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Applied AI in Retail & E-commerce Market Analysis

ID: MRFR/ICT/10660-HCR
128 Pages
Aarti Dhapte
October 2025

Applied AI in Retail & E-commerce Market Research Report: By Technology (Machine Learning, Natural Language Processing (NLP), Computer Vision, Speech Recognition, and Predictive Analytics), Application (Customer Service & Support, Sales & Marketing, Supply Chain Management, Price Optimization, Payment Processing, and Product Search & Discovery), Deployment (On-Premise, and Cloud-Based), End-User (Retailers, E-commerce Platforms, Consumer Goods Manufacturers, Logistics & Supply Chain Companies), By Region - Forecast Till 2... read more

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Market Analysis

In-depth Analysis of Applied AI in Retail & E-commerce Market Industry Landscape

Applied AI in Retail & E-commerce Market is a constantly evolving influential sector affected by multiple factors shaping its direction such as retail growth and online commerce rebirths. A major driver behind its expansion includes growing number of companies who realize the transformative role of AI technologies in enhancing customer experience, optimizing operations and improving operational efficiency. As such, Applied Artificial Intelligence (AI) becomes a critical instrument for personalization, predictive analytics and operation automation among retailers and e-commerce platforms struggling to maintain their competitiveness in the fast-changing market. Technological advancement is essential to the Applied AI in Retail & E-commerce Market. Improved artificial intelligence algorithms, machine learning models and natural language processing contribute to smart solutions that can analyze massive amounts of consumer data. Some of the innovations that have been taking place on the market include AI-driven recommendation engines, personalized marketing, demand forecasting as well as chatbot enabled customer service which are all geared towards empowering retailers and e-commerce players with data-driven insights as well as automation abilities. On the other hand, it should be noted that global economic conditions significantly influence applied AI in Retail & E-commerce Market. Global economy fluctuations can affect customers’ spending habits thus impacting investment decisions made by retail or e-commerce firms relating to AI-backed technologies adoption. In times of economic growth, more funds tend to flow into new technological developments hence fostering innovation for retail and e-commerce AI solutions. Contrarily, during an economic slowdown, a more cautious approach is taken thus affecting levels of investments within this sector leading to decreased rates of development in retail/e-commerce AI industry. Regulatory turbulence and privacy issues are essential elements in the Applied AI in Retail & E-commerce Market. Retail operations are intrinsically integrated with AI technology, thus necessitating the introduction of legal frameworks that regulate customer’s privacy, data security as well as ethical considerations. Compliance with regulations and being able to show responsible and ethical use of AI is crucial for companies involved in developing and implementing AI solutions in the retailing and e-commerce sector. The competitive landscape acts as a major driver for Applied AI in Retail & E-commerce Market. The retail market is flooded with different companies providing AI powered solutions therefore making competition stiffer than ever. When choosing an artificial intelligence solution, retailers and e-commerce platforms must consider factors such as the accuracy of their algorithms, how scalable they are, what customers’ experience will be like on them as well as how personalized they can make shopping experiences seamless. This is a fast moving industry where continuous innovation helps address unique challenges posed by retailing.

Author
Aarti Dhapte
Team Lead - Research

She holds an experience of about 6+ years in Market Research and Business Consulting, working under the spectrum of Information Communication Technology, Telecommunications and Semiconductor domains. Aarti conceptualizes and implements a scalable business strategy and provides strategic leadership to the clients. Her expertise lies in market estimation, competitive intelligence, pipeline analysis, customer assessment, etc.

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FAQs

How much is the Applied AI in Retail & E-commerce Market?

The Applied AI in Retail & E-commerce Market size was valued at USD 44.75 billion in 2024.

What is the growth rate of the Applied AI in Retail & E-commerce Market?

The global market is projected to grow at a CAGR of 30.86% during the forecast period, 2025-2034.

Which region held the largest market share in the Applied AI in Retail & E-commerce Market?

North America had the largest share in the Applied AI in Retail & E-commerce Market.

Who are the key players in the Applied AI in Retail & E-commerce Market?

The key players in the market are Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon, and other market players.

Which Technology Type led the Applied AI in Retail & E-commerce Market?

Machine Learning dominated the market in 2024.

Which application had the largest market share in the Applied AI in Retail & E-commerce Market?

The Customer Service & Support application had the largest share in the global market.

Market Summary

The Global Applied AI in Retail and E-commerce Market is projected to experience substantial growth from 44.75 USD Billion in 2024 to 862.56 USD Billion by 2035.

Key Market Trends & Highlights

Applied AI in Retail & E-commerce Market Key Trends and Highlights

  • The market is expected to grow at a remarkable CAGR of 30.88% from 2025 to 2035.
  • By 2035, the market valuation is anticipated to reach 862.5 USD Billion, indicating a robust expansion.
  • in 2024, the market is valued at 44.75 USD Billion, laying a strong foundation for future growth.
  • Growing adoption of AI technologies due to increasing consumer demand for personalized shopping experiences is a major market driver.

Market Size & Forecast

2024 Market Size 44.75 (USD Billion)
2035 Market Size 862.56 (USD Billion)
CAGR (2025-2035) 30.86%
Largest Regional Market Share in 2024 latin_america)

Major Players

Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon

Market Trends

Applied AI in Retail & E-commerce Market Market Drivers

Market Growth Projections

The Global Applied AI in Retail and E-commerce Market Industry is poised for remarkable growth, with projections indicating a market value of 44.7 USD Billion in 2024 and an anticipated surge to 862.5 USD Billion by 2035. This growth trajectory reflects a compound annual growth rate of 30.88% from 2025 to 2035, highlighting the increasing adoption of AI technologies across the retail sector. As businesses continue to recognize the transformative potential of AI, the market is likely to expand significantly, driven by advancements in technology, consumer demand for personalization, and the need for efficient supply chain management.

Enhanced Supply Chain Management

Efficient supply chain management is crucial for the success of the Global Applied AI in Retail and E-commerce Market Industry. AI technologies enable retailers to optimize inventory levels, forecast demand accurately, and streamline logistics. For example, predictive analytics can help businesses anticipate stock shortages and adjust procurement strategies accordingly. This optimization not only reduces operational costs but also enhances customer satisfaction by ensuring product availability. As the market evolves, the integration of AI in supply chain processes is expected to drive significant growth, with a projected compound annual growth rate of 30.88% from 2025 to 2035.

Rapid Technological Advancements

The Global Applied AI in Retail and E-commerce Market Industry is experiencing rapid technological advancements that enhance operational efficiency and customer experience. Innovations in machine learning, natural language processing, and computer vision are transforming how retailers interact with consumers. For instance, AI-driven chatbots are now commonplace, providing 24/7 customer service and personalized recommendations. This technological evolution is projected to drive the market's growth, with the industry expected to reach 44.7 USD Billion in 2024. As these technologies continue to evolve, they are likely to create new opportunities for retailers to optimize their supply chains and improve customer engagement.

Emergence of Omnichannel Retailing

The emergence of omnichannel retailing is reshaping the Global Applied AI in Retail and E-commerce Market Industry. Retailers are increasingly adopting a seamless approach to integrate online and offline shopping experiences, which is facilitated by AI technologies. By utilizing AI for data analysis, businesses can better understand consumer behavior across multiple channels and tailor their marketing strategies accordingly. This integration not only enhances customer engagement but also drives sales growth. As the market adapts to this omnichannel approach, it is likely to witness substantial growth, with projections indicating a market value of 862.5 USD Billion by 2035.

Growing Investment in AI Technologies

Investment in AI technologies is a key driver of the Global Applied AI in Retail and E-commerce Market Industry. Retailers are increasingly allocating resources to develop and implement AI solutions that enhance their operational capabilities. This trend is evidenced by the rising number of partnerships between technology firms and retail businesses aimed at harnessing AI for various applications, from customer service to inventory management. As companies recognize the potential return on investment from AI integration, funding for AI initiatives is expected to surge, further propelling market growth. The industry's value is anticipated to reach 44.7 USD Billion in 2024, reflecting this growing investment trend.

Increased Consumer Demand for Personalization

Consumer demand for personalized shopping experiences is a significant driver in the Global Applied AI in Retail and E-commerce Market Industry. Shoppers increasingly expect tailored recommendations and experiences that cater to their individual preferences. Retailers are leveraging AI algorithms to analyze consumer data and deliver personalized content, which has been shown to enhance customer satisfaction and loyalty. As a result, businesses that adopt AI-driven personalization strategies are likely to see increased sales and customer retention. This trend is expected to contribute to the market's growth, with projections indicating a substantial increase in market value, reaching 862.5 USD Billion by 2035.

Market Segment Insights

Applied AI in Retail & E-commerce Market- Technology Insights

The Applied AI in Retail & E-commerce Market segmentation, based on Technology, includes Machine Learning, Natural Language Processing (NLP), Computer Vision, Speech Recognition, and Predictive Analytics. The Machine Learning segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. Machine learning is a critical segment within the field of Applied AI in the retail and e-commerce market. It plays a central role in driving personalization, optimizing operations, and enhancing decision-making processes.

Machine learning algorithms analyze customer data, such as browsing history, purchase behavior, and preferences, to provide personalized product recommendations. These recommendations increase the likelihood of customers finding and purchasing products that align with their interests.

Applied AI in Retail & E-commerce Market- Application Insights

The Applied AI in Retail & E-commerce Market segmentation, based on Application, includes Customer Service & Support, Sales & Marketing, Supply Chain Management, Price Optimization, Payment Processing, and Product Search & Discovery. The Customer Service & Support segment dominated the market growth in 2022 and is projected to be the faster-growing segment during the forecast period, 2023-2032. The Customer Service & Support segment is a crucial area of Applied AI in the retail and e-commerce market, as it enables businesses to provide efficient, personalized, and 24/7 customer assistance.

AI-powered chatbots and virtual assistants handle routine customer inquiries, such as order tracking, product information, and return requests, freeing up human agents to focus on more complex issues. AI can route customer queries to the most appropriate human agents or departments, ensuring that customers receive prompt and accurate responses.

FIGURE 2: APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022 & 2032 (USD BILLION)

Source: Secondary Research, Primary Research, Market Research Future Database and Analyst Review

Applied AI in Retail & E-commerce Market – Deployment Mode Insights

The Applied AI in Retail & E-commerce Market segmentation, based on Deployment Mode, includes on-premise, and cloud based. The on-premise segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. The On-Premise segment in the Applied AI in Retail & E-commerce Market refers to the deployment mode where AI solutions and systems are hosted and operated within the physical infrastructure of the retailer or e-commerce company, rather than being hosted on cloud-based servers or third-party data centers.

In this deployment model, AI applications, servers, storage, and other necessary hardware and software components are located within the retailer's or e-commerce company's own data centers or facilities.

Applied AI in Retail & E-commerce Market – End User Insights

The Applied AI in Retail & E-commerce Market segmentation, based on End User, includes Retailers, E-commerce Platforms, Consumer Goods Manufacturers, Logistics & Supply Chain Companies, and Others. The Retailers segment held the majority share in 2022 in the Applied AI in Retail & E-commerce Market data and is projected to be the fast-growing segment in the forecast period. Retailers use Applied AI to analyze customer data and behavior, enabling personalized product recommendations and content to improve the AI-powered shopping experience. AI optimizes supply chain operations, reducing costs and enhancing the efficiency of inventory movement and logistics.

Retailers analyze customer behavior through AI to gain insights into shopping patterns, preferences, and trends.

Get more detailed insights about Applied AI in Retail & E-commerce Market Research Report - Forecast till 2035

Regional Insights

By region, the study provides the market insights into North America, Europe, Asia-Pacific, Middle East & Africa, and South America. North America Applied AI in Retail & E-commerce Market accounted for USD 7.65 billion in 2022 with a share of around 34.61% and is expected to exhibit a significant CAGR growth during the study period. The growth of Applied AI in the Retail & E-commerce Market in North America is driven by several key factors that reflect the region's strong technology infrastructure, consumer demand for personalized experiences, and the competitive nature of the retail industry.

North America, particularly the United States, boasts a mature and robust technology ecosystem with a concentration of AI research, development, and innovation centers. This fosters a conducive environment for the growth of Applied AI applications in retail and e-commerce. Consumers in the region value convenience and expect seamless shopping experiences, which Applied AI can deliver through features like chatbots, virtual assistants, and smooth checkout processes.

Further, the major countries studied in the market report are: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.

Figure 3: APPLIED AI IN RETAIL & E-COMMERCE MARKET SHARE BY REGION, 2022 & 2032 (USD BILLION)

Europe Applied AI in Retail & E-commerce Market accounts for the second-largest market share. The e-commerce sector in Europe has experienced significant growth, and it continues to expand rapidly. This growth has incentivized retailers and e-commerce platforms to invest in Applied AI technologies to stay competitive and improve operational efficiency. Moreover, Germany Applied AI in Retail & E-commerce Market held the largest market share, and the UK Applied AI in Retail & E-commerce Market was the fastest growing market in the European region.

Asia-Pacific Applied AI in Retail & E-commerce Market accounts for the third-largest market share and is projected to continue increasing due to rapid digital transformation. Asia-Pacific is experiencing rapid digital transformation, with more consumers and businesses going online. Retailers and e-commerce platforms are leveraging Applied AI to enhance their digital offerings and customer experiences. Further, the China Applied AI in Retail & E-commerce Market held the largest market share, and the India Applied AI in Retail & E-commerce Market was the fastest growing market in the region.

The Middle East & Africa Applied AI in Retail & E-commerce Market is rapidly growing due to increasing cross border trade. Cross-border e-commerce is growing in Middle East & Africa, and Applied AI helps retailers manage international operations, currency conversions, and localization to cater to a diverse customer base. The region's e-commerce market is competitive, with both local and international players. AI is used to gain a competitive edge through improved customer experiences, personalized recommendations, and efficient supply chain management.

Also, The South America Applied AI in Retail & E-commerce Market is growing due to increase in Tech-Savvy Consumers. South America has a growing population of tech-savvy consumers who are increasingly comfortable with digital technologies. AI-driven features such as personalized recommendations and mobile commerce are well-received by this demographic.

Key Players and Competitive Insights

Major market players are spending a lot of money on R&D to increase their product lines, which will help the Applied AI in Retail & E-commerce Market grow even more. Market participants are also taking a range of strategic initiatives to grow their worldwide footprint, with key market developments such as new product launches, mergers and acquisitions, contractual agreements, increased investments, and collaboration with other organizations. Competitors in the Applied AI in Retail & E-commerce industry must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.

One of the primary business strategies adopted by manufacturers in the global Applied AI in Retail & E-commerce industry to benefit clients and expand the market sector is to manufacture locally to reduce operating costs. In recent years, Applied AI in Retail & E-commerce industry has provided Technology segment with some of the most significant benefits. The Applied AI in Retail & E-commerce Market major player such as Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon, and other market players.

Brain Corp, San Diego, is a technology-based company specializing in the development of intelligent, autonomous navigation systems for everyday machines. In March 2023, Brain Corp has rolled out its autonomous floor scrubber ‘Auto-C’ that cleans the aisle of a Walmart’s store and captures in real-time, images of every single item in the store.

Key Companies in the Applied AI in Retail & E-commerce Market market include

Industry Developments

August 2023:The Singapore MIT-Alliance for Research and Technology (SMART), a research enterprise in Singapore, has launched a new interdisciplinary research group working on rise of artificial intelligence and other new technologies. 

September 2023:Zomato, a leading online meal delivery service, has introduced ‘Zomato AI’, an interactive chatbot to make food ordering process more convenient & personalized.

Future Outlook

Applied AI in Retail & E-commerce Market Future Outlook

The Applied AI in Retail & E-commerce Market is projected to grow at a 30.86% CAGR from 2025 to 2035, driven by enhanced customer personalization, operational efficiency, and data analytics advancements.

New opportunities lie in:

  • Develop AI-driven inventory management systems to optimize stock levels and reduce waste.
  • Implement personalized shopping experiences using AI algorithms to enhance customer engagement.
  • Leverage predictive analytics for targeted marketing campaigns to increase conversion rates.

By 2035, the market is expected to be a cornerstone of retail innovation and efficiency.

Market Segmentation

Applied AI in Retail & E-commerce End-User Outlook (USD Billion, 2019-2032)

  • Retailers
  • E-commerce Platforms
  • Consumer Goods Manufacturers
  • Logistics & Supply Chain Companies
  • Others

Applied AI in Retail & E-commerce Technology Outlook (USD Billion, 2019-2032)

  • Machine Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Speech Recognition
  • Predictive Analytics

Applied AI in Retail & E-commerce Application Outlook (USD Billion, 2019-2032)

  • Customer Service & Support
  • Sales & Marketing
  • Supply Chain Management
  • Price Optimization
  • Payment Processing
  • Product Search & Discovery

Applied AI in Retail & E-commerce Deployment Mode Outlook (USD Billion, 2019-2032)

  • On-premise
  • Cloud-based

Report Scope

Report Attribute/Metric Details
Market Size 2024 44.75 (USD Billion)
Market Size 2025 58.56 (USD Billion)
Market Size 2035 862.56 (USD Billion)
Compound Annual Growth Rate (CAGR) 30.86% (2025 - 2035)
Report Coverage Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Base Year 2024
Market Forecast Period 2025 - 2035
Historical Data 2019 - 2023
Market Forecast Units USD Billion
Segments Covered Technology, Application, Deployment Mode, End-User, and Region
Geographies Covered North America, Europe, Asia-Pacific Pacific, Middle East & Africa, and South America
Countries Covered The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil
Key Companies Profiled Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon, and other market players.
Key Market Opportunities AI can facilitate international expansion by automating translation, currency conversion, and localization efforts for e-commerce businesses
Key Market Dynamics Growing demand due to capability of Applied AI offering tailored product recommendations, pricing, and content, enhancing customer satisfaction & conversion rates Ability of Applied AI of demand forecasting, inventory management, and logistics optimization leading to cost savings, reduced stockouts, and improved order fulfillment

FAQs

How much is the Applied AI in Retail & E-commerce Market?

The Applied AI in Retail & E-commerce Market size was valued at USD 44.75 billion in 2024.

What is the growth rate of the Applied AI in Retail & E-commerce Market?

The global market is projected to grow at a CAGR of 30.86% during the forecast period, 2025-2034.

Which region held the largest market share in the Applied AI in Retail & E-commerce Market?

North America had the largest share in the Applied AI in Retail & E-commerce Market.

Who are the key players in the Applied AI in Retail & E-commerce Market?

The key players in the market are Quantifind, OpenAI, Accenture, DataRobot, SAS, IBM, Microsoft, Adobe, NVIDIA, Intel, Google, Amazon, and other market players.

Which Technology Type led the Applied AI in Retail & E-commerce Market?

Machine Learning dominated the market in 2024.

Which application had the largest market share in the Applied AI in Retail & E-commerce Market?

The Customer Service & Support application had the largest share in the global market.

  1. EXECUTIVE SUMMARY
    1. Market Attractiveness Analysis
      1. Global
  2. Applied AI in Retail & E-commerce Market, by Technology
  3. Global Applied
  4. AI in Retail & E-commerce Market, by Application
  5. Global Applied
  6. AI in Retail & E-commerce Market, by Deployment Mode
  7. Global Applied
  8. AI in Retail & E-commerce Market, by End-User
  9. Global Applied AI
  10. in Retail & E-commerce Market, by Region
  11. MARKET INTRODUCTION
    1. Definition
    2. Scope of the Study
    3. Market Structure
    4. Key
    5. Buying Criteria
    6. Macro Factor Indicator Analysis
  12. RESEARCH METHODOLOGY
    1. Research Process
    2. Primary Research
    3. Secondary Research
    4. Market Size Estimation
    5. Forecast Model
    6. List of Assumptions
  13. MARKET DYNAMICS
    1. Introduction
    2. Drivers
      1. Growing
      2. Ability of Applied AI of demand forecasting, inventory management, and
      3. Drivers impact analysis
    3. demand due to capability of Applied AI offering tailored product recommendations,
    4. pricing, and content, enhancing customer satisfaction & conversion rates
    5. logistics optimization leading to cost savings, reduced stockouts, and improved
    6. order fulfillment
    7. Restraints
      1. Collection & analysis of customer data for AI applications raise privacy
      2. Restraint impact analysis
    8. concerns
    9. Opportunities
    10. AI can facilitate international expansion by automating translation, currency conversion,
    11. and localization efforts for e-commerce businesses
    12. Challenges
    13. Integrating AI solutions into existing systems and processes can be complex and
    14. disruptive
    15. Covid-19 Impact Analysis
      1. Impact on Applied AI in
      2. Impact on End Users during the Lockdowns
    16. Retail & E-commerce Market
  14. MARKET FACTOR ANALYSIS
    1. Value Chain Analysis/Supply Chain Analysis
    2. Porter’s Five Forces Model
      1. Bargaining Power of Suppliers
      2. Bargaining Power of Buyers
      3. Threat of New Entrants
      4. Intensity of Rivalry
    3. Threat of Substitutes
  15. GLOBAL APPLIED AI
  16. IN RETAIL & E-COMMERCE MARKET, BY TECHNOLOGY
    1. Introduction
    2. Machine Learning
    3. Natural Language Processing (NLP)
    4. Computer
    5. Vision
    6. Speech Recognition
    7. Predictive Analytics
  17. GLOBAL
  18. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION
    1. Introduction
    2. Customer Service & Support
    3. Sales & Marketing
    4. Supply Chain Management
    5. Price Optimization
    6. Payment Processing
    7. Product Search & Discovery
  19. GLOBAL APPLIED AI IN RETAIL &
  20. E-COMMERCE MARKET, BY DEPLOYMENT MODE
    1. Introduction
    2. On-premise
    3. Cloud-based
  21. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY END-USER
    2. Introduction
    3. Retailers
    4. E-commerce Platforms
    5. Consumer Goods Manufacturers
    6. Logistics & Supply Chain Companies
    7. Others
  22. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE
    1. ESTIMATION & FORECAST, BY REGION
    2. Introduction
    3. North America
      1. Market Estimates & Forecast, by Country, 2018-2032
      2. Market
      3. Market Estimates
      4. Market Estimates & Forecast,
      5. Market Estimates & Forecast, by End-User,
      6. US
    4. Estimates & Forecast, by Technology, 2018-2032
    5. & Forecast, by Application, 2018-2032
    6. by Deployment Mode, 2018-2032
  23. Market Estimates & Forecast, by End-User, 2018-2032
  24. Canada
  25. Market Estimates & Forecast, by Technology, 2018-2032
    1. Estimates & Forecast, by Application, 2018-2032
    2. & Forecast, by Deployment Mode, 2018-2032
    3. Forecast, by End-User, 2018-2032
    4. & Forecast, by Technology, 2018-2032
    5. by Application, 2018-2032
    6. Mode, 2018-2032
  26. Market
  27. Market Estimates
  28. Market Estimates &
  29. Mexico
  30. Market Estimates
  31. Market Estimates & Forecast,
  32. Market Estimates & Forecast, by Deployment
  33. Market Estimates & Forecast, by End-User, 2018-2032
    1. Europe
      1. Market Estimates & Forecast, by Country, 2018-2032
      2. Market Estimates & Forecast, by Technology, 2018-2032
  34. Market Estimates & Forecast, by Application, 2018-2032
    1. & Forecast, by Deployment Mode, 2018-2032
    2. Forecast, by End-User, 2018-2032
    3. & Forecast, by Technology, 2018-2032
    4. by Application, 2018-2032
    5. Mode, 2018-2032
  35. Market Estimates
  36. Market Estimates &
  37. UK
  38. Market Estimates
  39. Market Estimates & Forecast,
  40. Market Estimates & Forecast, by Deployment
  41. Market Estimates & Forecast, by End-User, 2018-2032
  42. Germany
  43. Market Estimates & Forecast, by Technology,
  44. Market Estimates & Forecast, by Application, 2018-2032
  45. Market Estimates & Forecast, by Deployment Mode, 2018-2032
  46. Market Estimates & Forecast, by End-User, 2018-2032
  47. France
  48. Market Estimates & Forecast, by Technology, 2018-2032
    1. Estimates & Forecast, by Application, 2018-2032
    2. & Forecast, by Deployment Mode, 2018-2032
    3. Forecast, by End-User, 2018-2032
    4. & Forecast, by Technology, 2018-2032
    5. by Application, 2018-2032
    6. Mode, 2018-2032
  49. Market
  50. Market Estimates
  51. Market Estimates &
  52. Italy
  53. Market Estimates
  54. Market Estimates & Forecast,
  55. Market Estimates & Forecast, by Deployment
  56. Market Estimates & Forecast, by End-User, 2018-2032
  57. Spain
  58. Market Estimates & Forecast, by Technology,
  59. Market Estimates & Forecast, by Application, 2018-2032
  60. Market Estimates & Forecast, by Deployment Mode, 2018-2032
  61. Market Estimates & Forecast, by End-User, 2018-2032
  62. Rest of Europe
  63. Market Estimates & Forecast, by Technology, 2018-2032
  64. Market Estimates & Forecast, by Application, 2018-2032
    1. Estimates & Forecast, by Deployment Mode, 2018-2032
    2. & Forecast, by End-User, 2018-2032
    3. Estimates & Forecast, by Country, 2018-2032
    4. Forecast, by Technology, 2018-2032
    5. by Application, 2018-2032
    6. Mode, 2018-2032
  65. Market
  66. Market Estimates
    1. Asia-Pacific
      1. Market
      2. Market Estimates &
      3. Market Estimates & Forecast,
      4. Market Estimates & Forecast, by Deployment
      5. Market Estimates & Forecast, by End-User, 2018-2032
      6. China
  67. Market Estimates & Forecast, by Deployment Mode, 2018-2032
    1. Estimates & Forecast, by End-User, 2018-2032
  68. Market
  69. Japan
  70. Market Estimates & Forecast, by Technology, 2018-2032
    1. Estimates & Forecast, by Application, 2018-2032
    2. & Forecast, by Deployment Mode, 2018-2032
    3. Forecast, by End-User, 2018-2032
    4. & Forecast, by Technology, 2018-2032
    5. by Application, 2018-2032
    6. Mode, 2018-2032
  71. Market
  72. Market Estimates
  73. Market Estimates &
  74. India
  75. Market Estimates
  76. Market Estimates & Forecast,
  77. Market Estimates & Forecast, by Deployment
  78. Market Estimates & Forecast, by End-User, 2018-2032
  79. Australia
  80. Market Estimates & Forecast, by Technology,
  81. Market Estimates & Forecast, by Application, 2018-2032
  82. Market Estimates & Forecast, by Deployment Mode, 2018-2032
  83. Market Estimates & Forecast, by End-User, 2018-2032
  84. Rest of Asia-Pacific
  85. Market Estimates & Forecast, by Technology, 2018-2032
  86. Market Estimates & Forecast, by Application, 2018-2032
    1. Estimates & Forecast, by Deployment Mode, 2018-2032
    2. & Forecast, by End-User, 2018-2032
  87. Market
  88. Market Estimates
    1. Rest of the World
  89. Market Estimates & Forecast, by Technology, 2018-2032
    1. & Forecast, by Application, 2018-2032
    2. by Deployment Mode, 2018-2032
    3. & Forecast, by Technology, 2018-2032
    4. by Application, 2018-2032
    5. Mode, 2018-2032
  90. Market Estimates
  91. Market Estimates & Forecast,
  92. Market Estimates & Forecast, by End-User,
  93. Middle East & Africa
  94. Market Estimates
  95. Market Estimates & Forecast,
  96. Market Estimates & Forecast, by Deployment
  97. Market Estimates & Forecast, by End-User, 2018-2032
  98. South America
  99. Market Estimates & Forecast, by Technology,
  100. Market Estimates & Forecast, by Application, 2018-2032
  101. Market Estimates & Forecast, by Deployment Mode, 2018-2032
  102. Market Estimates & Forecast, by End-User, 2018-2032
  103. COMPETITIVE LANDSCAPE
    1. Introduction
    2. Key Developments & Growth Strategies
    3. Competitor Benchmarking
    4. Vendor Share Analysis, 2022(% Share)
    5. COMPANY PROFILES
    6. Quantifind
      1. Company Overview
      2. Product Offered
      3. Key Developments
      4. SWOT Analysis
      5. Key Strategies
    7. Financial Overview
    8. OpenAI
      1. Financial Overview
      2. Product Offered
      3. Key Developments
      4. SWOT Analysis
      5. Key Strategies
    9. Company Overview
    10. Accenture
      1. Company Overview
      2. Financial Overview
      3. Product Offered
      4. Key Developments
      5. SWOT Analysis
      6. Key Strategies
    11. DataRobot
      1. Company Overview
      2. Product Offered
      3. Key Developments
      4. SWOT Analysis
      5. Key Strategies
    12. Financial Overview
    13. SAS
      1. Financial Overview
      2. Product Offered
      3. Key Developments
      4. SWOT Analysis
      5. Key Strategies
    14. Company Overview
    15. IBM
      1. Company Overview
      2. Financial Overview
      3. Key Developments
      4. SWOT Analysis
    16. Product Offered
    17. Key Strategies
    18. Microsoft
      1. Company Overview
      2. Financial
      3. Product Offered
      4. Key Developments
      5. Key Strategies
    19. Overview
    20. SWOT Analysis
    21. Adobe
      1. Company
      2. Financial Overview
      3. Product Offered
      4. SWOT Analysis
      5. Key Strategies
      6. Company Overview
      7. Financial Overview
      8. Key Developments
      9. SWOT Analysis
    22. Overview
    23. Key Developments
    24. NVIDIA
    25. Product Offered
    26. Key Strategies
    27. Intel
      1. Company Overview
      2. Financial
      3. Product Offered
      4. Key Developments
      5. Key Strategies
    28. Overview
    29. SWOT Analysis
    30. Google
      1. Company
      2. Financial Overview
      3. Product Offered
      4. SWOT Analysis
      5. Key Strategies
      6. Company Overview
      7. Financial Overview
      8. Key Developments
      9. SWOT Analysis
    31. Overview
    32. Key Developments
    33. Amazon
    34. Product Offered
    35. Key Strategies
    36. Others
      1. Company Overview
      2. Financial
      3. Product Offered
      4. Key Developments
      5. Key Strategies
    37. Overview
    38. SWOT Analysis
  104. LIST OF TABLES
  105. PRIMARY
    1. INTERVIEWS 19
  106. LIST OF ASSUMPTIONS & LIMITATIONS 20
    1. TABLE 3
  107. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032
    1. (USD MILLION) 21
  108. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY APPLICATION, 2018–2032 (USD MILLION) 22
  109. GLOBAL APPLIED AI
  110. IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  111. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  112. GLOBAL APPLIED AI IN RETAIL &
  113. E-COMMERCE MARKET, BY REGION, 2018–2032 (USD MILLION) 25
  114. NORTH
  115. AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2018–2032
    1. (USD MILLION) 26
  116. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE
  117. MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 27
  118. NORTH AMERICA
  119. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD
    1. MILLION) 28
  120. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 29
  121. NORTH AMERICA
  122. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD
    1. MILLION) 30
  123. US APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION,
  124. US APPLIED AI IN RETAIL & E-COMMERCE
  125. MARKET, BY APPLICATION, 2018–2032 (USD MILLION) 32
  126. US APPLIED
  127. AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  128. US APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032
    1. (USD MILLION) 34
  129. CANADA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY FUNCTION, 2018–2032 (USD MILLION) 35
  130. CANADA APPLIED AI IN
  131. RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION) 36
  132. CANADA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE,
  133. CANADA APPLIED AI IN RETAIL &
  134. E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION) 38
  135. MEXICO
  136. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD
    1. MILLION) 39
  137. MEXICO APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. APPLICATION, 2018–2032 (USD MILLION) 40
  138. MEXICO APPLIED AI IN
  139. RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  140. MEXICO APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  141. EUROPE APPLIED AI IN RETAIL &
  142. E-COMMERCE MARKET, BY COUNTRY, 2018–2032 (USD MILLION) 43
  143. EUROPE
  144. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD
    1. MILLION) 44
  145. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. APPLICATION, 2018–2032 (USD MILLION) 45
  146. EUROPE APPLIED AI IN
  147. RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  148. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  149. UK APPLIED AI IN RETAIL & E-COMMERCE
  150. MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 48
  151. UK APPLIED AI
  152. IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION)
  153. UK APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT
    1. MODE, 2018–2032 (USD MILLION) 50
  154. UK APPLIED AI IN RETAIL &
  155. E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION) 51
  156. GERMANY
  157. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD
    1. MILLION) 52
  158. GERMANY APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY APPLICATION, 2018–2032 (USD MILLION) 53
  159. GERMANY APPLIED AI
  160. IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  161. GERMANY APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  162. FRANCE APPLIED AI IN RETAIL &
  163. E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 56
  164. FRANCE
  165. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD
    1. MILLION) 57
  166. FRANCE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. DEPLOYMENT MODE, 2018–2032 (USD MILLION) 58
  167. FRANCE APPLIED AI
  168. IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION) 59
  169. SPAIN APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032
    1. (USD MILLION) 60
  170. SPAIN APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY APPLICATION, 2018–2032 (USD MILLION) 61
  171. SPAIN APPLIED AI
  172. IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION)
  173. SPAIN APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  174. ITALY APPLIED AI IN RETAIL &
  175. E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 64
  176. ITALY
  177. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD
    1. MILLION) 65
  178. ITALY APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. DEPLOYMENT MODE, 2018–2032 (USD MILLION) 66
  179. ITALY APPLIED AI
  180. IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION) 67
  181. REST OF EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION,
  182. REST OF EUROPE APPLIED AI IN RETAIL
  183. & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION) 69
    1. TABLE
  184. REST OF EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE,
  185. REST OF EUROPE APPLIED AI IN RETAIL
  186. & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION) 71
    1. TABLE
  187. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2018–2032
    1. (USD MILLION) 72
  188. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE
  189. MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 73
  190. ASIA-PACIFIC
  191. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD
    1. MILLION) 74
  192. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 75
  193. ASIA-PACIFIC
  194. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD
    1. MILLION) 76
  195. CHINA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. FUNCTION, 2018–2032 (USD MILLION) 77
  196. CHINA APPLIED AI IN RETAIL
  197. & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION) 78
    1. TABLE
  198. CHINA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032
    1. (USD MILLION) 79
  199. CHINA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY END-USER, 2018–2032 (USD MILLION) 80
  200. JAPAN APPLIED AI IN
  201. RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 81
  202. JAPAN APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032
    1. (USD MILLION) 82
  203. JAPAN APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 83
  204. JAPAN APPLIED
  205. AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION)
  206. INDIA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION,
  207. INDIA APPLIED AI IN RETAIL &
  208. E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION) 86
    1. TABLE 69
  209. INDIA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032
    1. (USD MILLION) 87
  210. INDIA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY END-USER, 2018–2032 (USD MILLION) 88
  211. SOUTH KOREA APPLIED
  212. AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION)
  213. SOUTH KOREA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION,
  214. SOUTH KOREA APPLIED AI IN RETAIL
  215. & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 91
  216. SOUTH KOREA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  217. REST OF ASIA-PACIFIC APPLIED AI IN
  218. RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 93
  219. REST OF ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. APPLICATION, 2018–2032 (USD MILLION) 94
  220. REST OF ASIA-PACIFIC
  221. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032
    1. (USD MILLION) 95
  222. REST OF ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE
  223. MARKET, BY END-USER, 2018–2032 (USD MILLION) 96
  224. REST OF WORLD
  225. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2018–2032 (USD MILLION)
  226. REST OF WORLD APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. FUNCTION, 2018–2032 (USD MILLION) 98
  227. REST OF WORLD APPLIED AI
  228. IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032 (USD MILLION)
  229. REST OF WORLD APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. DEPLOYMENT MODE, 2018–2032 (USD MILLION) 100
  230. REST OF WORLD APPLIED
  231. AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032 (USD MILLION)
  232. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL & E-COMMERCE
  233. MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 102
  234. MIDDLE EAST
  235. & AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032
    1. (USD MILLION) 103
  236. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL &
  237. E-COMMERCE MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 104
    1. TABLE
  238. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  239. SOUTH AMERICA APPLIED AI IN RETAIL
  240. & E-COMMERCE MARKET, BY FUNCTION, 2018–2032 (USD MILLION) 110
    1. TABLE
  241. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2018–2032
    1. (USD MILLION) 111
  242. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE
  243. MARKET, BY DEPLOYMENT MODE, 2018–2032 (USD MILLION) 112
  244. SOUTH
  245. AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2018–2032
    1. (USD MILLION) 113
  246. BUSINESS EXPANSIONS/PRODUCT LAUNCHES 114
    1. TABLE
  247. PARTNERSHIPS/AGREEMENTS/CONTRACTS/COLLABORATIONS 115
  248. ACQUISITIONS/MERGERS
  249. QUANTIFIND : PRODUCTS OFFERED 117
  250. QUANTIFIND :
    1. KEY DEVELOPMENT 118
  251. OPENAI : PRODUCTS OFFERED 119
    1. TABLE 102
    2. OPENAI : KEY DEVELOPMENT 120
  252. ACCENTURE : PRODUCTS OFFERED 121
  253. ACCENTURE : KEY DEVELOPMENT 122
  254. DATAROBOT : PRODUCTS
    1. OFFERED 123
  255. DATAROBOT : KEY DEVELOPMENT 124
  256. SAS :
    1. PRODUCTS OFFERED 125
  257. SAS : KEY DEVELOPMENT 126
  258. IBM
    1. : PRODUCTS OFFERED 127
  259. IBM : KEY DEVELOPMENT 128
  260. MICROSOFT
    1. : PRODUCTS OFFERED 129
  261. MICROSOFT : KEY DEVELOPMENT 130
    1. TABLE
  262. ADOBE : PRODUCTS OFFERED 131
  263. ADOBE : KEY DEVELOPMENT 132
    1. TABLE
  264. NVIDIA : PRODUCTS OFFERED 133
  265. NVIDIA : KEY DEVELOPMENT 134
  266. INTEL : PRODUCTS OFFERED 135
  267. INTEL : KEY DEVELOPMENT
  268. GOOGLE : PRODUCTS OFFERED 137
  269. GOOGLE : KEY DEVELOPMENT
  270. AMAZON : PRODUCTS OFFERED 139
  271. AMAZON : KEY DEVELOPMENT
  272. OTHERS : PRODUCTS OFFERED 139
  273. OTHERS : KEY DEVELOPMENT
  274. LIST OF FIGURES
  275. MARKET SYNOPSIS
  276. MARKET ATTRACTIVENESS ANALYSIS: GLOBAL APPLIED AI IN RETAIL &
    1. E-COMMERCE MARKET 26
  277. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE
  278. MARKET ANALYSIS, BY FUNCTION 27
  279. GLOBAL APPLIED AI IN RETAIL &
  280. E-COMMERCE MARKET ANALYSIS, BY APPLICATION 28
  281. GLOBAL APPLIED AI IN
  282. RETAIL & E-COMMERCE MARKET ANALYSIS, BY DEPLOYMENT MODE 29
  283. GLOBAL
  284. APPLIED AI IN RETAIL & E-COMMERCE MARKET ANALYSIS, BY END-USER 30
    1. FIGURE
  285. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET ANALYSIS, BY REGION 31
  286. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET: STRUCTURE 32
  287. RESEARCH PROCESS 33
  288. TOP-DOWN AND BOTTOM-UP AND APPROACHES
  289. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE
  290. (USD MILLION) & MARKET SHARE (%), BY COUNTRY (2022 VS 2032) 35
    1. FIGURE 12
    2. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE (USD MILLION) & MARKET
    3. SHARE (%), BY COUNTRY (2022 VS 2032) 36
  291. ASIA PACIFIC APPLIED AI IN
  292. RETAIL & E-COMMERCE MARKET SIZE (USD MILLION) & MARKET SHARE (%), BY COUNTRY
    1. (2022 VS 2032) 37
  293. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL &
  294. E-COMMERCE MARKET SIZE (USD MILLION) & MARKET SHARE (%), BY COUNTRY (2022 VS
  295. AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE
  296. (USD MILLION) & MARKET SHARE (%), BY COUNTRY (2022 VS 2032) 39
    1. FIGURE 16
    2. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET SIZE (USD MILLION) &
  297. MARKET SHARE (%), BY COUNTRY (2022 VS 2032) 40
  298. MARKET DYNAMICS ANALYSIS
    1. OF THE GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET 41
  299. DRIVER
    1. IMPACT ANALYSIS 42
  300. RESTRAINT IMPACT ANALYSIS 43
  301. VALUE
    1. CHAIN: GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET 44
  302. PORTER''S
  303. FIVE FORCES ANALYSIS OF THE GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET
  304. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION,
  305. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY FUNCTION, 2022 VS 2032 (USD MILLION) 47
  306. GLOBAL APPLIED AI IN RETAIL
  307. & E-COMMERCE MARKET, BY APPLICATION, 2022 (% SHARE) 48
  308. GLOBAL
  309. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022 VS 2032 (USD
    1. MILLION) 49
  310. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY END-USER, 2022 (% SHARE) 50
  311. GLOBAL APPLIED AI IN RETAIL &
  312. E-COMMERCE MARKET, BY END-USER, 2022 VS 2032 (USD MILLION) 51
  313. GLOBAL
  314. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2022 VS 2032 (USD MILLION)
  315. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER,
  316. GLOBAL APPLIED AI IN RETAIL & E-COMMERCE
  317. MARKET, BY REGION, 2022 (% SHARE) 54
  318. GLOBAL APPLIED AI IN RETAIL
  319. & E-COMMERCE MARKET, BY REGION, 2022 VS 2032 (USD MILLION) 55
    1. FIGURE 32
  320. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2022 (%
    1. SHARE) 56
  321. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY COUNTRY, 2022 VS 2032 (USD MILLION) 57
  322. NORTH AMERICA APPLIED AI
  323. IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2022-2032 (USD MILLION) 58
    1. FIGURE
  324. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022-2032
    1. (USD MILLION) 59
  325. NORTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE
  326. MARKET, BY END-USER, 2022-2032 (USD MILLION) 60
  327. NORTH AMERICA APPLIED
  328. AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2022-2032 (USD MILLION) 61
  329. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2022
    1. (% SHARE) 62
  330. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY COUNTRY, 2022 VS 2032 (USD MILLION) 63
  331. EUROPE APPLIED AI IN RETAIL
  332. & E-COMMERCE MARKET, BY FUNCTION, 2022-2032 (USD MILLION) 64
    1. FIGURE 41
  333. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022-2032 (USD
    1. MILLION) 65
  334. EUROPE APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY END-USER, 2022-2032 (USD MILLION) 66
  335. EUROPE APPLIED AI IN RETAIL
  336. & E-COMMERCE MARKET, BY END-USER, 2022-2032 (USD MILLION) 67
    1. FIGURE 44
  337. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2022 (% SHARE)
  338. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. COUNTRY, 2022 VS 2032 (USD MILLION) 69
  339. ASIA-PACIFIC APPLIED AI IN
  340. RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2022-2032 (USD MILLION) 70
    1. FIGURE
  341. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022-2032
    1. (USD MILLION) 71
  342. ASIA-PACIFIC APPLIED AI IN RETAIL & E-COMMERCE
  343. MARKET, BY END-USER, 2022-2032 (USD MILLION) 72
  344. ASIA-PACIFIC APPLIED
  345. AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2022-2032 (USD MILLION) 73
  346. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY COUNTRY, 2022 (% SHARE) 74
  347. MIDDLE EAST & AFRICA APPLIED AI
  348. IN RETAIL & E-COMMERCE MARKET, BY COUNTRY, 2022 VS 2032 (USD MILLION) 75
  349. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY FUNCTION, 2022-2032 (USD MILLION) 76
  350. MIDDLE EAST & AFRICA
  351. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION, 2022-2032 (USD MILLION)
  352. MIDDLE EAST & AFRICA APPLIED AI IN RETAIL & E-COMMERCE
  353. MARKET, BY END-USER, 2022-2032 (USD MILLION) 78
  354. MIDDLE EAST &
  355. AFRICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2022-2032 (USD
    1. MILLION) 79
  356. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET,
    1. BY COUNTRY, 2022 (% SHARE) 86
  357. SOUTH AMERICA APPLIED AI IN RETAIL
  358. & E-COMMERCE MARKET, BY COUNTRY, 2022 VS 2032 (USD MILLION) 87
    1. FIGURE 64
  359. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY FUNCTION, 2022-2032
    1. (USD MILLION) 88
  360. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE
  361. MARKET, BY APPLICATION, 2022-2032 (USD MILLION) 89
  362. SOUTH AMERICA
  363. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY END-USER, 2022-2032 (USD MILLION)
  364. SOUTH AMERICA APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY
    1. END-USER, 2022-2032 (USD MILLION) 91
  365. GLOBAL APPLIED AI IN RETAIL
    1. & E-COMMERCE MARKET: COMPETITIVE BENCHMARKING 92
  366. VENDOR SHARE
    1. ANALYSIS (2022) (%) 93
  367. QUANTIFIND : FINANCIAL OVERVIEW SNAPSHOT 94
  368. QUANTIFIND : SWOT ANALYSIS 95
  369. OPENAI : FINANCIAL OVERVIEW
    1. SNAPSHOT 96
  370. OPENAI : SWOT ANALYSIS 97
  371. ACCENTURE :
    1. FINANCIAL OVERVIEW SNAPSHOT 98
  372. ACCENTURE : SWOT ANALYSIS 99
    1. FIGURE
  373. DATAROBOT : FINANCIAL OVERVIEW SNAPSHOT 100
  374. DATAROBOT : SWOT ANALYSIS
  375. SAS : FINANCIAL OVERVIEW SNAPSHOT 102
  376. SAS : SWOT
    1. ANALYSIS 103
  377. IBM : FINANCIAL OVERVIEW SNAPSHOT 104
    1. FIGURE 81
    2. IBM : SWOT ANALYSIS 105
  378. MICROSOFT : FINANCIAL OVERVIEW SNAPSHOT 106
  379. MICROSOFT : SWOT ANALYSIS 107
  380. ADOBE : FINANCIAL OVERVIEW
    1. SNAPSHOT 108
  381. ADOBE : SWOT ANALYSIS 109
  382. NVIDIA : FINANCIAL
    1. OVERVIEW SNAPSHOT 110
  383. NVIDIA : SWOT ANALYSIS 111
  384. INTEL
    1. : FINANCIAL OVERVIEW SNAPSHOT 112
  385. INTEL : SWOT ANALYSIS 113
    1. FIGURE
  386. GOOGLE : FINANCIAL OVERVIEW SNAPSHOT 114
  387. GOOGLE : SWOT ANALYSIS
  388. AMAZON : FINANCIAL OVERVIEW SNAPSHOT 116
  389. AMAZON
    1. : SWOT ANALYSIS 117
  390. OTHERS : FINANCIAL OVERVIEW SNAPSHOT 116
    1. FIGURE
  391. OTHERS : SWOT ANALYSIS 117

Applied AI in Retail & E-commerce Market Segmentation

Market Segmentation Overview

  • Detailed segmentation data will be available in the full report
  • Comprehensive analysis by multiple parameters
  • Regional and country-level breakdowns
  • Market size forecasts by segment
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