Artificial Intelligence In Fashion Market Trends & Growth by 2027

Artificial Intelligence In Fashion Market to 2027 - Global Analysis and Forecasts by Offerings (Solutions and Services); Deployment (On-premise and Cloud-based); Application (Product Recommendation, Virtual Assistant, Product Search and Discovery, Creative Designing and Trend Forecasting, Customer Relationship Management, and Others); End-User Industry (Apparel, Accessories, Cosmetics, and Others)

Publication Month : Oct 2019

  • Report Code : TIPRE00007131
  • Category : Technology, Media and Telecommunications
  • Status : Published
  • No. of Pages : 214
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The Artificial Intelligence in fashion market is anticipated to account to US$ 270.0 Mn in 2018 and is expected to grow at a CAGR of 36.9% during the forecast period 2019 – 2027, to account to US$ 4,391.7 Mn by 2027.

The availability of a large amount of data originating from different data sources is one of the key factors driving the growth of AI technology across the fashion industry. The proliferation of easy availability of the internet, smart devices, the advancement of technology, and others are some of the major reasons for the exponential increase in data generation. The RFID and Bluetooth implementation to locate products and gather information is also increasing exponentially in the fashion industry. Moreover, the voice-enabled chatbots such as Amazon Alexa and Apple Siri are continuously generating an enormous amount of data every second. By using these conversational solutions, fashion brands collect data by asking customer’s requirements, trends, and diving deeper into the purchase pattern.

This evolution in digitization presents a huge opportunity for fashion businesses to utilize the huge volumes of user/process data to gain useful insights. The paradigm shifts of fashion companies embracing digitalization has reaped greater benefits for the enterprises and resulted in more revenue generation opportunities. Also, with the advancement in computing and storage technology, computing power has increased multi-fold during the last decade. This has created new opportunities for managing and computing the big sets of data, and when coupled with AI technology, useful business and customer insights can be gained. With AI applications like machine learning and deep learning, fashion companies have a tremendous opportunity to harness the data available for useful insights and thus increasing their revenue. 

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Artificial Intelligence In Fashion Market: Strategic Insights

artificial-intelligence-in-fashion-market
Market Size Value inUS$ 270.0 Million in 2018
Market Size Value byUS$ 4,391.7 Million by 2027
Growth rateCAGR of 36.9% from 2019-2027
Forecast Period2019-2027
Base Year2019
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Lucrative Regions for Artificial Intelligence in Fashion Market

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Market Insights

Introduction of Natural Language Programming (NLP) to fashion industry are huge opportunity for AI in fashion vendors

NLP offers high-efficiency human experience and makes highly interactive chatbots. Vendors have a huge opportunity to improve their services by implementing NLP to its solutions. In the fashion industry, and NLP has capabilities to offer great help to fashion and apparel websites by filtering the majority of customer’s issues and send it to different customers to clarify the issues.

Business is taking efforts for better understanding and implementation of NLP. NLP’s are capable of handling the number of systems that work together to handle end-to-end interactions between machines and humans. This technology enables users to interact more naturally. Business is making huge investments in developing NLP enabled solutions for the fashion industry. For instance, Zalando SE, Germany based fashion company implemented the NLP model to its website based on PyTorch and Python.

Offering Market Insights

The AI in fashion market by offering is segmented into solutions and services. Among the list of emerging technologies including, AI, IoT, blockchain, AR/VR, and 3D printing, the artificial intelligence has been at the forefront of disruption for every industry. Perhaps one of the most noticeable ways the fashion and technology have been incorporated is the capability to turn a diverse set of data into enriching, engaging information. Cognitive computing and artificial intelligence are increasing agility for retailers. Significant investments are being made by some of the leading IT companies as well as fashion retailers. For instance, Oracle Corporation under its software, Oracle Retail, invests significant resources and time to continuously advance its retail science portfolio. This enables retailers to better forestall rapid changes in customer preference, allowing them to simplify optimal price and promotion across a rising number of combinations available to retailers and their consumers.

Artificial Intelligence in Fashion Market, by Deployment Model – 2018 and 2027

Artificial Intelligence in Fashion Market, by Deployment Model – 2018 and 2027
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Deployment Market Insight

The AI in fashion market by deployment type is segmented into on-premise and cloud. The companies and fashion brands those are planning to make substantial investments in artificial intelligence are expected to swiftly shift towards the modern platform by adopting either on-premise or cloud based solutions. The adoption of on-premise or cloud based AI solutions in fashion industry is also highly influenced by the willingness of the fashion companies or brands to switch to novel vendors offering advanced AI-based solutions. Apart from the large enterprises, various SMEs around the world are also adopting the AI-based solutions. The global AI in fashion market is experiencing a paradigm shift from traditional on-premise deployment to cloud-based deployments in the current scenario. This trend is predominantly driven by the presence of new category of cloud only solutions, which help in minimizing integration complexities and installation costs with quick setup. It was also being observed that not only the software providers in the global market since past 15 years are cloud-based, but there also are some on-premises providers, which are facilitating certain form of cloud deployed AI-based software for fashion industry. The increasing number of attractive cloud-based solutions for fashion industry also a revenue stimulating factor prevailing in the current market scenario. Further, partnerships and collaborations among the fashion brands/retailers and technology companies are driving the market for cloud-based services.

Application Market Insight

The fashion industry is implementing AI to attain competitiveness. Brands of all sizes, as well as specialties, are leveraging technology to comprehend customers better. A huge volume of data is generated by several social media interactions, mobile platforms, and e-commerce transactions in the fashion business, which offers an opportunity to the practitioners and researchers to analyse and develop systems capable of understanding consumer behaviours and tailoring the online platform services by efficient use of AI.

Today’s computer systems are far more capable of merely performing tasks that were once performed by humans owing to increased innovation and processing power in the development of the algorithm. The diversity and volume of the data collected have increased, which helps in better learning and smarter decision making with the help of AI.

Global Artificial Intelligence in Fashion Segments:

Artificial Intelligence in Fashion Market – By Offerings

  • Solutions
  • Services

Artificial Intelligence in Fashion Market – By Deployment

  • On-premise
  • Cloud-based

Artificial Intelligence in Fashion Market – By Application

  • Product Recommendation
  • Virtual Assistant
  • Product Search and Discovery
  • Creative Designing and Trend Forecasting
  • Customer Relationship Management
  • Others

Artificial Intelligence in Fashion Market – By End-User Industry

  • Apparel
  • Accessories
  • Cosmetics
  • Others

Artificial Intelligence in Fashion Market – By Geography

  • North America

    • U.S.
    • Canada
    • Mexico
  • Europe

    • France
    • Germany
    • Italy
    • Spain
    • UK
    • Rest of Europe
  • Asia Pacific (APAC)

    • Australia
    • China
    • India
    • Japan
    • Rest of APAC
  • Middle East & Africa (MEA)

    • Saudi Arabia
    • UAE
    • South Africa
    • Rest of MEA
  • South America (SAM)

    • Brazil
    • Rest of SAM

Companies

  • Adobe Inc.
  • Alphabet Inc. (Google)
  • Amazon.com, Inc.
  • Catchoom
  • Facebook Inc.
  • Huawei Technologies Co., Ltd.
  • IBM Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • SAP SE
Report Coverage
Report Coverage

Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends

Segment Covered
Segment Covered

Offerings ; Deployment ; Application ; End-User Industry

Regional Scope
Regional Scope

North America, Europe, Asia Pacific, Middle East & Africa, South & Central America

Country Scope
Country Scope

US, Canada, Mexico, UK, Germany, Spain, Italy, France, India, China, Japan, South Korea, Australia, UAE, Saudi Arabia, South Africa, Brazil, Argentina

The List of Companies - Artificial Intelligence In Fashion Market

  1. Adobe Inc.
  2. Amazon Web Services, Inc.
  3. Catchoom Technologies S.L.
  4. Facebook, Inc.
  5. Google LLC
  6. Huawei Technologies Co., Ltd.
  7. IBM Corporation
  8. Microsoft Corporation
  9. Oracle Corporation
  10. SAP SE

The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.

  1. Data Collection and Secondary Research:

As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.

Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.

  1. Primary Research:

The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.

For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.

A typical research interview fulfils the following functions:

  • Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
  • Validates and strengthens in-house secondary research findings
  • Develops the analysis team’s expertise and market understanding

Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:

  • Industry participants: VPs, business development managers, market intelligence managers and national sales managers
  • Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.

Below is the breakup of our primary respondents by company, designation, and region:

Research Methodology

Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.

  1. Data Analysis:

Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.

  • 3.1 Macro-Economic Factor Analysis:

We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.

  • 3.2 Country Level Data:

Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.

  • 3.3 Company Profile:

The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.

  • 3.4 Developing Base Number:

Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.

  1. Data Triangulation and Final Review:

The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.

We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.

We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.

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