19.6. Others (eyewear, home decor) 15.20. China AI in Fashion Market Forecast, By End-User 15.20.1. Fashion Designers 15.20.2. Fashion Stores 15.21. India AI in Fashion Market Forecast, By Components 15.21.1. Solution 15.21.1.1. Software Tools 15.21.1.2. Platforms 15.21.2. Services 15.21.2.1. Training and Consulting 15.21.2.2. System Integration and Testing 15.21.2.3. Support and Maintenance 15.22. India AI in Fashion Market Forecast, By Applications 15.22.1. Product Recommendation 15.22.2. Product Search and Discovery 15.22.3. Supply Chain Management and Demand Forecasting 15.22.4. Creative Designing and Trend Forecasting 15.22.5. Customer Relationship Management 15.22.6. Virtual Assistants 15.22.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.23. India AI in Fashion Market Forecast, By Deployment Mode 15.23.1. Cloud 15.23.2. On-premises 15.24. India AI in Fashion Market Forecast, By Category 15.24.1. Apparel 15.24.2. Accessories 15.24.3. Footwear 15.24.4. Beauty and Cosmetics 15.24.5. Jewelry and Watches 15.24.6. Others (eyewear, home decor) 15.25. India AI in Fashion Market Forecast, By End-User 15.25.1. Fashion Designers 15.25.2. Fashion Stores 15.26. Japan AI in Fashion Market Forecast, By Components 15.26.1. Solution 15.26.1.1. Software Tools 15.26.1.2. Platforms 15.26.2. Services 15.26.2.1. Training and Consulting 15.26.2.2. System Integration and Testing 15.26.2.3. Support and Maintenance 15.27. Japan AI in Fashion Market Forecast, By Applications 15.27.1. Product Recommendation 15.27.2. Product Search and Discovery 15.27.3. Supply Chain Management and Demand Forecasting 15.27.4. Creative Designing and Trend Forecasting 15.27.5. Customer Relationship Management 15.27.6. Virtual Assistants 15.27.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.28. Japan AI in Fashion Market Forecast, By Deployment Mode 15.28.1. Cloud 15.28.2. On-premises 15.29. Japan AI in Fashion Market Forecast, By Category 15.29.1. Apparel 15.29.2. Accessories 15.29.3. Footwear 15.29.4. Beauty and Cosmetics 15.29.5. Jewelry and Watches 15.29.6. Others (eyewear, home decor) 15.30. Japan AI in Fashion Market Forecast, By End-User 15.30.1. Fashion Designers 15.30.2. Fashion Stores 15.31. ASEAN AI in Fashion Market Forecast, By Components 15.31.1. Solution 15.31.1.1. Software Tools 15.31.1.2. Platforms 15.31.2. Services 15.31.2.1. Training and Consulting 15.31.2.2. System Integration and Testing 15.31.2.3. Support and Maintenance 15.32. ASEAN AI in Fashion Market Forecast, By Applications 15.32.1. Product Recommendation 15.32.2. Product Search and Discovery 15.32.3. Supply Chain Management and Demand Forecasting 15.32.4. Creative Designing and Trend Forecasting 15.32.5. Customer Relationship Management 15.32.6. Virtual Assistants 15.32.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.33. ASEAN AI in Fashion Market Forecast, By Deployment Mode 15.33.1. Cloud 15.33.2. On-premises 15.34. ASEAN AI in Fashion Market Forecast, By Category 15.34.1. Apparel 15.34.2. Accessories 15.34.3. Footwear 15.34.4. Beauty and Cosmetics 15.34.5. Jewelry and Watches 15.34.6. Others (eyewear, home decor) 15.35. ASEAN AI in Fashion Market Forecast, By End-User 15.35.1. Fashion Designers 15.35.2. Fashion Stores 15.36. Rest of Asia Pacific AI in Fashion Market Forecast, By Components 15.36.1. Solution 15.36.1.1. Software Tools 15.36.1.2. Platforms 15.36.2. Services 15.36.2.1. Training and Consulting 15.36.2.2. System Integration and Testing 15.36.2.3. Support and Maintenance 15.37. Rest of Asia Pacific AI in Fashion Market Forecast, By Applications 15.37.1. Product Recommendation 15.37.2. Product Search and Discovery 15.37.3. Supply Chain Management and Demand Forecasting 15.37.4. Creative Designing and Trend Forecasting 15.37.5. Customer Relationship Management 15.37.6. Virtual Assistants 15.37.7. Others (Fraud detection, fabric waste reduction, and price optimization) 15.38. Rest of Asia Pacific AI in Fashion Market Forecast, By Deployment Mode 15.38.1. Cloud 15.38.2. On-premises 15.39. Rest of Asia Pacific AI in Fashion Market Forecast, By Category 15.39.1. Apparel 15.39.2. Accessories 15.39.3. Footwear 15.39.4. Beauty and Cosmetics 15.39.5. Jewelry and Watches 15.39.6. Others (eyewear, home decor) 15.40. Rest of Asia Pacific AI in Fashion Market Forecast, By End-User 15.40.1. Fashion Designers 15.40.2. Fashion Stores 15.41. Asia Pacific AI in Fashion Market Attractiveness Analysis 15.41.1. By Components 15.41.2. By Applications 15.41.3. By Deployment Mode 15.41.4. By Category 15.41.5. By End-User 15.42. PEST Analysis 15.43. Key Trends 15.44. Key Developments 16. Middle East & Africa AI in Fashion Market Analysis 16.1. Key Findings 16.2. Middle East & Africa AI in Fashion Market Overview 16.3. Middle East & Africa AI in Fashion Market Value Share Analysis, By Components 16.4. Middle East & Africa AI in Fashion Market Forecast, By Components 16.4.1. Solution 16.4.1.1. Software Tools 16.4.1.2. Platforms 16.4.2. Services 16.4.2.1. Training and Consulting 16.4.2.2. System Integration and Testing 16.4.2.3. Support and Maintenance 16.5. Middle East & Africa AI in Fashion Market Value Share Analysis, By Applications 16.6. Middle East & Africa AI in Fashion Market Forecast, By Applications 16.6.1. Product Recommendation 16.6.2. Product Search and Discovery 16.6.3. Supply Chain Management and Demand Forecasting 16.6.4. Creative Designing and Trend Forecasting 16.6.5. Customer Relationship Management 16.6.6. Virtual Assistants 16.6.7. Others (Fraud detection, fabric waste reduction, and price optimization) 16.7. Middle East & Africa AI in Fashion Market Value Share Analysis, By Deployment Mode 16.8. Middle East & Africa AI in Fashion Market Forecast, By Deployment Mode 16.8.1. Cloud 16.8.2. On-premises 16.9. Middle East & Africa AI in Fashion Market Value Share Analysis, By Category 16.10. Middle East & Africa AI in Fashion Market Forecast, By Category 16.10.1. Apparel 16.10.2. Accessories 16.10.3. Footwear 16.10.4. Beauty and Cosmetics 16.10.5. Jewelry and Watches 16.10.6. Others (eyewear, home decor) 16.11. Middle East & Africa AI in Fashion Market Value Share Analysis, By End-User 16.12. Middle East & Africa AI in Fashion Market Forecast, By End-User 16.12.1. Fashion Designers 16.12.2. Fashion Stores 16.13. Middle East & Africa AI in Fashion Market Value Share Analysis, by Country 16.14. Middle East & Africa AI in Fashion Market Forecast, by Country 16.14.1. GCC 16.14.2. South Africa 16.14.3. Rest of Middle East & Africa 16.15. Middle East & Africa AI in Fashion Market Analysis, by Country 16.16. GCC AI in Fashion Market Forecast, By Components 16.16.1. Solution 16.16.1.1. Software Tools 16.16.1.2. Platforms 16.16.2. Services 16.16.2.1. Training and Consulting 16.16.2.2. System Integration and Testing 16.16.2.3. Support and Maintenance 16.17. GCC AI in Fashion Market Forecast, By Applications 16.17.1. Product Recommendation 16.17.2. Product Search and Discovery 16.17.3. Supply Chain Management and Demand Forecasting 16.17.4. Creative Designing and Trend Forecasting 16.17.5. Customer Relationship Management 16.17.6. Virtual Assistants 16.17.7. Others (Fraud detection, fabric waste reduction, and price optimization) 16.18. GCC AI in Fashion Market Forecast, By Deployment Mode 16.18.1. Cloud 16.18.2. On-premises 16.19. GCC AI in Fashion Market Forecast, By Category 16.19.1. Apparel 16.19.2. Accessories 16.19.3. Footwear 16.19.4. Beauty and Cosmetics 16.19.5. Jewelry and Watches 16.19.6. Others (eyewear, home decor) 16.20. GCC AI in Fashion Market Forecast, By End-User 16.20.1. Fashion Designers 16.20.2. Fashion Stores 16.21. South Africa AI in Fashion Market Forecast, By Components 16.21.1. Solution 16.21.1.1. Software Tools 16.21.1.2. Platforms 16.21.2. Services 16.21.2.1. Training and Consulting 16.21.2.2. System Integration and Testing 16.21.2.3. Support and Maintenance 16.22. South Africa AI in Fashion Market Forecast, By Applications 16.22.1. Product Recommendation 16.22.2. Product Search and Discovery 16.22.3. Supply Chain Management and Demand Forecasting 16.22.4. Creative Designing and Trend Forecasting 16.22.5. Customer Relationship Management 16.22.6. Virtual Assistants 16.22.7. Others (Fraud detection, fabric waste reduction, and price optimization) 16.23. South Africa AI in Fashion Market Forecast, By Deployment Mode 16.23.1. Cloud 16.23.2. On-premises 16.24. South Africa AI in Fashion Market Forecast, By Category 16.24.1. Apparel 16.24.2. Accessories 16.24.3. Footwear 16.24.4. Beauty and Cosmetics 16.24.5. Jewelry and Watches 16.24.6. Others (eyewear, home decor) 16.25. South Africa AI in Fashion Market Forecast, By End-User 16.25.1. Fashion Designers 16.25.2. Fashion Stores 16.26. Rest of Middle East & Africa AI in Fashion Market Forecast, By Components 16.26.1. Solution 16.26.1.1. Software Tools 16.26.1.2. Platforms 16.26.2. Services 16.26.2.1. Training and Consulting 16.26.2.2. System Integration and Testing 16.26.2.3. Support and Maintenance 16.27. Rest of Middle East & Africa AI in Fashion Market Forecast, By Applications 16.27.1. Product Recommendation 16.27.2. Product Search and Discovery 16.27.3. Supply Chain Management and Demand Forecasting 16.27.4. Creative Designing and Trend Forecasting 16.27.5. Customer Relationship Management 16.27.6. Virtual Assistants 16.27.7. Others (Fraud detection, fabric waste reduction, and price optimization) 16.28. Rest of Middle East & Africa AI in Fashion Market Forecast, By Deployment Mode 16.28.1. Cloud 16.28.2. On-premises 16.29. Rest of Middle East & Africa AI in Fashion Market Forecast, By Category 16.29.1. Apparel 16.29.2. Accessories 16.29.3. Footwear 16.29.4. Beauty and Cosmetics 16.29.5. Jewelry and Watches 16.29.6. Others (eyewear, home decor) 16.30. Rest of Middle East & Africa AI in Fashion Market Forecast, By End-User 16.30.1. Fashion Designers 16.30.2. Fashion Stores 16.31. Middle East & Africa AI in Fashion Market Attractiveness Analysis 16.31.1. By Components 16.31.2. By Applications 16.31.3. By Deployment Mode 16.31.4. By Category 16.31.5. By End-User 16.32. PEST Analysis 16.33. Key Trends 16.34. Key Developments 17. South America AI in Fashion Market Analysis 17.1. Key Findings 17.2. South America AI in Fashion Market Overview 17.3. South America AI in Fashion Market Value Share Analysis, By Components 17.4. South America AI in Fashion Market Forecast, By Components 17.4.1. Solution 17.4.1.1. Software Tools 17.4.1.2. Platforms 17.4.2. Services 17.4.2.1. Training and Consulting 17.4.2.2. System Integration and Testing 17.4.2.3. Support and Maintenance 17.5. South America AI in Fashion Market Value Share Analysis, By Applications 17.6. South America AI in Fashion Market Forecast, By Applications 17.6.1. Product Recommendation 17.6.2. Product Search and Discovery 17.6.3. Supply Chain Management and Demand Forecasting 17.6.4. Creative Designing and Trend Forecasting 17.6.5. Customer Relationship Management 17.6.6. Virtual Assistants 17.6.7. Others (Fraud detection, fabric waste reduction, and price optimization) 17.7. South America AI in Fashion Market Value Share Analysis, By Deployment Mode 17.8. South America AI in Fashion Market Forecast, By Deployment Mode 17.8.1. Cloud 17.8.2. On-premises 17.9. South America AI in Fashion Market Value Share Analysis, By Category 17.10. South America AI in Fashion Market Forecast, By Category 17.10.1. Apparel 17.10.2. Accessories 17.10.3. Footwear 17.10.4. Beauty and Cosmetics 17.10.5. Jewelry and Watches 17.10.6. Others (eyewear, home decor) 17.11. South America AI in Fashion Market Value Share Analysis, By End-User 17.12. South America AI in Fashion Market Forecast, By End-User 17.12.1. Fashion Designers 17.12.2. Fashion Stores 17.13. South America AI in Fashion Market Value Share Analysis, by Country 17.14. South America AI in Fashion Market Forecast, by Country 17.14.1. Brazil 17.14.2. Mexico 17.14.3. Rest of South America 17.15. South America AI in Fashion Market Analysis, by Country 17.16. Brazil AI in Fashion Market Forecast, By Components 17.16.1. Solution 17.16.1.1. Software Tools 17.16.1.2. Platforms 17.16.2. Services 17.16.2.1. Training and Consulting 17.16.2.2. System Integration and Testing 17.16.2.3. Support and Maintenance 17.17. Brazil AI in Fashion Market Forecast, By Applications 17.17.1. Product Recommendation 17.17.2. Product Search and Discovery 17.17.3. Supply Chain Management and Demand Forecasting 17.17.4. Creative Designing and Trend Forecasting 17.17.5. Customer Relationship Management 17.17.6. Virtual Assistants 17.17.7. Others (Fraud detection, fabric waste reduction, and price optimization) 17.18. Brazil AI in Fashion Market Forecast, By Deployment Mode 17.18.1. Cloud 17.18.2. On-premises 17.19. Brazil AI in Fashion Market Forecast, By Category 17.19.1. Apparel 17.19.2. Accessories 17.19.3. Footwear 17.19.4. Beauty and Cosmetics 17.19.5. Jewelry and Watches 17.19.6. Others (eyewear, home decor) 17.20. Brazil AI in Fashion Market Forecast, By End-User 17.20.1. Fashion Designers 17.20.2. Fashion Stores 17.21. Mexico AI in Fashion Market Forecast, By Components 17.21.1. Solution 17.21.1.1. Software Tools 17.21.1.2. Platforms 17.21.2. Services 17.21.2.1. Training and Consulting 17.21.2.2. System Integration and Testing 17.21.2.3. Support and Maintenance 17.22. Mexico AI in Fashion Market Forecast, By Applications 17.22.1. Product Recommendation 17.22.2. Product Search and Discovery 17.22.3. Supply Chain Management and Demand Forecasting 17.22.4. Creative Designing and Trend Forecasting 17.22.5. Customer Relationship Management 17.22.6. Virtual Assistants 17.22.7. Others (Fraud detection, fabric waste reduction, and price optimization) 17.23. Mexico AI in Fashion Market Forecast, By Deployment Mode 17.23.1. Cloud 17.23.2. On-premises 17.24. Mexico AI in Fashion Market Forecast, By Category 17.24.1. Apparel 17.24.2. Accessories 17.24.3. Footwear 17.24.4. Beauty and Cosmetics 17.24.5. Jewelry and Watches 17.24.6. Others (eyewear, home decor) 17.25. Mexico AI in Fashion Market Forecast, By End-User 17.25.1. Fashion Designers 17.25.2. Fashion Stores 17.26. Rest of South America AI in Fashion Market Forecast, By Components 17.26.1. Solution 17.26.1.1. Software Tools 17.26.1.2. Platforms 17.26.2. Services 17.26.2.1. Training and Consulting 17.26.2.2. System Integration and Testing 17.26.2.3. Support and Maintenance 17.27. Rest of South America AI in Fashion Market Forecast, By Applications 17.27.1. Product Recommendation 17.27.2. Product Search and Discovery 17.27.3. Supply Chain Management and Demand Forecasting 17.27.4. Creative Designing and Trend Forecasting 17.27.5. Customer Relationship Management 17.27.6. Virtual Assistants 17.27.7. Others (Fraud detection, fabric waste reduction, and price optimization) 17.28. Rest of South America AI in Fashion Market Forecast, By Deployment Mode 17.28.1. Cloud 17.28.2. On-premises 17.29. Rest of South America AI in Fashion Market Forecast, By Category 17.29.1. Apparel 17.29.2. Accessories 17.29.3. Footwear 17.29.4. Beauty and Cosmetics 17.29.5. Jewelry and Watches 17.29.6. Others (eyewear, home decor) 17.30. Rest of South America AI in Fashion Market Forecast, By End-User 17.30.1. Fashion Designers 17.30.2. Fashion Stores 17.31. South America AI in Fashion Market Attractiveness Analysis 17.31.1. By Components 17.31.2. By Applications 17.31.3. By Deployment Mode 17.31.4. By Category 17.31.5. By End-User 17.32. PEST Analysis 17.33. Key Trends 17.34. Key Developments 18. Company Profiles 18.1. Market Share Analysis, by Company 18.2. Competition Matrix 18.2.1. Competitive Benchmarking of key players by price, presence, market share, Applications and R&D investment 18.2.2. New Product Launches and Product Enhancements 18.2.3. Market Consolidation 18.2.3.1. M&A by Regions, Investment and Applications 18.2.3.2. M&A Key Players, Forward Integration and Backward Integration 18.3. Company Profiles: Key Players 18.3.1. Microsoft 18.3.1.1. Company Overview 18.3.1.2. Financial Overview 18.3.1.3. Product Portfolio 18.3.1.4. Business Strategy 18.3.1.5. Recent Developments 18.3.1.6. Manufractring Footprint 18.3.2. IBM 18.3.3. Google 18.3.4. AWS 18.3.5. SAP 18.3.6. Facebook 18.3.7. Adobe 18.3.8. Oracle 18.3.9. Catchoom 18.3.10. Huawei 18.3.11. Vue.AI 18.3.12. Heuritech 18.3.13. Wide Eyes 18.3.14. Findmine 18.3.15. Intelistyle 18.3.16. Lily AI 18.3.17. Pttrns.AI 18.3.18. Syte 18.3.19. Mode.AI 18.3.20. Stitch Fix 18.3.21. Alibaba. 18.3.22. Amazon. 18.3.23. H&M. 18.3.24. Tommy Hilfiger. 18.3.25. ASOS. 19. Primary Key Insights

About This Report

Report ID 54494
Category Information Technology & Telecommunication
Published Date March 2020
Updated Date April 2021
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