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    Applied AI in Retail & E-commerce Market Size

    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...

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    Applied Ai In Retail E Commerce Size

    Applied AI in Retail & E-commerce Market Growth Projections and Opportunities

    The first driver that shapes the market dynamics of Applied AI in Retail and E-commerce is personalized customer experiences. Personalized product recommendations carry out via AI algorithms using customer data from browsing behaviors to historical purchase patterns while targeted marketing campaigns are facilitated by individualized promotions. Enhanced understanding of customers' preferences by AI results into better engagement with clients hence boosting conversion rates leading to loyalty development. Seamless shopping journey that is also personalizable has been one major force driving adoption of artificial intelligence on retail/e-commerce platforms. The industry’s acceleration towards superior customer experiences delivered through AI-driven technologies, improved operational efficiency and the transformative power of Artificial Intelligence shape the market dynamics of Applied AI in Retail and E-commerce. In Retail and E-commerce, Applied AI covers a wide range of applications like personalized recommendations, supply chain optimization, demand forecasting and customer service automation. Several key drivers contribute to the dynamic nature of this market, reflecting the evolving landscape of retail and the imperative for innovation in an increasingly digital and competitive environment.

    Applied AI in Retail: Market Dynamics – e-Commerce evolution and online purchasing influencing factors. For instance with more consumers turning to online platform for their purchases, there have been new developments such as virtual try-ons which aid in visual search as well as interactive shopping. Simplifying buying process online, product discovery improvement or provision of virtual assistance services are some other areas where artificial intelligence technologies are employed here. This helps them meet growing demands for digital-savvy customers but also cope with challenges linked to changing face of internet retailing. Additionally, Applied AI Market Dynamics: Efficiency needs for retail operations & supply chain management. Balanced inventory management systems enhanced through machine learning techniques allow proper demand forecasting thus reducing total costs besides minimizing stockouts resulting in better performance all through a supply chain. Predictive abilities of AI help in fast adapting to changing consumer trends as per past data and market analysis. In the developing retail landscape, improved operations brought about by artificial intelligence and better supply chain visibility are therefore essential.

    Applied AI in Retail & E-commerce Market Size Graph

    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 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

    The integration of artificial intelligence in retail and e-commerce is reshaping consumer experiences and operational efficiencies, suggesting a transformative shift in how businesses engage with their customers.

    U.S. Department of Commerce

    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 2034

    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)

    APPLIED AI IN RETAIL & E-COMMERCE MARKET SHARE BY REGION, 2022 & 2032

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

    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 Regional Outlook (USD Billion, 2019-2032)

    • US
    • Canada

    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

    Market Highlights

    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.

    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. 2.1.
      2. Definition
      3. Scope of the Study
      4. Market Structure
      5. Key
      6. Buying Criteria
      7. 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. 4.4.1.
      11. AI can facilitate international expansion by automating translation, currency conversion,
      12. and localization efforts for e-commerce businesses
      13. Challenges
      14. 4.5.1.
      15. Integrating AI solutions into existing systems and processes can be complex and
      16. disruptive
      17. Covid-19 Impact Analysis
        1. Impact on Applied AI in
        2. Impact on End Users during the Lockdowns
      18. 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. 5.2.4.
      4. Threat of Substitutes
    15. GLOBAL APPLIED AI
    16. IN RETAIL & E-COMMERCE MARKET, BY TECHNOLOGY
      1. Introduction
      2. 6.2.
      3. Machine Learning
      4. Natural Language Processing (NLP)
      5. Computer
      6. Vision
      7. Speech Recognition
      8. Predictive Analytics
    17. GLOBAL
    18. APPLIED AI IN RETAIL & E-COMMERCE MARKET, BY APPLICATION
      1. Introduction
      2. Customer Service & Support
      3. Sales & Marketing
      4. 7.4.
      5. Supply Chain Management
      6. Price Optimization
      7. Payment Processing
      8. 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
      7. 10.2.6.4.
    23. Market Estimates & Forecast, by End-User, 2018-2032
      1. 10.2.7.1.
    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
      7. 10.3.3.
    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
      6. 10.3.7.4.
    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
      1. 10.3.8.1.
    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
      7. 10.3.10.4.
    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
      1. 10.3.11.2.
    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
      7. 10.4.6.3.
    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
      2. 10.4.7.1.
    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
      7. 10.4.9.4.
    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
      1. 10.4.10.2.
    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
      3. 10.5.1.
    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
      6. 10.5.6.4.
    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. 11.3.
      4. Competitor Benchmarking
      5. Vendor Share Analysis, 2022(% Share)
      6. 12.
      7. COMPANY PROFILES
      8. Quantifind
        1. Company Overview
        2. Product Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      9. 12.1.2.
      10. Financial Overview
      11. OpenAI
        1. Financial Overview
        2. Product Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      12. 12.2.1.
      13. Company Overview
      14. Accenture
        1. Company Overview
        2. Financial Overview
        3. Product Offered
        4. Key Developments
        5. SWOT Analysis
        6. Key Strategies
      15. DataRobot
        1. Company Overview
        2. Product Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      16. 12.4.2.
      17. Financial Overview
      18. SAS
        1. Financial Overview
        2. Product Offered
        3. Key Developments
        4. SWOT Analysis
        5. Key Strategies
      19. 12.5.1.
      20. Company Overview
      21. IBM
        1. Company Overview
        2. Financial Overview
        3. Key Developments
        4. SWOT Analysis
      22. 12.6.3.
      23. Product Offered
      24. 12.6.6.
      25. Key Strategies
      26. Microsoft
        1. Company Overview
        2. Financial
        3. Product Offered
        4. Key Developments
        5. Key Strategies
      27. Overview
      28. 12.7.5.
      29. SWOT Analysis
      30. 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
      31. Overview
      32. 12.8.4.
      33. Key Developments
      34. 12.9.
      35. NVIDIA
      36. 12.9.3.
      37. Product Offered
      38. 12.9.6.
      39. Key Strategies
      40. Intel
        1. Company Overview
        2. Financial
        3. Product Offered
        4. Key Developments
        5. Key Strategies
      41. Overview
      42. 12.10.5.
      43. SWOT Analysis
      44. 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
      45. Overview
      46. 12.11.4.
      47. Key Developments
      48. 12.12.
      49. Amazon
      50. 12.12.3.
      51. Product Offered
      52. 12.12.6.
      53. Key Strategies
      54. Others
        1. Company Overview
        2. Financial
        3. Product Offered
        4. Key Developments
        5. Key Strategies
      55. Overview
      56. 12.13.5.
      57. 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)
      1. 23
    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)
      1. 33
    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)
      1. 41
    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)
      1. 46
    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)
      1. 49
    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)
      1. 54
    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)
      1. 62
    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)
      1. 84
    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)
      1. 89
    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)
      1. 97
    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)
      1. 99
    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)
      1. 101
    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
      1. 116
    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
      1. 136
    268. GOOGLE : PRODUCTS OFFERED 137
    269. GOOGLE : KEY DEVELOPMENT
      1. 138
    270. AMAZON : PRODUCTS OFFERED 139
    271. AMAZON : KEY DEVELOPMENT
      1. 140
    272. OTHERS : PRODUCTS OFFERED 139
    273. OTHERS : KEY DEVELOPMENT
      1. 140
    274. LIST OF FIGURES
    275. MARKET SYNOPSIS
      1. 25
    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
      1. 34
    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
      1. 45
    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)
      1. 52
    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)
      1. 68
    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)
      1. 77
    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)
      1. 90
    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
      1. 101
    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
      1. 115
    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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    Customer Strories

    “I am very pleased with how market segments have been defined in a relevant way for my purposes (such as "Portable Freezers & refrigerators" and "last-mile"). In general the report is well structured. Thanks very much for your efforts.”

    Victoria Milne

    Founder
    Case Study
    Chemicals and Materials