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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

As per MRFR analysis, the Applied AI in Retail & E-commerce Market was estimated at 44.75 USD Billion in 2024. The Applied AI industry is projected to grow from 58.57 USD Billion in 2025 to 862.56 USD Billion by 2035, exhibiting a compound annual growth rate (CAGR) of 30.86 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The Applied AI in Retail and E-commerce Market is experiencing robust growth driven by technological advancements and evolving consumer expectations.

  • Personalization and customer engagement strategies are increasingly becoming central to retail operations, particularly in North America.
  • Supply chain optimization through AI technologies is gaining traction, especially in the Asia-Pacific region, which is witnessing rapid growth.
  • Customer service automation remains the largest segment, while personalized marketing is emerging as the fastest-growing area within the market.
  • Enhanced customer insights and the automation of operations are key drivers propelling the market forward.

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 North America

Major Players

<p>Amazon (US), Alibaba (CN), Walmart (US), JD.com (CN), eBay (US), Target (US), Zalando (DE), Shopify (CA), Rakuten (JP)</p>

Market Trends

The Applied AI in Retail & E-commerce Market is currently experiencing a transformative phase, characterized by the integration of advanced technologies that enhance customer experiences and streamline operations. Retailers are increasingly adopting AI-driven solutions to personalize shopping experiences, optimize inventory management, and improve supply chain efficiency. This shift appears to be driven by the need for businesses to remain competitive in a rapidly evolving digital landscape. As consumer expectations continue to rise, the demand for innovative applications of AI is likely to grow, prompting retailers to invest in sophisticated tools that can analyze vast amounts of data and provide actionable insights. Moreover, the market seems to be influenced by the growing emphasis on sustainability and ethical practices. Retailers are exploring AI technologies that not only enhance profitability but also contribute to environmental goals. This dual focus on efficiency and sustainability may lead to the development of new business models that prioritize responsible consumption. As the Applied AI in Retail & E-commerce Market evolves, it is expected that collaboration between technology providers and retailers will intensify, fostering an ecosystem that supports continuous innovation and adaptation to changing consumer behaviors.

Personalization and Customer Engagement

The trend towards personalization is becoming increasingly pronounced, as retailers leverage AI to tailor experiences to individual preferences. By analyzing customer data, businesses can create targeted marketing campaigns and recommend products that align with consumer interests, thereby enhancing engagement and loyalty.

Supply Chain Optimization

AI technologies are being utilized to streamline supply chain processes, enabling retailers to predict demand more accurately and manage inventory effectively. This optimization not only reduces costs but also ensures that products are available when and where they are needed, improving overall operational efficiency.

Sustainability Initiatives

There is a growing trend towards integrating sustainability into retail strategies, with AI playing a crucial role. Retailers are employing AI to analyze environmental impacts and develop strategies that promote sustainable practices, appealing to a more environmentally conscious consumer base.

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

By Application: Customer Service Automation (Largest) vs. Personalized Marketing (Fastest-Growing)

<p>Within the Applied AI in Retail & E-commerce market, Customer Service Automation holds the largest share among the application segments, reflecting retailers' commitment to enhancing customer interaction efficiency. This segment utilizes AI-driven chatbots and virtual assistants, allowing businesses to reduce operational costs while improving service quality. Conversely, Personalized Marketing is rapidly emerging as a key player in the industry, leveraging data analytics and machine learning to tailor marketing messages to individual customers, thereby significantly increasing conversion rates and customer engagement.</p>

<p>Customer Service Automation (Dominant) vs. Personalized Marketing (Emerging)</p>

<p>Customer Service Automation is a dominant force in the Applied AI in Retail & E-commerce market, providing crucial services such as 24/7 support, query resolution, and feedback collection. Its integration helps retailers streamline operations and significantly enhance customer experience. In contrast, Personalized Marketing represents an emerging trend, utilizing AI technologies to analyze consumer behavior and preferences to deliver personalized recommendations and advertisements. This evolving application not only boosts customer satisfaction but also drives sales growth, making it essential for retailers aiming to establish deeper connections with their clientele.</p>

By Technology: Machine Learning (Largest) vs. Natural Language Processing (Fastest-Growing)

<p>In the Applied AI in Retail & E-commerce Market, Machine Learning holds the largest share, leveraging large data sets to enhance customer personalization and operational efficiency. Natural Language Processing is emerging rapidly, utilizing text data to improve customer interactions and automate responses. Computer Vision, Robotic Process Automation, and Predictive Analytics also contribute, but they are yet to reach the same prominence as the top two segments.</p>

<p>Machine Learning: Dominant vs. Natural Language Processing: Emerging</p>

<p>Machine Learning (ML) stands as the cornerstone of the Applied AI segment, dominating current applications with its ability to analyze vast datasets for actionable insights, enabling retailers to optimize inventory and tailor marketing strategies. In contrast, Natural Language Processing (NLP) is gaining momentum as the fastest-growing area, transforming customer engagement through chatbots and automated support systems that comprehend and respond in human-like manners. While ML continues to refine existing processes, NLP is enhancing customer experience and operational capabilities, marking its importance in modern retail and e-commerce.</p>

By End Use: Online Retail (Largest) vs. Marketplaces (Fastest-Growing)

<p>The Applied AI in Retail & E-commerce market is significantly shaped by various end-use segments, with online retail holding the largest share. This segment benefits from increased consumer preference for digital shopping experiences and the enhancement of personalized recommendations driven by AI. Brick-and-mortar retail, while still relevant, lags in market share due to the shift towards online counterparts, although it maintains a crucial role in customer experience. Wholesale distribution and e-commerce platforms follow, with marketplaces rapidly gaining ground due to their ability to cater to diverse consumer needs effectively. The growth trends across these segments highlight a robust transformation in the retail landscape. Online retail continues to evolve as consumers seek seamless shopping experiences, while marketplaces are emerging as the fastest-growing due to their dynamic nature and competitive pricing strategies. Innovations in AI such as chatbots and inventory management are driving efficiency across all end-use segments, making them more appealing to both retailers and customers. As consumer habits continue to shift and technology advances, these segments will adapt to meet evolving demands, further influencing market dynamics.</p>

<p>E-commerce Platforms (Dominant) vs. Brick-and-Mortar Retail (Emerging)</p>

<p>E-commerce platforms remain dominant in the Applied AI in Retail & E-commerce market, characterized by their extensive reach and capability to leverage AI for enhancing user experience through personalized recommendations and automated customer engagement. These platforms harness vast amounts of consumer data to optimize product offerings and streamline operations. In contrast, brick-and-mortar retail is emerging, focusing on integrating AI to create a harmonious omnichannel experience for customers. Physical stores are now utilizing AI for in-store analytics and inventory management, adapting to consumer expectations in a post-pandemic world. Despite the challenges posed by online competition, brick-and-mortar retailers are striving to leverage technology to enhance customer engagement and loyalty.</p>

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

Regional Insights

North America : Innovation Hub for Retail AI

North America is poised to maintain its dominance in the Applied AI in Retail & E-commerce market, holding a significant market share of 22.5 in 2024. The region's growth is driven by rapid technological advancements, increasing consumer demand for personalized shopping experiences, and supportive regulatory frameworks. Companies are leveraging AI to enhance operational efficiency and customer engagement, making it a fertile ground for innovation. The competitive landscape is characterized by major players such as Amazon, Walmart, and eBay, who are investing heavily in AI technologies. The U.S. leads the charge, with Canada also emerging as a key player in the AI retail space. The presence of tech giants and a robust startup ecosystem further solidifies North America's position as a leader in Applied AI, fostering a culture of continuous improvement and adaptation.

Europe : Emerging Powerhouse in AI

Europe is rapidly evolving into a significant player in the Applied AI in Retail & E-commerce market, with a market size of 10.5. The region benefits from a strong regulatory environment that encourages innovation while ensuring consumer protection. Factors such as increasing online shopping trends and the demand for enhanced customer experiences are driving growth. European retailers are increasingly adopting AI solutions to optimize supply chains and personalize marketing strategies. Leading countries like Germany, the UK, and France are at the forefront of this transformation, with companies like Zalando and Shopify making substantial investments in AI technologies. The competitive landscape is diverse, with both established retailers and innovative startups vying for market share. As Europe continues to embrace AI, it is set to play a crucial role in shaping the future of retail and e-commerce.

Asia-Pacific : Dynamic Growth in Retail AI

The Asia-Pacific region is witnessing a dynamic shift in the Applied AI in Retail & E-commerce market, with a market size of 9.0. The growth is fueled by increasing internet penetration, mobile commerce, and a tech-savvy consumer base. Countries like China and Japan are leading the charge, supported by favorable government policies that promote digital transformation. The demand for AI-driven solutions is growing as retailers seek to enhance customer experiences and streamline operations. China, with giants like Alibaba and JD.com, is at the forefront of AI adoption in retail, while Japan's Rakuten is also making significant strides. The competitive landscape is characterized by rapid innovation and collaboration between tech firms and retailers. As the region continues to evolve, the integration of AI technologies is expected to reshape the retail landscape significantly.

Middle East and Africa : Emerging Market for AI Solutions

The Middle East and Africa (MEA) region is emerging as a promising market for Applied AI in Retail & E-commerce, with a market size of 2.75. The growth is driven by increasing smartphone penetration, a young population, and rising e-commerce activities. Governments in the region are also recognizing the potential of AI, implementing policies to foster innovation and attract investment in technology sectors. Countries like South Africa and the UAE are leading the way in AI adoption, with local retailers beginning to explore AI solutions for enhancing customer engagement and operational efficiency. The competitive landscape is still developing, with both local and international players entering the market. As the region continues to invest in AI technologies, it is poised for significant growth in the retail sector.

Key Players and Competitive Insights

The Applied AI in Retail & E-commerce Market is characterized by a rapidly evolving competitive landscape, driven by technological advancements and shifting consumer preferences. Major players such as Amazon (US), Alibaba (CN), and Walmart (US) are at the forefront, leveraging AI to enhance customer experiences and streamline operations. Amazon (US) continues to innovate with its AI-driven recommendation systems, while Alibaba (CN) focuses on integrating AI into its logistics and supply chain management. Walmart (US) emphasizes digital transformation through AI applications in inventory management and personalized marketing, collectively shaping a competitive environment that prioritizes efficiency and customer engagement.

The market structure appears moderately fragmented, with key players employing various business tactics to optimize their operations. Localizing manufacturing and enhancing supply chain efficiency are prevalent strategies among these companies. The collective influence of these major players fosters a competitive atmosphere where agility and responsiveness to market demands are crucial for success.

In November 2025, Amazon (US) announced the launch of its AI-powered virtual shopping assistant, designed to enhance customer interaction and streamline the purchasing process. This strategic move underscores Amazon's commitment to integrating advanced AI technologies to improve user experience and drive sales. The introduction of this assistant is likely to reinforce Amazon's market position by providing a more personalized shopping experience, which could lead to increased customer loyalty.

In October 2025, Alibaba (CN) unveiled its AI-driven smart logistics platform, aimed at optimizing delivery routes and reducing operational costs. This initiative reflects Alibaba's focus on enhancing its supply chain capabilities through AI, potentially leading to faster delivery times and improved customer satisfaction. The strategic importance of this development lies in its ability to position Alibaba as a leader in logistics efficiency, which is increasingly vital in the competitive e-commerce landscape.

In September 2025, Walmart (US) expanded its partnership with AI technology firms to enhance its predictive analytics capabilities. This collaboration aims to refine inventory management and demand forecasting, which are critical for maintaining operational efficiency. By investing in AI-driven analytics, Walmart is likely to improve its responsiveness to consumer trends, thereby solidifying its competitive edge in the retail sector.

As of December 2025, current trends in the Applied AI in Retail & E-commerce Market indicate a strong emphasis on digitalization, sustainability, and AI integration. Strategic alliances among key players are shaping the landscape, fostering innovation and collaboration. The shift from price-based competition to a focus on technological advancement and supply chain reliability is evident. Companies that prioritize innovation and customer-centric solutions are likely to thrive, as the market continues to evolve towards a more sophisticated and technology-driven future.

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

<p>The Applied AI in Retail & E-commerce Market is projected to grow at a 30.86% CAGR from 2024 to 2035, driven by enhanced customer personalization, operational efficiency, and data analytics advancements.</p>

New opportunities lie in:

  • <p>Automated inventory management systems leveraging AI for real-time stock optimization.</p>
  • <p>AI-driven customer insights platforms to enhance targeted marketing strategies.</p>
  • <p>Personalized shopping experiences through AI chatbots and virtual assistants.</p>

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

Market Segmentation

Applied AI in Retail & E-commerce Market End Use Outlook

  • Online Retail
  • Brick-and-Mortar Retail
  • Wholesale Distribution
  • E-commerce Platforms
  • Marketplaces

Applied AI in Retail & E-commerce Market Technology Outlook

  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • Robotic Process Automation
  • Predictive Analytics

Applied AI in Retail & E-commerce Market Application Outlook

  • Customer Service Automation
  • Personalized Marketing
  • Inventory Management
  • Fraud Detection
  • Supply Chain Optimization

Report Scope

MARKET SIZE 202444.75(USD Billion)
MARKET SIZE 202558.57(USD Billion)
MARKET SIZE 2035862.56(USD Billion)
COMPOUND ANNUAL GROWTH RATE (CAGR)30.86% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Billion
Key Companies ProfiledAmazon (US), Alibaba (CN), Walmart (US), JD.com (CN), eBay (US), Target (US), Zalando (DE), Shopify (CA), Rakuten (JP)
Segments CoveredApplication, Technology, End Use
Key Market OpportunitiesIntegration of personalized shopping experiences through advanced predictive analytics in Applied AI in Retail and E-commerce Market.
Key Market DynamicsRising integration of artificial intelligence enhances customer personalization and operational efficiency in retail and e-commerce.
Countries CoveredNorth America, Europe, APAC, South America, MEA

FAQs

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

The Applied AI in Retail &amp; 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 &amp; 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 &amp; 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
    1.  
  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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