Dublin, Oct. 23, 2019 (GLOBE NEWSWIRE) -- The "AI in Fashion Market by Component (Solutions and Services), Application (Product Recommendation, Product Search & Discovery, and CRM), Deployment Mode, Category, (Apparel, Accessories, and Beauty & Cosmetics), End User, and Region - Global Forecast to 2024" report has been added to ResearchAndMarkets.com's offering.
The global AI in fashion market is expected to grow from USD 228 million in 2019 to USD 1,260 million by 2024, at a CAGR of 40.8% during the forecast period.
The AI in fashion market revenue is classified primarily into revenues from solutions and services. Solution revenue is associated with the platforms and software tools, while services' revenue is associated with training and consulting system integration and testing, and support and maintenance services. The market is also segmented based on component, deployment mode, applications, category, end-user, and region.
The AI in fashion market comprises major solution providers such as Microsoft (US), IBM (US), Google (US), AWS (US), SAP (Germany), Facebook (US), Adobe (US), Oracle (US), Catchoom (Spain), Huawei (China), Vue.ai (US), Heuritech (France), Wide Eyes (Spain), FINDMINE (US), Intelistyle (England), Lily AI (US), Pttrns.ai (Netherlands), Syte (Israel), mode.ai (US), and Stitch Fix (US). The study includes an in-depth competitive analysis of these key players in the AI in the fashion market with their company profiles, recent developments, and key market strategies.
Customer's demand for a personalized experience to drive the adoption of AI in fashion across end-users
Major growth factors for the market include increasing need for inventory management, customer's demand for a personalized experience, and the growing influence of social media in the fashion industry. However, integration with the legacy system would limit market growth.
Fashion designer end-user segment to grow at a higher CAGR during the forecast period
Based on end-user, AI in the fashion market is divided into fashion designers and fashion stores. Fashion stores comprise online and offline brand stores.
Popular fashion designers are using AI solutions to have an in-depth understanding of people, culture, and their anthropological aspect to bring new designs to the market. Moreover, with the help of AI system designers can listen to social media's trending gossips on current fashion inclination, colors, patterns, and styles that help them launch new products as per market demand.
The companies such as Amazon and Glitch have launched an AI-powered solution that can curate current fashion data and design new stylish clothing similar to human designs. The designers such as Falguni and Shane Peacock are using AI-powered solutions to introduce their latest collection designed by AI solutions.
Cloud deployment mode to hold a higher market share during the forecast period
Organizations have been gradually recognizing the importance of AI in the fashion industry and have started deploying them as per their needs including inventory management, designing, manufacturing, and sales and marketing. Most of the SMEs are adopting SDKs, APIs, and ML models that can be easily deployed on the cloud and does not need infrastructure in the premises. Due to ease of use and low-cost SMEs are moving on cloud deployment compared to on-premises.
AI in the fashion market in Asia Pacific (APAC) to grow at the highest CAGR during the forecast period
The high growth in the APAC market is attributed to the significant growth potential, increasing social media adoption, and rising digitalization with an increasing need to remain globally competitive. Furthermore, the inclination of APAC countries toward emerging technologies such as 3G and 4G is also expected to fuel the growth of the AI in the fashion market.
However, the lack of technological awareness, privacy issues, and limited technical expertise in advanced technologies remain significant hurdles in the AI in fashion adoption across the region. The cloud-based AI in fashions presents an optimal solution for these countries by minimizing integration complexities and installation costs.
Key benefits of the report:
- The report would help the market leaders/new entrants in the market with the information on the closest approximations of the revenue numbers for the overall AI in the fashion market and the subsegments.
- The report would help stakeholders understand the competitive landscape and gain insights to better position their businesses and plan suitable go-to-market strategies.
- The report also helps stakeholders understand the pulse of the market and provides them with information on the key market drivers, restraints, challenges, and opportunities.
Key Topics Covered
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities in the AI in Fashion Market
4.2 Market Top 4 Categories
4.3 Market Top 3 Applications and Regions
4.4 Market By Application
5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Customer Demand for Personalized Experience
5.2.1.2 Increasing Need for Inventory Management
5.2.1.3 Growing Influence of Social Media on the Fashion Industry
5.2.2 Restraints
5.2.2.1 Integration With Legacy Systems
5.2.3 Opportunities
5.2.3.1 Identifying Future Fashion Trends By Analyzing Customer Buying Behavior
5.2.3.2 Growth of Fast Fashion Retail to Boost the Adoption of AI in the Fashion Industry
5.2.4 Challenges
5.2.4.1 Incorporating Cultural Differentiation in Fashion Trends
5.3 Technologies That Impact Fashion Industry
5.3.1 Machine Learning
5.3.2 Deep Learning
5.3.3 Natural Language Processing
5.3.4 Augmented Reality/Virtual Reality
5.4 Use Cases
6 AI in Fashion Market By Component
6.1 Introduction
6.2 Solutions
6.2.1 Software Tools
6.2.1.1 Growing Need for specific Solutions for Every Application to Drive the Adoption of Software Tools During the Forecast Period
6.2.2 Platforms
6.2.2.1 Increasing Need for Comprehensive AI Solutions Across Fashion Industry to Drive the Adoption of AI Platforms
6.3 Services
6.3.1 Training and Consulting
6.3.1.1 Need for Rapid Adoption and Optimization of AI Solutions to Drive the Training and Consulting Services Segment
6.3.2 System Integration and Testing
6.3.2.1 Need to Ensure Proper Integration of Existing Infrastructure With AI Fashion Solutions to Drive the Demand for System Integration and Testing Services
6.3.3 Support and Maintenance
6.3.3.1 Complexity of Operations and Need for Regular Assistance During the Software Life Cycle to Foster the Growth of Support and Maintenance Services
7 AI in Fashion Market By Deployment Mode
7.1 Introduction
7.2 Cloud
7.2.1 Ease of Deployment and Improved Scalability and Integration to Drive the Adoption of Cloud-Based AI Solutions in Fashion Industry
7.3 On-Premises
7.3.1 Advantages of Data Privacy and Security to Accelerate the Growth of the On-Premises Deployment Mode
8 AI in Fashion Market By Application
8.1 Introduction
8.2 Product Recommendation
8.2.1 Ability to Effectively Engage Customers Across Online and Offline Channels to Contribute to the Growth of the Segment
8.3 Product Search and Discovery
8.3.1 Growing Need to Provide Seamless Shopping Experiences to Increase the Adoption of AI-Powered Technologies
8.4 Supply Chain Management and Demand Planning
8.4.1 Need to Streamline Supply Chain Operations and Gain A Competitive Edge in the Market to Drive the Adoption of AI in Fashion
8.5 Creative Designing and Trend Forecasting
8.5.1 Need for Quality Insights Into Ongoing Fashion Trends to Drive the Creative Designing and Trend Forecasting Application
8.6 Customer Relationship Management
8.6.1 Fashion Retailers to Adopt AI Solutions to Better Analyze Sale Prospects
8.7 Virtual Assistant
8.7.1 Virtual Assistant to Play A Critical Role in Developing Effective Communication Between Fashion Brands and Customers
8.8 Others
9 AI in Fashion Market By Category
9.1 Introduction
9.2 Apparel
9.2.1 Rapid Technological Changes to Drive the Adoption of AI Fashion Solution to Provide Style Recommendations
9.3 Accessories
9.3.1 Brands to Adopt ML Technologies to Predict Purchase Patterns
9.4 Footwear
9.4.1 Footwear Brands to Adopt AI and ML Technologies to Deliver Personalized Customer Experience
9.5 Beauty and Cosmetics
9.5.1 Beauty and Cosmetics Brands to Use AI and ML Technologies to Helps Shoppers Find Appropriate Products
9.6 Jewelry and Watches
9.6.1 Jewelry and Watches Brands to Leverage AI and ML Technologies to Identify Latest Consumer Trends
9.7 Others
10 AI in Fashion Market By End User
10.1 Introduction
10.2 Fashion Designers
10.2.1 AI Technologies to Assist Fashion Designers Enhance Their Creative Designing Process
10.3 Fashion Stores
10.3.1 Fashion Brands to Adopt AI Technologies to Gain Competitive Advantage in the Market
11 AI in Fashion Market By Region
11.1 Introduction
11.2 North America
11.2.1 United States
11.2.1.1 Rapid Growth of Technologies and Infrastructures to Increase the Adoption of AI-Based Solutions Among the Fashion Industry
11.2.2 Canada
11.2.2.1 Growing Technological Advancements in Canada to Boost the Growth of AI Solutions Among Fashion Retailers
11.3 Europe
11.3.1 United Kingdom
11.3.1.1 Rising Online Shopping to Drive the Market Growth in the UK
11.3.2 Germany
11.3.2.1 Numerous Expansion Opportunities for Fashion Brands in Germany to Drive the Growth of AI in Fashion Solutions
11.3.3 France
11.3.3.1 Increasing Use of Fashion and Lifestyle Products to Create A Potential Market for AI in Fashion in France
11.3.4 Rest of Europe
11.4 Asia Pacific
11.4.1 China
11.4.1.1 Increasing Technological Developments in China to Boost the Adoption of AI Technology Among Fashion Brands
11.4.2 India
11.4.2.1 Growing Fashion Trend of Wearable Tech to Boost the Adoption of AI Technology in India
11.4.3 Japan
11.4.3.1 Increasing Need for Automation in Japan to Drive the Growth of AI in Inventory and Supply Chain Management in Fashion Retail
11.4.4 Australia
11.4.4.1 Increasing Customer Expectations to Drive the Fashion Retail Investments in Advanced Technologies in Australia
11.4.5 Rest of Asia Pacific
11.5 Middle East and Africa
11.5.1 United Arab Emirates
11.5.1.1 Changing Customer Expectations and Shorter Strategy Cycle to Enhance the Adoption of Digital and AI Technology Across the UAE
11.5.2 Saudi Arabia
11.5.2.1 Gradual Adoption of Fashionable Clothing to Drive the Adoption the AI in Fashion Retail
11.5.3 South Africa
11.5.3.1 Lack of Technological Skills and Poor Data Quality to Restrain the Growth of AI Among South African Fashion Retailers
11.5.4 Rest of Middle East and Africa
11.6 Latin America
11.6.1 Brazil
11.6.1.1 Growing eCommerce Across Brazil to Boost the Adoption of AI in the Fashion Industry
11.6.2 Mexico
11.6.2.1 Growing Developments in Computer Vision, ML, and NLP to Provide Opportunities for Fashion Retailers for Adopting Advanced Technologies in Mexico
11.6.3 Argentina
11.6.3.1 Growing Demand for Luxurious Goods and Need for Streamlined Supply Chain to Enhance the Adoption of AI in Argentina
11.6.4 Rest of Latin America
12 Competitive Landscape
12.1 Introduction
12.2 Competitive Leadership Mapping
12.2.1 Progressive Companies
12.2.2 Responsive Companies
12.2.3 Dynamic Companies
12.2.4 Starting Blocks
13 Company Profiles
13.1 Introduction
13.2 Microsoft
13.3 IBM
13.4 Google
13.5 AWS
13.6 SAP
13.7 Facebook
13.8 Adobe
13.9 Oracle
13.10 Catchoom
13.11 Huawei
13.12 Vue.AI
13.13 Heuritech
13.14 Wide Eyes
13.15 Findmine
13.16 Intelistyle
13.17 Lily AI
13.18 Pttrns.AI
13.19 Syte
13.20 Mode.AI
13.21 Stitch Fix
For more information about this report visit https://www.researchandmarkets.com/r/egc08y
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