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

The global AI in fashion market size was estimated to be around US$ 1.58 billion in 2023 and is projected to reach US$ 49.07 billion by 2033, indicating a CAGR of 41% from 2024 to 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.

The market research report on the AI in fashion market provides a comprehensive analysis of various key aspects. It includes the definition, classification, and application of AI in fashion products. The report examines the development trends, competitive landscape, and industrial chain structure within the industry. Furthermore, it presents an overview of the industry, analyzes national policies and planning, and offers insights into the latest market dynamics and opportunities at a global level.

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AI in Fashion Market Scope

Read More: IoT Sensors Market Size to Attain USD 312.22 Billion by 2033

The report presents the volume and value-based market size for the base year 2023 and forecasts the market’s growth between 2023 and 2032. It estimates market numbers based on product form and application, providing size and forecast for each application segment in both global and regional markets.

Focusing on the global AI in fashion market, the report highlights its status, future forecasts, growth opportunities, key market players, and key market regions such as the United States, Europe, and China. The study aims to present the development of the AI in fashion market by considering factors like Year-on-Year (Y-o-Y) growth, in addition to Compound Annual Growth Rate (CAGR). This approach enables a better understanding of market certainty and the identification of lucrative opportunities.

Regarding production, the report investigates the capacity, production, value, ex-factory price, growth rate, and market share of major manufacturers, regions, and product types. On the consumption side, the report focuses on the regional consumption of AI in fashion products across different countries and applications.

Buyers of the report gain access to verified market figures, including global market size in terms of revenue and volume. The report provides reliable estimations and calculations for global revenue and volume by product type from 2024 to 2033. It also includes accurate figures for production capacity and production by region during the same period.

The research includes product parameters, production processes, cost structures, and data classified by region, technology, and application. Furthermore, it conducts SWOT analysis and investment feasibility studies for new projects.

This in-depth research report offers valuable insights into the AI in fashion market. It employs an objective and fair approach to analyze industry trends, supporting customer competition analysis, development planning, and investment decision-making. The project received support and assistance from technicians and marketing personnel across various links in the industry chain.

The competitive landscape section of the report provides detailed information on xx market competitors. It includes company overviews, financials, revenue generation, market potential, research and development investments, new market initiatives, global presence, production sites, production capacities, strengths and weaknesses, product launches, product range, and application dominance. However, the data points provided only focus on the companies’ activities related to the AI in fashion market.

Prominent players in the market are expected to face tough competition from new entrants. Key players are targeting acquisitions of startup companies to maintain their dominance. The report

Reasons to Purchase this Report:

• Comprehensive market segmentation analysis incorporating qualitative and quantitative research, considering the impact of economic and policy factors.
• In-depth regional and country-level analysis, examining the demand and supply dynamics that influence market growth.
• Market size in USD million and volume in million units provided for each segment and sub-segment.
• Detailed competitive landscape, including market share of major players, recent projects, and strategies implemented over the past five years.
• Comprehensive company profiles encompassing product offerings, key financial information, recent developments, SWOT analysis, and employed strategies by major market players.

AI in Fashion Market Companies

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

Segments Covered in the Report

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

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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