AI in Fashion Market Size to Reach USD 49.07 Billion by 2033

The AI in fashion market size is poised to grow by USD 49.07 billion by 2033 from USD 1.58 billion in 2023, exhibiting a CAGR of 41% during the forecast period 2024-2033.

Key Points

• North America led the AI in the fashion market with the largest market size in 2023.
• Asia Pacific is expected to witness the fastest growth in the market during the forecast period.
• By component, the solution segment dominated the market in 2023.
• By deployment, the cloud segment is projected to witness the fastest rate of expansion during the forecast period.
• By application, the product recommendation segment dominated the market in 2023.
• By application, the product search and discovery segment is expected to witness the fastest rate of expansion during the forecast period.
• By type, the apparel segment dominated the market with the largest share in 2023.
• By type, the accessories segment is expected to grow at a significant rate during the forecast period.
• By end-user, the fashion designers segment led the market in 2023.

Precedence Research has conducted a comprehensive market study that provides valuable insights into the performance of the market during the forecast period. The study identifies significant trends that are shaping the growth of the AI in fashion market. In this recently published report, essential dynamics such as drivers, restraints, and opportunities are highlighted for both established market players and emerging participants involved in production and supply.

To begin with, the AI in fashion Market report features an executive summary that offers a concise overview of the marketplace. It outlines the key players and industry categories expected to have an impact on the market in the coming years. The executive summary provides an unbiased summary of the market.

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AI in Fashion Market Scope

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The empirical study on the global AI in fashion market primarily focuses on the drivers in subsequent sections. It demonstrates how changing demographics are projected to influence the supply and demand dynamics in the AI in fashion Market. Our market report for the AI in fashion market also delves into the significant rules and regulations that are likely to impact the future growth of this sector. Moreover, in order to comprehend the underlying demand factors, industry experts have provided insights into its fundamental origins.

AI in Fashion Market Companies

• Microsoft Corporation
• IBM Corporation
• Google Inc.
• Amazon Web Service Inc.
• SAP AG
• Lily AI
• Oracle Corporation
• Catchoom
• Heuritch

Data Sources and Methodology

To gather comprehensive insights on the Global AI in fashion Market, we relied on a range of data sources and followed a well-defined methodology. Our approach involved interactions with industry experts and key stakeholders across the market’s value chain, including management organizations, processing organizations, and analytics service providers.

We followed a rigorous data analysis process to ensure the quality and credibility of our research. The gathered information was carefully evaluated, and relevant quantitative data was subjected to statistical analysis. By employing robust analytical techniques, we were able to derive meaningful insights and present a comprehensive overview of the Global AI in fashion Market.

The most resonating, simple, genuine, and important causes because of which you must decide to buy the AI in fashion market report exclusively from precedence research

• The research report has been meticulously crafted to provide comprehensive knowledge on essential marketing strategies and a holistic understanding of crucial marketing plans spanning the forecasted period from 2024 to 2033.

Key Features of the Report:

• Comprehensive Coverage: The report extensively encompasses a detailed explanation of highly effective analytical marketing methods applicable to companies across all industry sectors.
• Decision-Making Enhancement: It outlines a concise overview of the decision-making process while highlighting key techniques to enhance it, ensuring favorable business outcomes in the future.
• Articulated R&D Approach: The report presents a well-defined approach to conducting research and development (R&D) activities, enabling accurate data acquisition on current and future marketing conditions.

Market Segmentation:

By Component

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

By Deployment

• Product Recommendation
• Product Search and Discovery
• Supply Chain Management and Demand Forecasting
• Creative Designing and Trend Forecasting
• Customer Relationship Management
• Virtual Assistants

By Application

• Cloud
• On-premises

By Type

• Apparel
• Accessories
• Footwear
• Beauty and Cosmetics
• Jewelry and Watches

By End-User

• Fashion Designers
• Fashion Stores

By Geography

• North America
• Europe
• Asia-Pacific
• Latin America
• Middle East and Africa

Reasons to Consider Purchasing the Report:

• Enhance your market research capabilities by accessing this comprehensive and precise report on the global AI in fashion market.
• Gain a thorough understanding of the overall market landscape and be prepared to overcome challenges while ensuring robust growth.
• Benefit from in-depth research and analysis of the latest trends shaping the global AI in fashion market.
• Obtain detailed insights into evolving market trends, current and future technologies, and strategic approaches employed by key players in the global AI in fashion market.
• Receive valuable recommendations and guidance for both new entrants and established players seeking further market expansion.
• Discover not only the cutting-edge technological advancements in the global AI in fashion market but also the strategic plans of industry leaders.

Table of Content

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology (Premium Insights)

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on AI in Fashion Market 

5.1. COVID-19 Landscape: AI in Fashion Industry Impact

5.2. COVID 19 – Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global AI in Fashion Market, By Component

8.1. AI in Fashion Market, by Component, 2024-2033

8.1.1. Solution

8.1.1.1. Market Revenue and Forecast (2021-2033)

8.1.2. Software Tools

8.1.2.1. Market Revenue and Forecast (2021-2033)

8.1.3. Platforms

8.1.3.1. Market Revenue and Forecast (2021-2033)

8.1.4. Services

8.1.4.1. Market Revenue and Forecast (2021-2033)

8.1.5. Training and Consulting

8.1.5.1. Market Revenue and Forecast (2021-2033)

8.1.6. System Integration and Testing

8.1.6.1. Market Revenue and Forecast (2021-2033)

8.1.7. Support and Maintenance

8.1.7.1. Market Revenue and Forecast (2021-2033)

Chapter 9. Global AI in Fashion Market, By Deployment

9.1. AI in Fashion Market, by Deployment, 2024-2033

9.1.1. Product Recommendation

9.1.1.1. Market Revenue and Forecast (2021-2033)

9.1.2. Product Search and Discovery

9.1.2.1. Market Revenue and Forecast (2021-2033)

9.1.3. Supply Chain Management and Demand Forecasting

9.1.3.1. Market Revenue and Forecast (2021-2033)

9.1.4. Creative Designing and Trend Forecasting

9.1.4.1. Market Revenue and Forecast (2021-2033)

9.1.5. Customer Relationship Management

9.1.5.1. Market Revenue and Forecast (2021-2033)

9.1.6. Virtual Assistants

9.1.6.1. Market Revenue and Forecast (2021-2033)

Chapter 10. Global AI in Fashion Market, By Application 

10.1. AI in Fashion Market, by Application, 2024-2033

10.1.1. Cloud

10.1.1.1. Market Revenue and Forecast (2021-2033)

10.1.2. On-premises

10.1.2.1. Market Revenue and Forecast (2021-2033)

Chapter 11. Global AI in Fashion Market, By Type

11.1. AI in Fashion Market, by Type, 2024-2033

11.1.1. Apparel

11.1.1.1. Market Revenue and Forecast (2021-2033)

11.1.2. Accessories

11.1.2.1. Market Revenue and Forecast (2021-2033)

11.1.3. Footwear

11.1.3.1. Market Revenue and Forecast (2021-2033)

11.1.4. Beauty and Cosmetics

11.1.4.1. Market Revenue and Forecast (2021-2033)

11.1.5. Jewelry and Watches

11.1.5.1. Market Revenue and Forecast (2021-2033)

Chapter 12. Global AI in Fashion Market, By End-User

12.1. AI in Fashion Market, by End-User, 2024-2033

12.1.1. Fashion Designers

12.1.1.1. Market Revenue and Forecast (2021-2033)

12.1.2. Fashion Stores

12.1.2.1. Market Revenue and Forecast (2021-2033)

Chapter 13. Global AI in Fashion Market, Regional Estimates and Trend Forecast

13.1. North America

13.1.1. Market Revenue and Forecast, by Component (2021-2033)

13.1.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.1.3. Market Revenue and Forecast, by Application (2021-2033)

13.1.4. Market Revenue and Forecast, by Type (2021-2033)

13.1.5. Market Revenue and Forecast, by End-User (2021-2033)

13.1.6. U.S.

13.1.6.1. Market Revenue and Forecast, by Component (2021-2033)

13.1.6.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.1.6.3. Market Revenue and Forecast, by Application (2021-2033)

13.1.6.4. Market Revenue and Forecast, by Type (2021-2033)

13.1.6.5. Market Revenue and Forecast, by End-User (2021-2033)

13.1.7. Rest of North America

13.1.7.1. Market Revenue and Forecast, by Component (2021-2033)

13.1.7.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.1.7.3. Market Revenue and Forecast, by Application (2021-2033)

13.1.7.4. Market Revenue and Forecast, by Type (2021-2033)

13.1.7.5. Market Revenue and Forecast, by End-User (2021-2033)

13.2. Europe

13.2.1. Market Revenue and Forecast, by Component (2021-2033)

13.2.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.2.3. Market Revenue and Forecast, by Application (2021-2033)

13.2.4. Market Revenue and Forecast, by Type (2021-2033)

13.2.5. Market Revenue and Forecast, by End-User (2021-2033)

13.2.6. UK

13.2.6.1. Market Revenue and Forecast, by Component (2021-2033)

13.2.6.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.2.6.3. Market Revenue and Forecast, by Application (2021-2033)

13.2.7. Market Revenue and Forecast, by Type (2021-2033)

13.2.8. Market Revenue and Forecast, by End-User (2021-2033)

13.2.9. Germany

13.2.9.1. Market Revenue and Forecast, by Component (2021-2033)

13.2.9.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.2.9.3. Market Revenue and Forecast, by Application (2021-2033)

13.2.10. Market Revenue and Forecast, by Type (2021-2033)

13.2.11. Market Revenue and Forecast, by End-User (2021-2033)

13.2.12. France

13.2.12.1. Market Revenue and Forecast, by Component (2021-2033)

13.2.12.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.2.12.3. Market Revenue and Forecast, by Application (2021-2033)

13.2.12.4. Market Revenue and Forecast, by Type (2021-2033)

13.2.13. Market Revenue and Forecast, by End-User (2021-2033)

13.2.14. Rest of Europe

13.2.14.1. Market Revenue and Forecast, by Component (2021-2033)

13.2.14.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.2.14.3. Market Revenue and Forecast, by Application (2021-2033)

13.2.14.4. Market Revenue and Forecast, by Type (2021-2033)

13.2.15. Market Revenue and Forecast, by End-User (2021-2033)

13.3. APAC

13.3.1. Market Revenue and Forecast, by Component (2021-2033)

13.3.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.3.3. Market Revenue and Forecast, by Application (2021-2033)

13.3.4. Market Revenue and Forecast, by Type (2021-2033)

13.3.5. Market Revenue and Forecast, by End-User (2021-2033)

13.3.6. India

13.3.6.1. Market Revenue and Forecast, by Component (2021-2033)

13.3.6.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.3.6.3. Market Revenue and Forecast, by Application (2021-2033)

13.3.6.4. Market Revenue and Forecast, by Type (2021-2033)

13.3.7. Market Revenue and Forecast, by End-User (2021-2033)

13.3.8. China

13.3.8.1. Market Revenue and Forecast, by Component (2021-2033)

13.3.8.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.3.8.3. Market Revenue and Forecast, by Application (2021-2033)

13.3.8.4. Market Revenue and Forecast, by Type (2021-2033)

13.3.9. Market Revenue and Forecast, by End-User (2021-2033)

13.3.10. Japan

13.3.10.1. Market Revenue and Forecast, by Component (2021-2033)

13.3.10.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.3.10.3. Market Revenue and Forecast, by Application (2021-2033)

13.3.10.4. Market Revenue and Forecast, by Type (2021-2033)

13.3.10.5. Market Revenue and Forecast, by End-User (2021-2033)

13.3.11. Rest of APAC

13.3.11.1. Market Revenue and Forecast, by Component (2021-2033)

13.3.11.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.3.11.3. Market Revenue and Forecast, by Application (2021-2033)

13.3.11.4. Market Revenue and Forecast, by Type (2021-2033)

13.3.11.5. Market Revenue and Forecast, by End-User (2021-2033)

13.4. MEA

13.4.1. Market Revenue and Forecast, by Component (2021-2033)

13.4.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.4.3. Market Revenue and Forecast, by Application (2021-2033)

13.4.4. Market Revenue and Forecast, by Type (2021-2033)

13.4.5. Market Revenue and Forecast, by End-User (2021-2033)

13.4.6. GCC

13.4.6.1. Market Revenue and Forecast, by Component (2021-2033)

13.4.6.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.4.6.3. Market Revenue and Forecast, by Application (2021-2033)

13.4.6.4. Market Revenue and Forecast, by Type (2021-2033)

13.4.7. Market Revenue and Forecast, by End-User (2021-2033)

13.4.8. North Africa

13.4.8.1. Market Revenue and Forecast, by Component (2021-2033)

13.4.8.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.4.8.3. Market Revenue and Forecast, by Application (2021-2033)

13.4.8.4. Market Revenue and Forecast, by Type (2021-2033)

13.4.9. Market Revenue and Forecast, by End-User (2021-2033)

13.4.10. South Africa

13.4.10.1. Market Revenue and Forecast, by Component (2021-2033)

13.4.10.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.4.10.3. Market Revenue and Forecast, by Application (2021-2033)

13.4.10.4. Market Revenue and Forecast, by Type (2021-2033)

13.4.10.5. Market Revenue and Forecast, by End-User (2021-2033)

13.4.11. Rest of MEA

13.4.11.1. Market Revenue and Forecast, by Component (2021-2033)

13.4.11.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.4.11.3. Market Revenue and Forecast, by Application (2021-2033)

13.4.11.4. Market Revenue and Forecast, by Type (2021-2033)

13.4.11.5. Market Revenue and Forecast, by End-User (2021-2033)

13.5. Latin America

13.5.1. Market Revenue and Forecast, by Component (2021-2033)

13.5.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.5.3. Market Revenue and Forecast, by Application (2021-2033)

13.5.4. Market Revenue and Forecast, by Type (2021-2033)

13.5.5. Market Revenue and Forecast, by End-User (2021-2033)

13.5.6. Brazil

13.5.6.1. Market Revenue and Forecast, by Component (2021-2033)

13.5.6.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.5.6.3. Market Revenue and Forecast, by Application (2021-2033)

13.5.6.4. Market Revenue and Forecast, by Type (2021-2033)

13.5.7. Market Revenue and Forecast, by End-User (2021-2033)

13.5.8. Rest of LATAM

13.5.8.1. Market Revenue and Forecast, by Component (2021-2033)

13.5.8.2. Market Revenue and Forecast, by Deployment (2021-2033)

13.5.8.3. Market Revenue and Forecast, by Application (2021-2033)

13.5.8.4. Market Revenue and Forecast, by Type (2021-2033)

13.5.8.5. Market Revenue and Forecast, by End-User (2021-2033)

Chapter 14. Company Profiles

14.1. Microsoft Corporation

14.1.1. Company Overview

14.1.2. Product Offerings

14.1.3. Financial Performance

14.1.4. Recent Initiatives

14.2. IBM Corporation

14.2.1. Company Overview

14.2.2. Product Offerings

14.2.3. Financial Performance

14.2.4. Recent Initiatives

14.3. Google Inc.

14.3.1. Company Overview

14.3.2. Product Offerings

14.3.3. Financial Performance

14.3.4. Recent Initiatives

14.4. Amazon Web Service Inc.

14.4.1. Company Overview

14.4.2. Product Offerings

14.4.3. Financial Performance

14.4.4. Recent Initiatives

14.5. SAP AG

14.5.1. Company Overview

14.5.2. Product Offerings

14.5.3. Financial Performance

14.5.4. Recent Initiatives

14.6. Lily AI

14.6.1. Company Overview

14.6.2. Product Offerings

14.6.3. Financial Performance

14.6.4. Recent Initiatives

14.7. Oracle Corporation

14.7.1. Company Overview

14.7.2. Product Offerings

14.7.3. Financial Performance

14.7.4. Recent Initiatives

14.8. Catchoom

14.8.1. Company Overview

14.8.2. Product Offerings

14.8.3. Financial Performance

14.8.4. Recent Initiatives

14.9. Heuritch

14.9.1. Company Overview

14.9.2. Product Offerings

14.9.3. Financial Performance

14.9.4. Recent Initiatives

Chapter 15. Research Methodology

15.1. Primary Research

15.2. Secondary Research

15.3. Assumptions

Chapter 16. Appendix

16.1. About Us

16.2. Glossary of Terms

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