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Artificial Intelligence In Fashion Market Analysis By Component (Software, Services), By Deployment Mode (Cloud, On-Premises), By Application (Product Design and Development, Supply Chain Management, Customer Service and Experience) & Forecast 2024-2035

  • PUBLISHED ON
  • 21/03/2023
  • NO OF PAGES
  • 266
  • CATEGORY
  • Retails & Consumer
Market Overview:
Artificial Intelligence (AI) has rapidly transformed the fashion industry in recent years. The AI in fashion market is expected to grow significantly in the coming years, driven by the increasing demand for personalized shopping experiences, as well as the need for more sustainable and efficient supply chains. AI in fashion refers to the use of machine learning algorithms and other AI technologies to improve various aspects of the fashion industry, including design, production, supply chain management, and customer experience.

One of the key advantages of AI in fashion is its ability to provide personalized recommendations and improve the customer experience. AI-powered chatbots, for example, can provide customers with personalized recommendations based on their preferences and past purchases. This not only improves the customer experience but also helps retailers to increase sales and improve customer loyalty. Another advantage of AI in fashion is its ability to optimize supply chain management. AI can help retailers to better forecast demand, manage inventory, and reduce waste, leading to more efficient and sustainable supply chains. AI can also help retailers to identify and address quality control issues early on, minimizing product returns and improving customer satisfaction.

AI is being used in various ways in the fashion industry. One of the most common uses is in product recommendation systems, which use machine learning algorithms to analyze customer data and provide personalized product recommendations. AI is also being used in fashion design. For example, designers can use AI-powered tools to generate new design ideas or create customized designs for individual customers. AI can also be used to optimize the production process, by analyzing data to identify the most efficient production methods and reducing waste.

The increasing demand for personalized shopping experiences and efficient supply chain management is driving the adoption of AI in the fashion industry.
The fashion industry is becoming increasingly competitive, with retailers looking for new ways to provide personalized shopping experiences and optimize their supply chains. This is where AI comes in, as it offers various benefits that can help retailers to meet these goals. One of the key driving factors for the adoption of AI in the fashion industry is the need for more personalized shopping experiences. Customers are looking for more customized and relevant product recommendations, and AI-powered recommendation engines can provide this. By analyzing customer data and preferences, AI algorithms can provide personalized product recommendations and styling advice, leading to increased customer satisfaction and loyalty.

Another driving factor is the need for more efficient and sustainable supply chains. Retailers are looking for ways to reduce waste, optimize inventory management, and improve the overall efficiency of their supply chains. AI-powered predictive analytics can help with this, by providing insights into demand forecasting, inventory optimization, and production efficiency. This can lead to more efficient and sustainable supply chains, with reduced waste and improved sustainability. In addition, AI can help fashion retailers to improve their product design and development processes. AI-powered tools can generate new design ideas, create customized designs for individual customers, and optimize the production process. By analyzing data on customer preferences and market trends, AI algorithms can help designers to create more innovative and successful products.

Segmentation:
By Component:
• Software
• Services

By Deployment Mode:
• Cloud
• On-Premises

By Application:
• Product Design and Development
• Supply Chain Management
• Customer Service and Experience

Geography:
North America is expected to dominate the AI in fashion market due to the high adoption of AI technologies in the fashion industry in this region. The United States is one of the largest markets for AI technology in the world, and the fashion industry is no exception. Major fashion brands and retailers in the US are increasingly adopting AI-powered solutions to provide personalized shopping experiences, optimize their supply chains, and improve their product design and development processes. Europe is also expected to be a significant market for AI in fashion, driven by the presence of major fashion brands and retailers in the region, as well as a high level of technological advancement. The Asia Pacific region is also expected to grow rapidly, with countries such as China and Japan investing heavily in AI technologies for the fashion industry.

Impact of COVID-19 on the global Artificial Intelligence In Fashion Market:
The COVID-19 pandemic has had a significant impact on the AI in fashion market, as it has on many other industries. The pandemic has disrupted supply chains across the fashion industry, leading to delays and disruptions in manufacturing and distribution. This has led to increased interest in AI-powered supply chain management solutions, which can help to optimize inventory management and improve efficiency. With physical stores closed or operating at reduced capacity, many consumers have shifted to online shopping. This has led to increased demand for AI-powered product recommendation engines and personalized shopping experiences, which can help retailers to provide a more engaging and customized online shopping experience. Many fashion brands and retailers have been forced to implement cost-cutting measures due to the pandemic, leading to increased interest in AI-powered solutions that can help to reduce costs and improve efficiency.
Overall, the impact of COVID-19 on the AI in fashion market has been mixed. While the pandemic has created challenges for the industry, it has also led to increased interest in AI-powered solutions that can help to address these challenges and improve efficiency and sustainability in the long term

Impact of the Russia-Ukraine War on the global Artificial Intelligence In Fashion Market:
If the conflict escalates, it could disrupt supply chains in the fashion industry, particularly in Europe, where many fashion brands and retailers rely on Ukrainian suppliers for textiles and other materials. This could lead to increased interest in AI-powered supply chain management solutions, as companies seek to optimize their supply chains and reduce their reliance on any one supplier or region. The conflict could also lead to economic instability in the region, which could impact consumer spending on fashion and other luxury goods. This could lead to decreased demand for AI-powered solutions in the short term, as companies focus on cutting costs and conserving resources. The conflict could create political and regulatory uncertainty in the region, which could impact the ability of companies to do business in Ukraine and Russia. This could lead to increased interest in AI-powered solutions that can help companies navigate complex regulatory environments and mitigate political risk.

Company Profiles:
• Adobe Inc.
• Amazon Web Services, Inc.
• Catchoom Technologies S.L.
• Facebook, Inc.
• Huawei Technologies Co. Ltd.
• IBM Corporation
• Intel Corporation
• Microsoft Corporation
• Oracle Corporation
• SAP SE
• Sentient Technologies Holdings Limited
• Syte.ai Ltd.
• ViSenze Pte Ltd.
• Wide Eyes Technologies
• Ximilar s.r.o.
Base Year: 2023
Historic Year: 2016-2022
Forecast: 2024-2035

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Case Study- Automotive Sector

One of the key manufacturers of automotive had plans to invest in electric utility vehicles. The electric cars and associated markets being a of evolving nature, the automotive client approached Straits Research for a detailed insight on the market forecasts. The client specifically asked for competitive analysis, regulatory framework, regional prospects studied under the influence of drivers, challenges, opportunities, and pricing in terms of revenue and sales (million units).

Solution

The overall study was executed in three stages, intending to help the client meet its objective of precisely understanding the entire market before deciding on an investment. At first, secondary research was conducted considering political, economic, social, and technological parameters to get a gist of the various aspects of the market. This stage of the study concluded with the derivation of drivers, opportunities, and challenges. It also laid substantial emphasis on understanding and collecting data not only on a global scale but also on the regional and country levels. Data Extraction through Primary Research

The second stage involved primary research in which several market players and automotive parts suppliers were contacted to study their viewpoint concerning the development of their market and production capacity, clientele, and product line. This stage concluded in a brief understanding of the competitive ecosystem and also glanced through the strategies and pricing of the companies profiled.

Market Estimates and Forecast

In the final stage of the study, market forecasts for the electric utility were derived using multiple market engineering approaches. This data helped the client to get an overview of the market and accelerate the process of investment.

Case Study- ICT Sector

Business process outsourcing, being one of the lucrative markets from both supply- and demand- side, has appealed to various companies. One of the prominent corporations based out of Japan approached us with their requirements regarding the scope of the procurement outsourcing market for around 50 countries. Additionally, the client also sought key players operating in the market and their revenue breakdown in terms of region and application.


Business Solution

An exhaustive market study was conducted based on primary and secondary research that involved factors such as labor costs in various countries, skilled and technical labors, manufacturing scenario, and their respective contributions in the global GDP. A comparative study of the market was conducted from both supply- and demand side, with the supply-side comprising of notable companies, such as GEP, Accenture, and others, that provide these services. On the other hand, large manufacturing companies from them demand-side were considered that opt for these services.


Conclusion

The report aided the client in understanding the market trends, including country-level business scenarios, consumer behavior, and trends in 50 countries. The report also provided financial insights of crucial players and detailed market estimations and forecasts till 2028.


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