AI in Fashion Market Growing at a CAGR 40.8% | Key Player Microsoft, IBM, Google, AWS, SAP

AI in Fashion Market Growing at a CAGR 40.8% | Key Player Microsoft, IBM, Google, AWS, SAP

“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).”
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

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 Compound Annual Growth Rate (CAGR) of 40.8% during the forecast period. Major growth factors for the market include customer’s demand for a personalized experience, increasing the need for inventory management and the growing influence of social media in the fashion industry.

Product recommendation application segment to hold the largest market size during the forecast period

With the rising adoption of social media and increasing customer awareness, fashion retailers are trying to provide every best possible service to their customers to enhance trust and hold them for a longer time. Hence, product recommendation has become important to engage customers in an effective way With the growing online sales trends, fashion retailers have started deploying AI-powered recommendation systems in order to make personalized product recommendations based on shoppers buying history, style, taste, and preferences. Therefore, the growth of this application would continue to grow during the forecast period.

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Fashion store end user to hold the largest market size during the forecast period

Fashion stores include online fashion stores and offline fashion stores that have started deploying AI technologies into their operations. The fashion store end-user segment is estimated to account for the largest size during the forecast period. Increasing deployment of cloud-based AI-powered solution by fashion retailers has enabled brands to gain a competitive advantage over other players.

The AI in fashion market comprises leading 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 the key players in the AI in the fashion market with their company profiles, recent developments, and key market strategies. The players in the market have embraced various strategies to expand presence and their market shares. New product launches and enhancements; and partnerships, acquisitions, and collaborations, have been the most adopted strategies by the major players from 2017 to 2019, which helped them innovate on their offerings and broaden their customer base.

Google (US) is among one of the leaders in the AI in the fashion market. It adopts a balanced approach towards growth strategies and continues to enhance its expertise through constant product enhancements, technology acquisitions, collaborations, and partnerships. For instance, in September 2019, Google partnered with the Business of Fashion (BoF) to explore and demonstrate the potential applications of AI in fashion, and begin a dialogue between the industry and one of the global leaders in ML. In its first instance, the partnership would focus on a series of experiments with data sets from BoF’s Fashion Week coverage.

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AWS (US) is another established player in the AI in the fashion market. The company offers cloud-based AI platform for the fashion industry, the solution enables developer and data scientist to build, train, and deploy ML models in a rapid manner. The company has adopted various organic and inorganic strategies to strengthen its product portfolio and expand its presence in various geographical regions. For instance, in May 2019, Amazon SageMaker announced new features to the built-in Object2Vec algorithm. The algorithm is now faster while training deep-learning models. The new features can be accessed as hyperparameters from the Amazon SageMaker console or using the Amazon SageMaker Python API.

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