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全球零售人工智慧市场：按解决方案、产品类型和最终用户 - 预测（~2030 年）
市场调查报告书
商品编码
1585121

全球零售人工智慧市场：按解决方案、产品类型和最终用户 - 预测（~2030 年）

Artificial Intelligence in Retail Market by Solution (Personalized Product Recommendation, Visual Search, Virtual Stores, Virtual Customer Assistant, CRM), Type (Generative AI, Other AI), End-user (Online, Offline) - Global Forecast to 2030
出版日期: | 出版商: MarketsandMarkets | 英文 307 Pages | 订单完成后即时交付

价格

预计2024年全球零售人工智慧市场规模将达311.2亿美元，2030年将达1,647.4亿美元，预计2024年至2030年复合年增长率为32.0%。

零售业人工智慧采用的关键驱动因素之一是消费者对个人化购物体验不断增长的需求。机器学习和自然语言处理等人工智慧技术使零售商能够分析大量消费者资料，以了解偏好和行为模式。这种资料主导的洞察力使零售商能够提供个人化的推荐、有针对性的促销和个人化的行销策略。对于希望透过零售市场的超个人化来提高客户参与和满意度的公司来说，人工智慧解决方案已变得至关重要。

调查范围
调查年份 2019-2030
基准年 2023年
预测期 2024-2030
单元 10亿美元
部分 产品、类型、业务能力、最终用户、区域
目标区域 北美、欧洲、亚太地区、中东/非洲、拉丁美洲

“在预测期内，行销和销售业务功能将在零售人工智慧市场中贡献最大的市场占有率。”

零售业人工智慧正在透过提供更好的工具和业务洞察力来提高客户参与、个人化行销工作和优化销售流程，从而改变行销和销售业务功能。人工智慧聊天机器人和人工智慧虚拟助理可以透过提供快速支援和引导整个购买流程来帮助改善客户体验。人工智慧将透过实现超个人化的宣传活动和产品推荐来彻底改变行销方式。亚马逊和 eBay 等公司使用人工智慧来分析客户资料和偏好，以帮助提供个人化广告、产品提案和促销。人工智慧的另一个应用是动态定价。透过动态定价，价格会像现实生活中一样频繁变化，具体取决于需求、竞争和客户行为。人工智慧还透过向相关客户发送有针对性的讯息来帮助管理客户忠诚度计画。生成式人工智慧用于自动创建行销内容，例如电子邮件和广告。处于利用人工智慧进行行销和销售前沿的主要企业包括阿里巴巴、H&M 和耐吉。

“图像搜寻解决方案预计将在预测期内实现最高的复合年增长率。”

图像搜寻采用人工智慧来改变购物体验，让客户更轻鬆地上传图像、搜寻产品和获取类似产品。这项技术在时尚产业和家居装饰中得到了广泛应用。人工智慧驱动的图像搜寻追踪客户的搜寻历史记录和需求，以提供客製化的解决方案。影像搜寻技术打通线上线下，让线上线下购物变得一样。消费者可以拍摄他们感兴趣的产品的图像，进行图像搜寻，并在线获取有关该产品的更多资讯。这使得顾客更容易购买到自己需要的产品，提供了更大的便利。零售商还可以使用图像搜寻进行库存管理，使他们能够了解当前库存并知道某些产品何时需要更新。像 ASOS 这样的领先电子商务公司正在实施影像搜寻技术来改善消费者的购物体验。

本报告研究和分析了全球零售人工智慧市场，提供了关键驱动因素和限制因素、竞争格局和未来趋势的资讯。

目录

第一章简介

第二章调查方法

第三章执行摘要

第 4 章重要考察

  • 对零售人工智慧市场主要企业来说具有吸引力的机会
  • 零售人工智慧市场：按产品分类
  • 零售人工智慧市场：按服务分类
  • 零售人工智慧市场：按业务功能划分
  • 零售人工智慧市场：按类型
  • 零售人工智慧市场：按解决方案分类
  • 零售人工智慧市场：按最终用户分类
  • 北美零售人工智慧市场排名前三的解决方案和服务

第五章市场概况及产业趋势

  • 介绍
  • 市场动态
    • 促进因素
    • 抑制因素
    • 机会
    • 任务
  • 影响客户业务的趋势/干扰
  • 价格分析
    • 平均销售价格趋势：按主要企业和解决方案分类
    • 主要企业参考价格分析
  • 供应链分析
  • 生态系统
  • 技术分析
    • 主要技术
    • 互补技术
    • 邻近技术
  • 专利分析
  • 贸易分析
    • 处理器和控制器导出场景
    • 处理器和控制器导入场景
  • 重大会议和活动（2024-2026）
  • 关税和监管环境
    • 关税资料(HSN: 854231) - 处理器、控制器
    • 监管机构、政府机构和其他组织
    • 主要规定
  • 波特五力分析
  • 主要相关利益者和采购标准
  • 零售业人工智慧的演变
  • 案例研究分析

第六章零售人工智慧市场：透过提供

  • 介绍
  • 解决方案
    • 个性化产品推荐
    • 客户关係管理
    • 图片搜寻
    • 虚拟客户助理
    • 价格优化
    • 供应链管理/需求计划
    • 虚拟商店
    • 智慧结帐
    • 其他解决方案
  • 服务
    • 专业服务
    • 託管服务

第七章零售人工智慧市场：按类型

  • 介绍
  • 人工智慧世代
  • 其他人工智慧
    • 判别性机器学习
    • 自然语言处理
    • 电脑视觉
    • 预测分析

第 8 章零售人工智慧市场：按业务功能划分

  • 介绍
  • 行销/销售
  • HR
  • 财务/会计
  • 管理
  • 网路安全

第 9 章零售人工智慧市场：按最终用户划分

  • 介绍
  • 在线的
  • 离线

第10章零售人工智慧市场：按地区

  • 介绍
  • 北美洲
    • 北美宏观经济展望
    • 美国
    • 加拿大
  • 欧洲
    • 欧洲宏观经济展望
    • 英国
    • 义大利
    • 德国
    • 法国
    • 西班牙
    • 北欧国家
    • 欧洲其他地区
  • 亚太地区
    • 亚太宏观经济展望
    • 中国
    • 日本
    • 印度
    • 澳洲/纽西兰
    • 韩国
    • 东南亚国协
    • 其他亚太地区
  • 中东/非洲
    • 中东和非洲宏观经济前景
    • 南非
    • 其他中东/非洲
  • 拉丁美洲
    • 拉丁美洲宏观经济展望
    • 巴西
    • 墨西哥
    • 阿根廷
    • 其他拉丁美洲

第十一章竞争格局

  • 介绍
  • 主要企业策略/主要企业
  • 收益分析
  • 市场占有率分析
  • 企业评价矩阵：主要企业（2023年）
  • 企业评估矩阵：Start-Ups/中小企业（2023）
  • 竞争格局及趋势
  • 品牌/产品比较
  • 公司评价及财务指标

第十二章 公司简介

  • 主要企业
    • IBM
    • AMAZON
    • SALESFORCE, INC.
    • ORACLE
    • MICROSOFT
    • GOOGLE
    • NVIDIA
    • ACCENTURE
    • SAP SE
    • SERVICENOW
    • INFOSYS
    • INTEL CORPORATION
    • AMD
    • HUAWEI
    • ALIBABA
    • FUJITSU
    • CAPGEMINI
    • TCS
    • TALKDESK
    • SYMPHONY AI
    • BLOOMREACH
    • C3.AI
  • Start-Ups/小型企业
    • VISENZE
    • PATHR.AI
    • VUE.AI
    • NEXTAIL
    • DAISY INTELLIGENCE
    • CRESTA
    • MASON
    • SYTE
    • TRAX RETAIL
    • FEEDZAI
    • SHOPIC

第十三章邻近/相关市场

  • 介绍
  • 人工智慧市场 - 世界预测（~2030）
    • 市场定义
    • 市场概况
  • 零售分析市场 - 全球预测（~2029）
    • 市场定义
    • 市场概况

第十四章附录

Product Code: TC 5669

The Artificial intelligence in retail market is estimated to be USD 31.12 billion in 2024 to USD 164.74 billion in 2030 at a CAGR of 32.0% from 2024 to 2030. One of the primary drivers for AI adoption in retail is the growing consumer demand for personalized shopping experiences. AI technologies such as machine learning and natural language processing enable retailers to analyze large volumes of consumer data to understand preferences and behavior patterns. This data-driven insight allows retailers to offer personalized recommendations, targeted promotions, and tailor-made marketing strategies. AI solutions are becoming essential for businesses seeking to enhance customer engagement and satisfaction due to hyper-personalization in the retail market.

Scope of the Report
Years Considered for the Study2019-2030
Base Year2023
Forecast Period2024-2030
Units ConsideredUSD (Billion)
SegmentsBy Offering, Type, Business Function, End-user and Region
Regions coveredNorth America, Europe, Asia Pacific, Middle East & Africa, and Latin America

"During the forecast period, the marketing and sales business function contributed the largest market share in the artificial intelligence in the retail market."

Al in retail is changing the marketing and sales business functions by offering superior tools and business insights that enhance customer engagement, personalize marketing efforts, and optimize sales processes. AI Chatbots and AI virtual assistants can help to improve customers' experience by offering prompt support and helping them navigate throughout the buying process. AI revolutionizes marketing by enabling hyper-personalized campaigns and product recommendations; companies such as Amazon and eBay use AI to analyze customer data and preferences, helping them deliver personalized ads, product suggestions, and promotions. Another application of AIis dynamic pricing, where the prices can change as frequently as in real life depending on the demand, competition, and customers' behavior. AI also assists in managing customer loyalty programs by targeting relevant customers with targeted messages. Generative AI is used to automate content creation for marketing, including emails and advertisements. Some key players at the forefront of using AI in marketing and sales include Alibaba, H&M, and Nike.

"The visual search solution is projected to register the highest CAGR during the forecast period."

Visual search employs AI to make it easier for customers to search for products by uploading images and getting similar products, changing the shopping experience. This technology showcased higher usage in the fashion industry and in home decor. Al-driven visual search tracks customer's search history and needs to provide customized solutions. Visual search technology makes shopping online and offline identical by interconnecting them. Consumers can snap images of the goods they are interested in and conduct a visual search to get their details online. This makes it easier for the customer to buy the needed products, thus increasing convenience. Retailers can also use visual search to manage their stock since they get to keep an eye on their current stock and know when certain products need to be renewed. E-commerce giants such as ASOS have implemented visual search technology to enhance the shopping experience among consumers.

"Middle East & Africa will register the highest growth rate during the forecast period."

Middle Eastern retail market is estimated to grow at a higher growth due to several key factors, such as governments promoting AI adoption and businesses heavily investing in UAE and KSA. The e-commerce sector also compels retailers to explore AI solutions to understand online consumer behavior better and optimize their digital marketing strategies. Additionally, retailers leverage data analytics to improve in-store layouts and visual merchandising, enhancing the overall shopping experience. Presight's strategic alliance with Intel aims to foster advanced AI solutions across the Middle East, indicating a strong trend toward harnessing AI for improved customer insights and enhanced in-store shopping experiences. Developing nations such as South Africa and the UAE are anticipated to see notable growth, driven by e-commerce advancements encouraging retailers to adopt AI-driven strategies.

Breakdown of primaries

The study contains insights from various industry experts, from solution vendors to Tier 1 companies. The break-up of the primaries is as follows:

  • By Company Type: Tier 1 - 62%, Tier 2 - 23%, and Tier 3 - 15%
  • By Designation: C-level -50%, D-level - 30%, and Managers - 20%
  • By Region: North America - 38%, Europe - 15%, Asia Pacific - 35%, Middle East & Africa- 7%, and Latin America- 5%.

The major players in the Artificial intelligence in retail market are Microsoft (US), IBM (US), Google (US), Amazon (US), Oracle (US), Salesforce (US), NVIDIA (US), SAP (Germany), Servicenow (US), Accenture (Ireland), Infosys (India), Alibaba (China), Intel (US), AMD (US), Fujitsu (Japan), Capgemini (France), TCS (India), Talkdesk (US), Symphony AI (US), Bloomreach (US), C3.AI (US), Visenze (Singapore), Pathr.ai (US), Vue.AI (US), Nextail (Spain), Daisy Intelligence (Canada), Cresta (US), Mason (US), Syte(Israel), Trax(Singapore), Feedzai(US) and Shopic(Israel). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their artificial intelligence in retail footprint.

Research Coverage

The market study covers the artificial intelligence in retail market size across different segments. It aims to estimate the market size and the growth potential across various segments, including offering, infrastructure platform, application performance platform, security platform, digital experience platform, workforce operations platform, vertical, and region. The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.

Key Benefits of Buying the Report

The report will help market leaders and new entrants with information on the closest approximations of the global artificial intelligence in retail market's revenue numbers and subsegments. It will also help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market's pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.

The report provides insights on the following pointers:

Analysis of key drivers (increasing adoption of conversational AI in retail for advice and recommendations, evolving consumer expectations and social commerce integration, enhancing checkout experiences with AI-powered automation, data-driven decision making), restraints (high implementation costs, data privacy and security), opportunities (AI-powered customer engagement, enhanced decision-making with predictive analytics, AI in supply chain optimization) and challenges (addressing rising theft and fraud issues, integration with legacy systems, ethical concerns in AI) influencing the growth of the artificial intelligence in retail market.

Product Development/Innovation: Detailed insights on upcoming technologies, research and development activities, and new product and service launches in the artificial intelligence in retail market. Market Development: Comprehensive information about lucrative markets - the report analyses various regions' artificial intelligence in retail markets. Market Diversification: Exhaustive information about new products and services, untapped geographies, recent developments, and investments in the artificial intelligence in retail market. Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players such as Microsoft (US), IBM (US), Google (US), Amazon (US), Oracle (US), Salesforce (US), NVIDIA (US), SAP (Germany), Servicenow (US), Accenture (Ireland), Infosys (India), Alibaba (China), Intel (US), AMD (US), Fujitsu (Japan), Capgemini (France), TCS (India), Talkdesk (US), Symphony AI (US), Bloomreach (US), C3.AI (US), Visenze (Singapore), Pathr.ai (US), Vue.AI (US), Nextail (Spain), Daisy Intelligence (Canada), Cresta (US), Mason (US), Syte (Israel), Trax (Singapore), Feedzai (US) and Shopic (Israel).

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 STUDY OBJECTIVES
  • 1.2 MARKET DEFINITION
  • 1.3 STUDY SCOPE
    • 1.3.1 MARKET SEGMENTATION
    • 1.3.2 INCLUSIONS AND EXCLUSIONS
  • 1.4 YEARS CONSIDERED
  • 1.5 CURRENCY CONSIDERED
  • 1.6 STAKEHOLDERS

2 RESEARCH METHODOLOGY

  • 2.1 RESEARCH DATA
    • 2.1.1 SECONDARY DATA
      • 2.1.1.1 Key data from secondary sources
    • 2.1.2 PRIMARY DATA
      • 2.1.2.1 Breakup of primary interviews
      • 2.1.2.2 Primary interviews with experts
      • 2.1.2.3 Key insights from industry experts
  • 2.2 MARKET SIZE ESTIMATION METHODOLOGY
    • 2.2.1 TOP-DOWN APPROACH
      • 2.2.1.1 Supply-side analysis
    • 2.2.2 BOTTOM-UP APPROACH
      • 2.2.2.1 Demand-side analysis
  • 2.3 DATA TRIANGULATION
  • 2.4 RESEARCH ASSUMPTIONS
  • 2.5 RESEARCH LIMITATIONS
  • 2.6 RISK ASSESSMENT

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

  • 4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • 4.2 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING
  • 4.3 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE
  • 4.4 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION
  • 4.5 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE
  • 4.6 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION
  • 4.7 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY END USER
  • 4.8 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, TOP THREE SOLUTIONS AND SERVICES

5 MARKET OVERVIEW AND INDUSTRY TRENDS

  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    • 5.2.1 DRIVERS
      • 5.2.1.1 Increasing adoption of conversational AI in retail for advice and recommendations
      • 5.2.1.2 Evolving consumer expectations and social media integration
      • 5.2.1.3 Enhancing checkout experiences with AI-powered automation
      • 5.2.1.4 Data-driven decision-making
    • 5.2.2 RESTRAINTS
      • 5.2.2.1 High implementation costs
      • 5.2.2.2 Data privacy and security
    • 5.2.3 OPPORTUNITIES
      • 5.2.3.1 AI-powered customer engagement
      • 5.2.3.2 Enhanced decision-making with predictive analytics
      • 5.2.3.3 AI in supply chain optimization
    • 5.2.4 CHALLENGES
      • 5.2.4.1 Rising theft and fraud issues
      • 5.2.4.2 Complexity in integrating with legacy systems
      • 5.2.4.3 Ethical concerns in AI
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.4 PRICING ANALYSIS
    • 5.4.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
    • 5.4.2 INDICATIVE PRICING ANALYSIS OF ARTIFICIAL INTELLIGENCE IN RETAIL KEY PLAYERS
  • 5.5 SUPPLY CHAIN ANALYSIS
  • 5.6 ECOSYSTEM
  • 5.7 TECHNOLOGY ANALYSIS
    • 5.7.1 KEY TECHNOLOGIES
      • 5.7.1.1 Conversational AI
      • 5.7.1.2 Autonomous AI & autonomous agent
      • 5.7.1.3 AutoML
    • 5.7.2 COMPLEMENTARY TECHNOLOGIES
      • 5.7.2.1 Edge computing
      • 5.7.2.2 Big data analytics
      • 5.7.2.3 Cloud computing
    • 5.7.3 ADJACENT TECHNOLOGIES
      • 5.7.3.1 Blockchain
      • 5.7.3.2 Cybersecurity solutions
  • 5.8 PATENT ANALYSIS
    • 5.8.1 LIST OF MAJOR PATENTS
  • 5.9 TRADE ANALYSIS
    • 5.9.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
    • 5.9.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
  • 5.10 KEY CONFERENCES AND EVENTS, 2024-2026
  • 5.11 TARIFF AND REGULATORY LANDSCAPE
    • 5.11.1 TARIFF DATA (HSN: 854231) - PROCESSORS AND CONTROLLERS
    • 5.11.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    • 5.11.3 KEY REGULATIONS
      • 5.11.3.1 North America
        • 5.11.3.1.1 SCR 17: Artificial Intelligence Bill (California)
        • 5.11.3.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
        • 5.11.3.1.3 National Artificial Intelligence Initiative Act (NAIIA)
        • 5.11.3.1.4 The Artificial Intelligence and Data Act (AIDA) - Canada
      • 5.11.3.2 Europe
        • 5.11.3.2.1 The European Union (EU) - Artificial Intelligence Act (AIA)
        • 5.11.3.2.2 General Data Protection Regulation (Europe)
      • 5.11.3.3 Asia Pacific
        • 5.11.3.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
        • 5.11.3.3.2 The National AI Strategy (Singapore)
        • 5.11.3.3.3 The Hiroshima AI Process Comprehensive Policy Framework (Japan)
      • 5.11.3.4 Middle East & Africa
        • 5.11.3.4.1 The National Strategy for Artificial Intelligence (UAE)
        • 5.11.3.4.2 The National Artificial Intelligence Strategy (Qatar)
        • 5.11.3.4.3 The AI Ethics Principles and Guidelines (Dubai)
      • 5.11.3.5 Latin America
        • 5.11.3.5.1 The Santiago Declaration (Chile)
        • 5.11.3.5.2 The Brazilian Artificial Intelligence Strategy (EBIA)
  • 5.12 PORTER'S FIVE FORCES' ANALYSIS
      • 5.12.1.1 Threat of new entrants
      • 5.12.1.2 Threat of substitutes
      • 5.12.1.3 Bargaining power of buyers
      • 5.12.1.4 Bargaining power of suppliers
      • 5.12.1.5 Intensity of competitive rivalry
  • 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
    • 5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
    • 5.13.2 BUYING CRITERIA
  • 5.14 EVOLUTION OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • 5.15 CASE STUDY ANALYSIS
    • 5.15.1 TARGET LEVERAGED GOOGLE CLOUD TO ENHANCE CUSTOMER EXPERIENCES AND ACHIEVE SIGNIFICANT REVENUE GROWTH
    • 5.15.2 PRADA GROUP IMPROVED CUSTOMER EXPERIENCE USING ORACLE'S CLOUD SOLUTIONS FOR PERSONALIZED RETAIL STRATEGIES
    • 5.15.3 PEPE JEANS INDIA AUGMENTED ONLINE SHOPPING WITH SALESFORCE BY FOCUSING ON DIRECT CONSUMER ENGAGEMENT AND PERSONALIZATION
    • 5.15.4 WALMART ENHANCED DIGITAL SHOPPING WITH MICROSOFT'S GENERATIVE AI FOR PERSONALIZED SEARCH AND IMPROVED CX
    • 5.15.5 AI-POWERED CHECKOUT-FREE SHOPPING SOLUTION TRANSFORMED RETAIL OPERATIONS OF ITREX GROUP

6 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING

  • 6.1 INTRODUCTION
    • 6.1.1 OFFERINGS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 6.2 SOLUTIONS
    • 6.2.1 PERSONALIZED PRODUCT RECOMMENDATIONS
      • 6.2.1.1 AI to help tailor product suggestions based on customer behavior and drive engagement and sales in retail
    • 6.2.2 CUSTOMER RELATIONSHIP MANAGEMENT
      • 6.2.2.1 AI-driven CRM to automate personalized marketing and customer segmentation and churn prevention strategies
    • 6.2.3 VISUAL SEARCH
      • 6.2.3.1 Visual search to enable customers find products using images and enhance discovery and shopping experiences
    • 6.2.4 VIRTUAL CUSTOMER ASSISTANT
      • 6.2.4.1 AI-powered virtual assistants to offer real-time customer support, improving response times and personalization
    • 6.2.5 PRICE OPTIMIZATION
      • 6.2.5.1 AI-powered price optimization to help retailers adjust prices dynamically based on competition, demand, and market conditions
    • 6.2.6 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING
      • 6.2.6.1 AI to optimize retail supply chains by predicting demand and streamlining inventory management
    • 6.2.7 VIRTUAL STORES
      • 6.2.7.1 AI to offer immersive shopping experiences with AR and VR technologies
    • 6.2.8 SMART CHECKOUT
      • 6.2.8.1 AI to eliminate wait times and enable frictionless shopping experiences
    • 6.2.9 OTHER SOLUTIONS
  • 6.3 SERVICES
    • 6.3.1 PROFESSIONAL SERVICES
      • 6.3.1.1 Professional services in AI for retail to help businesses effectively integrate advanced AI technologies into their operations
      • 6.3.1.2 Training & consulting
        • 6.3.1.2.1 Optimizing IT operations for improved business performance to propel market
      • 6.3.1.3 System integration & deployment
        • 6.3.1.3.1 System integration & deployment services to help retailers seamlessly incorporate AI solutions into their existing infrastructure
      • 6.3.1.4 Support & maintenance
        • 6.3.1.4.1 Support & maintenance services in AI for retail to ensure that AI systems function optimally post-deployment
    • 6.3.2 MANAGED SERVICES
      • 6.3.2.1 Managed services in AI to provide continuous monitoring and management of AI systems for scalability and efficiency

7 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE

  • 7.1 INTRODUCTION
    • 7.1.1 TYPES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 7.2 GENERATIVE AI
  • 7.3 OTHER AI
    • 7.3.1 DISCRIMINATIVE MACHINE LEARNING
      • 7.3.1.1 ML to optimize retail with personalized recommendations, dynamic pricing, and efficient demand forecasting
    • 7.3.2 NATURAL LANGUAGE PROCESSING
      • 7.3.2.1 NLP to enhance customer service with AI chatbots and sentiment analysis for personalized, real-time engagement
    • 7.3.3 COMPUTER VISION
      • 7.3.3.1 Computer vision to revolutionize retail with smart checkouts, visual search, and in-store analytics to boost efficiency
    • 7.3.4 PREDICTIVE ANALYTICS
      • 7.3.4.1 Predictive analytics to improve demand forecasting, price optimization, and customer targeting in retail operations

8 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION

  • 8.1 INTRODUCTION
    • 8.1.1 BUSINESS FUNCTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 8.2 MARKETING & SALES
    • 8.2.1 AI TO IMPROVE PERSONALIZED CAMPAIGNS, PRODUCT RECOMMENDATIONS, AND DYNAMIC PRICING IN RETAIL
  • 8.3 HUMAN RESOURCES
    • 8.3.1 AI TO AUTOMATE RECRUITMENT, WORKFORCE OPTIMIZATION, AND PERSONALIZED TRAINING IN RETAIL HR
  • 8.4 FINANCE & ACCOUNTING
    • 8.4.1 AI TO SYSTEMATIZE FINANCIAL PROCESSES, SUCH AS BILLING, FORECASTING, AND FRAUD DETECTION IN RETAIL
  • 8.5 OPERATIONS
    • 8.5.1 AI TO ENHANCE SUPPLY CHAIN OPTIMIZATION, INVENTORY MANAGEMENT, AND LOGISTICS IN RETAIL OPERATIONS
  • 8.6 CYBERSECURITY
    • 8.6.1 AI TO STRENGTHEN FRAUD DETECTION, DATA SECURITY, AND BIOMETRIC AUTHENTICATION IN RETAIL CYBERSECURITY

9 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY END USER

  • 9.1 INTRODUCTION
    • 9.1.1 END USERS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 9.2 ONLINE
    • 9.2.1 AI TO REVOLUTIONIZE ONLINE RETAIL BY IMPROVING SHOPPING EXPERIENCE THROUGH PERSONALIZATION, INVENTORY MANAGEMENT, AND REAL-TIME CUSTOMER SUPPORT
  • 9.3 OFFLINE
    • 9.3.1 ESSENTIAL SECURITY TOOLS TO MONITOR NETWORK TRAFFIC FOR THREATS
    • 9.3.2 SUPERMARKETS & HYPERMARKETS
      • 9.3.2.1 AI to improve inventory management, customer experience, and operational efficiency with smart checkout and predictive analytics
    • 9.3.3 SPECIALTY STORES
      • 9.3.3.1 AI to personalize shopping experiences and optimize inventory management in specialty stores
    • 9.3.4 CONVENIENCE STORES
      • 9.3.4.1 Smart checkout, dynamic pricing, and improved inventory management to ensure operational efficiency and quick service in convenience stores
    • 9.3.5 OTHER OFFLINE STORES

10 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION

  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
    • 10.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
    • 10.2.2 US
      • 10.2.2.1 Technological advancements and strategic partnerships to propel market
    • 10.2.3 CANADA
      • 10.2.3.1 Need for predicting product demand, optimizing inventory, and enhancing personalized customer experiences to drive market
  • 10.3 EUROPE
    • 10.3.1 EUROPE: MACROECONOMIC OUTLOOK
    • 10.3.2 UK
      • 10.3.2.1 Need to enhance customer experiences, streamline operations, and optimize inventory management to accelerate market growth
    • 10.3.3 ITALY
      • 10.3.3.1 Increasing demand for enhanced customer experiences, operational efficiency, and data-driven decision-making to fuel market growth
    • 10.3.4 GERMANY
      • 10.3.4.1 Need to enhance operational efficiency, customer engagement, and government initiatives to enhance market growth
    • 10.3.5 FRANCE
      • 10.3.5.1 Integration of AI to enhance customer experiences through personalized recommendations, dynamic pricing, and improved inventory management
    • 10.3.6 SPAIN
      • 10.3.6.1 Strong emphasis on predictive analytics and focus on mitigating risks and enhancing decision-making investments in retail sector to boost market growth
    • 10.3.7 NORDIC COUNTRIES
      • 10.3.7.1 Increasing consumer expectations for personalized experiences and operational efficiency to foster market growth
    • 10.3.8 REST OF EUROPE
  • 10.4 ASIA PACIFIC
    • 10.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
    • 10.4.2 CHINA
      • 10.4.2.1 Strong government support for AI technology, rapid digitalization, and growing consumer demand for personalized and efficient retail experiences to fuel market growth
    • 10.4.3 JAPAN
      • 10.4.3.1 Labor shortages arising due to aging population, push for operational efficiency in retail sector, and government investments and initiatives to bolster market
    • 10.4.4 INDIA
      • 10.4.4.1 Rapid eCommerce growth, increasing smartphone penetration, and demand for personalized customer experiences to augment market growth
    • 10.4.5 AUSTRALIA & NEW ZEALAND
      • 10.4.5.1 Increasing eCommerce activity and need for enhanced customer experience to propel market
    • 10.4.6 SOUTH KOREA
      • 10.4.6.1 Advanced technological infrastructure, high internet penetration, and implementation of AI National Strategy to accelerate market
    • 10.4.7 ASEAN COUNTRIES
    • 10.4.8 REST OF ASIA PACIFIC
  • 10.5 MIDDLE EAST & AFRICA
    • 10.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
      • 10.5.1.1 UAE
        • 10.5.1.1.1 Investments and collaborations aimed at enhancing retail experiences through AI technologies to drive market
      • 10.5.1.2 KSA
        • 10.5.1.2.1 Substantial investments in AI and establishment of Vision 2030 to foster market growth
      • 10.5.1.3 Kuwait
        • 10.5.1.3.1 Rapid development of Kuwait Vision 2035 to fuel demand for AI in retail market
      • 10.5.1.4 Bahrain
        • 10.5.1.4.1 Strategic location, supportive government policies, and growing eCommerce industry to drive market
    • 10.5.2 SOUTH AFRICA
      • 10.5.2.1 Rise of AI and related technologies during COVID-19 to fuel market growth
    • 10.5.3 REST OF MIDDLE EAST & AFRICA
  • 10.6 LATIN AMERICA
    • 10.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
    • 10.6.2 BRAZIL
      • 10.6.2.1 Influx of foreign eCommerce platforms to boost demand for AI in retail market
    • 10.6.3 MEXICO
      • 10.6.3.1 Embracing emerging technologies with notable funding from both domestic and international investors to bolster market growth
    • 10.6.4 ARGENTINA
      • 10.6.4.1 Focus on advancing digital infrastructure to drive market
    • 10.6.5 REST OF LATIN AMERICA

11 COMPETITIVE LANDSCAPE

  • 11.1 INTRODUCTION
  • 11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
    • 11.2.1 OVERVIEW OF STRATEGIES ADOPTED BY KEY ARTIFICIAL INTELLIGENCE IN RETAIL MARKET VENDORS
  • 11.3 REVENUE ANALYSIS
  • 11.4 MARKET SHARE ANALYSIS
    • 11.4.1 MARKET RANKING ANALYSIS
  • 11.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    • 11.5.1 STARS
    • 11.5.2 EMERGING LEADERS
    • 11.5.3 PERVASIVE PLAYERS
    • 11.5.4 PARTICIPANTS
    • 11.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
      • 11.5.5.1 Company footprint
      • 11.5.5.2 Type footprint
      • 11.5.5.3 Offering footprint
      • 11.5.5.4 Regional footprint
  • 11.6 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
    • 11.6.1 PROGRESSIVE COMPANIES
    • 11.6.2 RESPONSIVE COMPANIES
    • 11.6.3 DYNAMIC COMPANIES
    • 11.6.4 STARTING BLOCKS
    • 11.6.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023
      • 11.6.5.1 Key start-ups/SMEs
      • 11.6.5.2 Competitive benchmarking of key start-ups/SMEs
  • 11.7 COMPETITIVE SCENARIOS AND TRENDS
    • 11.7.1 PRODUCT LAUNCHES & ENHANCEMENTS
    • 11.7.2 DEALS
  • 11.8 BRAND/PRODUCT COMPARISON
  • 11.9 COMPANY VALUATION AND FINANCIAL METRICS

12 COMPANY PROFILES

  • 12.1 KEY PLAYERS
    • 12.1.1 IBM
      • 12.1.1.1 Business overview
      • 12.1.1.2 Products/Solutions/Services offered
      • 12.1.1.3 Recent developments
        • 12.1.1.3.1 Product enhancements
        • 12.1.1.3.2 Deals
      • 12.1.1.4 MnM view
        • 12.1.1.4.1 Right to win
        • 12.1.1.4.2 Strategic choices
        • 12.1.1.4.3 Weaknesses and competitive threats
    • 12.1.2 AMAZON
      • 12.1.2.1 Business overview
      • 12.1.2.2 Products/Solutions/Services offered
        • 12.1.2.2.1 Deals
        • 12.1.2.2.2 Other deals/developments
      • 12.1.2.3 MnM view
        • 12.1.2.3.1 Right to win
        • 12.1.2.3.2 Strategic choices
        • 12.1.2.3.3 Weaknesses and competitive threats
    • 12.1.3 SALESFORCE, INC.
      • 12.1.3.1 Business overview
      • 12.1.3.2 Products/Solutions/Services offered
      • 12.1.3.3 Recent developments
        • 12.1.3.3.1 Product launches and enhancements
        • 12.1.3.3.2 Deals
    • 12.1.4 ORACLE
      • 12.1.4.1 Business overview
      • 12.1.4.2 Products/Solutions/Services offered
      • 12.1.4.3 Recent developments
        • 12.1.4.3.1 Deals
    • 12.1.5 MICROSOFT
      • 12.1.5.1 Business overview
      • 12.1.5.2 Products/Solutions/Services offered
      • 12.1.5.3 Recent developments
        • 12.1.5.3.1 Deals
      • 12.1.5.4 MnM view
        • 12.1.5.4.1 Right to win
        • 12.1.5.4.2 Strategic choices
        • 12.1.5.4.3 Weaknesses and competitive threats
    • 12.1.6 GOOGLE
      • 12.1.6.1 Business overview
      • 12.1.6.2 Products/Solutions/Services offered
      • 12.1.6.3 Recent developments
        • 12.1.6.3.1 Product enhancements
        • 12.1.6.3.2 Deals
      • 12.1.6.4 MnM view
        • 12.1.6.4.1 Right to win
        • 12.1.6.4.2 Strategic choices
        • 12.1.6.4.3 Weaknesses and competitive threats
    • 12.1.7 NVIDIA
      • 12.1.7.1 Business overview
      • 12.1.7.2 Products/Solutions/Services offered
      • 12.1.7.3 Recent developments
        • 12.1.7.3.1 Deals
      • 12.1.7.4 MnM view
        • 12.1.7.4.1 Right to win
        • 12.1.7.4.2 Strategic choices
        • 12.1.7.4.3 Weaknesses and competitive threats
    • 12.1.8 ACCENTURE
      • 12.1.8.1 Business overview
      • 12.1.8.2 Products/Solutions/Services offered
      • 12.1.8.3 Recent developments
        • 12.1.8.3.1 Deals
    • 12.1.9 SAP SE
      • 12.1.9.1 Business overview
      • 12.1.9.2 Products/Solutions/Services offered
      • 12.1.9.3 Recent developments
        • 12.1.9.3.1 Deals
    • 12.1.10 SERVICENOW
      • 12.1.10.1 Business overview
      • 12.1.10.2 Products/Solutions/Services offered
      • 12.1.10.3 Recent developments
        • 12.1.10.3.1 Product enhancements
        • 12.1.10.3.2 Deals
    • 12.1.11 INFOSYS
      • 12.1.11.1 Business overview
      • 12.1.11.2 Products/Solutions/Services offered
      • 12.1.11.3 Recent developments
        • 12.1.11.3.1 Deals
    • 12.1.12 INTEL CORPORATION
      • 12.1.12.1 Business overview
      • 12.1.12.2 Products/Solutions/Services offered
      • 12.1.12.3 Recent developments
        • 12.1.12.3.1 Product launches
        • 12.1.12.3.2 Deals
    • 12.1.13 AMD
      • 12.1.13.1 Business overview
      • 12.1.13.2 Products/Solutions/Services offered
      • 12.1.13.3 Recent developments
        • 12.1.13.3.1 Product enhancements
        • 12.1.13.3.2 Deals
    • 12.1.14 HUAWEI
      • 12.1.14.1 Business overview
      • 12.1.14.2 Products/Solutions/Services offered
      • 12.1.14.3 Recent developments
        • 12.1.14.3.1 Product launches
    • 12.1.15 ALIBABA
    • 12.1.16 FUJITSU
    • 12.1.17 CAPGEMINI
    • 12.1.18 TCS
    • 12.1.19 TALKDESK
    • 12.1.20 SYMPHONY AI
    • 12.1.21 BLOOMREACH
    • 12.1.22 C3.AI
  • 12.2 START-UPS/SMES
    • 12.2.1 VISENZE
    • 12.2.2 PATHR.AI
    • 12.2.3 VUE.AI
    • 12.2.4 NEXTAIL
    • 12.2.5 DAISY INTELLIGENCE
    • 12.2.6 CRESTA
    • 12.2.7 MASON
    • 12.2.8 SYTE
    • 12.2.9 TRAX RETAIL
    • 12.2.10 FEEDZAI
    • 12.2.11 SHOPIC

13 ADJACENT/RELATED MARKETS

  • 13.1 INTRODUCTION
  • 13.2 ARTIFICIAL INTELLIGENCE MARKET - GLOBAL FORECAST TO 2030
    • 13.2.1 MARKET DEFINITION
    • 13.2.2 MARKET OVERVIEW
      • 13.2.2.1 Artificial intelligence market, by offering
      • 13.2.2.2 Artificial intelligence market, by technology
      • 13.2.2.3 Artificial intelligence market, by business function
      • 13.2.2.4 Artificial intelligence market, by vertical
      • 13.2.2.5 Artificial intelligence market, by region
  • 13.3 RETAIL ANALYTICS MARKET - GLOBAL FORECAST TO 2029
    • 13.3.1 MARKET DEFINITION
    • 13.3.2 MARKET OVERVIEW
      • 13.3.2.1 Retail analytics market, by offering
      • 13.3.2.2 Retail analytics market, by business function
      • 13.3.2.3 Retail analytics market, by application
      • 13.3.2.4 Retail analytics market, by end user
      • 13.3.2.5 Retail analytics market, by region

14 APPENDIX

  • 14.1 DISCUSSION GUIDE
  • 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 14.3 CUSTOMIZATION OPTIONS
  • 14.4 RELATED REPORTS
  • 14.5 AUTHOR DETAILS

List of Tables

  • TABLE 1 USD EXCHANGE RATES, 2021-2023
  • TABLE 2 PRIMARY INTERVIEWS WITH EXPERTS
  • TABLE 3 RESEARCH ASSUMPTIONS
  • TABLE 4 FACTOR ANALYSIS
  • TABLE 5 AVERAGE SELLING PRICE OF ARTIFICIAL INTELLIGENCE IN RETAIL SOLUTIONS
  • TABLE 6 INDICATIVE PRICING ANALYSIS OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • TABLE 7 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: ECOSYSTEM
  • TABLE 8 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DETAILED LIST OF CONFERENCES AND EVENTS, 2024-2026
  • TABLE 9 TARIFF RELATED TO PROCESSORS AND CONTROLLERS (HSN: 854231), 2023
  • TABLE 10 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 11 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 12 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 13 REST OF THE WORLD: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 14 IMPACT OF EACH FORCE ON ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • TABLE 15 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE SOLUTIONS
  • TABLE 16 KEY BUYING CRITERIA FOR TOP THREE SOLUTIONS
  • TABLE 17 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 18 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 19 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 20 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 21 SOLUTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 22 SOLUTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 23 PERSONALIZED PRODUCT RECOMMENDATIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 24 PERSONALIZED PRODUCT RECOMMENDATIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 25 CUSTOMER RELATIONSHIP MANAGEMENT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 26 CUSTOMER RELATIONSHIP MANAGEMENT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 27 VISUAL SEARCH: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 28 VISUAL SEARCH: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 29 VIRTUAL CUSTOMER ASSISTANT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 30 VIRTUAL CUSTOMER ASSISTANT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 31 PRICE OPTIMIZATION: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 32 PRICE OPTIMIZATION: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 33 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 34 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 35 VIRTUAL STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 36 VIRTUAL STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 37 SMART CHECKOUT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 38 SMART CHECKOUT: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 39 OTHER SOLUTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 40 OTHER SOLUTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 41 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 42 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 43 SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 44 SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 45 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 46 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 47 PROFESSIONAL SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 48 PROFESSIONAL SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 49 MANAGED SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 50 MANAGED SERVICES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 51 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 52 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 53 GENERATIVE AI: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 54 GENERATIVE AI: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 55 OTHER AI: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 56 OTHER AI: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 57 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 58 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 59 MARKETING & SALES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 60 MARKETING & SALES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 61 HUMAN RESOURCES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 62 HUMAN RESOURCES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 63 FINANCE & ACCOUNTING: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 64 FINANCE & ACCOUNTING: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 65 OPERATIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 66 OPERATIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 67 CYBERSECURITY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 68 CYBERSECURITY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 69 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY END USER, 2019-2023 (USD MILLION)
  • TABLE 70 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY END USER, 2024-2030 (USD MILLION)
  • TABLE 71 ONLINE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 72 ONLINE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 73 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 74 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 75 OFFLINE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 76 OFFLINE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 77 SUPERMARKETS & HYPERMARKETS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 78 SUPERMARKETS & HYPERMARKETS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 79 SPECIALTY STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 80 SPECIALTY STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 81 CONVENIENCE STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 82 CONVENIENCE STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 83 OTHER OFFLINE STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 84 OTHER OFFLINE STORES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 85 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 86 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2024-2030 (USD MILLION)
  • TABLE 87 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 88 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 89 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 90 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 91 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 92 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 93 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 94 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 95 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 96 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 97 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 98 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 99 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 100 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 101 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 102 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 103 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 104 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 105 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 106 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 107 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 108 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 109 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 110 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 111 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 112 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 113 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 114 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 115 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 116 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 117 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 118 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 119 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 120 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 121 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 122 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 123 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 124 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 125 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 126 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 127 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 128 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 129 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 130 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 131 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 132 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 133 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 134 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 135 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 136 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 137 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY/SUBREGION, 2019-2023 (USD MILLION)
  • TABLE 138 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY/SUBREGION, 2024-2030 (USD MILLION)
  • TABLE 139 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 140 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 141 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 142 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 143 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 144 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 145 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 146 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 147 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 148 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 149 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 150 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 151 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 152 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 153 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 154 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 155 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 156 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 157 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 158 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 159 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 160 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 161 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 162 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 163 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 164 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 165 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 166 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 167 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 168 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 169 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 170 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 171 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 172 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 173 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 174 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 175 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 176 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 177 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 178 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 179 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 180 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 181 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 182 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 183 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 184 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 185 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 186 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 187 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY/SUBREGION, 2019-2023 (USD MILLION)
  • TABLE 188 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY/SUBREGION, 2024-2030 (USD MILLION)
  • TABLE 189 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 190 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 191 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 192 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 193 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 194 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 195 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 196 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 197 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 198 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 199 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 200 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 201 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 202 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 203 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 204 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 205 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 206 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 207 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 208 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 209 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 210 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 211 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 212 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 213 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 214 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 215 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 216 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 217 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 218 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 219 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 220 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 221 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 222 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 223 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 224 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 225 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 226 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 227 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 228 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 229 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 230 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 231 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 232 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 233 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 234 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 235 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 236 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 237 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 238 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 239 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 240 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 241 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 242 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 243 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 244 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 245 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 246 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 247 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 248 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 249 KSA: AI IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 250 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 251 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 252 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 253 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 254 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 255 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 256 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 257 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 258 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 259 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 260 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 261 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 262 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 263 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 264 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 265 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 266 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 267 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 268 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 269 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 270 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 271 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2019-2023 (USD MILLION)
  • TABLE 272 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY COUNTRY, 2024-2030 (USD MILLION)
  • TABLE 273 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 274 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2024-2030 (USD MILLION)
  • TABLE 275 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019-2023 (USD MILLION)
  • TABLE 276 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2024-2030 (USD MILLION)
  • TABLE 277 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2019-2023 (USD MILLION)
  • TABLE 278 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SERVICE, 2024-2030 (USD MILLION)
  • TABLE 279 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2019-2023 (USD MILLION)
  • TABLE 280 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024-2030 (USD MILLION)
  • TABLE 281 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2019-2023 (USD MILLION)
  • TABLE 282 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024-2030 (USD MILLION)
  • TABLE 283 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 284 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD MILLION)
  • TABLE 285 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2019-2023 (USD MILLION)
  • TABLE 286 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024-2030 (USD MILLION)
  • TABLE 287 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2019-2023 (USD MILLION)
  • TABLE 288 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFLINE, 2024-2030 (USD MILLION)
  • TABLE 289 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DEGREE OF COMPETITION
  • TABLE 290 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: TYPE FOOTPRINT
  • TABLE 291 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: OFFERING FOOTPRINT
  • TABLE 292 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: REGIONAL FOOTPRINT
  • TABLE 293 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DETAILED LIST OF KEY START-UPS/SMES
  • TABLE 294 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: COMPETITIVE BENCHMARKING OF KEY START-UPS/SMES
  • TABLE 295 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, JUNE 2022-OCTOBER 2024
  • TABLE 296 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DEALS, JUNE 2022-OCTOBER 2024
  • TABLE 297 IBM: COMPANY OVERVIEW
  • TABLE 298 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 299 IBM: PRODUCT ENHANCEMENTS
  • TABLE 300 IBM: DEALS
  • TABLE 301 AMAZON: COMPANY OVERVIEW
  • TABLE 302 AMAZON: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 303 AMAZON: DEALS
  • TABLE 304 AMAZON: OTHER DEALS/DEVELOPMENTS
  • TABLE 305 SALESFORCE: COMPANY OVERVIEW
  • TABLE 306 SALESFORCE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 307 SALESFORCE: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 308 SALESFORCE: DEALS
  • TABLE 309 ORACLE: COMPANY OVERVIEW
  • TABLE 310 ORACLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 311 ORACLE: DEALS
  • TABLE 312 MICROSOFT: COMPANY OVERVIEW
  • TABLE 313 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 314 MICROSOFT: PRODUCT ENHANCEMENTS
  • TABLE 315 MICROSOFT: DEALS
  • TABLE 316 GOOGLE: COMPANY OVERVIEW
  • TABLE 317 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 318 GOOGLE: PRODUCT LAUNCHES
  • TABLE 319 GOOGLE: DEALS
  • TABLE 320 NVIDIA: COMPANY OVERVIEW
  • TABLE 321 NVIDIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 322 NVIDIA: DEALS
  • TABLE 323 ACCENTURE: COMPANY OVERVIEW
  • TABLE 324 ACCENTURE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 325 ACCENTURE: DEALS
  • TABLE 326 SAP SE: COMPANY OVERVIEW
  • TABLE 327 SAP SE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 328 SAP SE: DEALS
  • TABLE 329 SERVICENOW: COMPANY OVERVIEW
  • TABLE 330 SERVICENOW: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 331 SERVICENOW: PRODUCT ENHANCEMENTS
  • TABLE 332 SERVICENOW: DEALS
  • TABLE 333 INFOSYS: COMPANY OVERVIEW
  • TABLE 334 INFOSYS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 335 INFOSYS: DEALS
  • TABLE 336 INTEL: COMPANY OVERVIEW
  • TABLE 337 INTEL: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 338 INTEL: PRODUCT LAUNCHES
  • TABLE 339 INTEL: DEALS
  • TABLE 340 AMD: COMPANY OVERVIEW
  • TABLE 341 AMD: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 342 AMD: PRODUCT ENHANCEMENTS
  • TABLE 343 AMD: DEALS
  • TABLE 344 HUAWEI: COMPANY OVERVIEW
  • TABLE 345 HUAWEI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 346 HUAWEI: PRODUCT LAUNCHES
  • TABLE 347 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2019-2023 (USD BILLION)
  • TABLE 348 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2024-2030 (USD BILLION)
  • TABLE 349 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2019-2023 (USD BILLION)
  • TABLE 350 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2024-2030 (USD BILLION)
  • TABLE 351 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD BILLION)
  • TABLE 352 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2024-2030 (USD BILLION)
  • TABLE 353 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2019-2023 (USD BILLION)
  • TABLE 354 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2024-2030 (USD BILLION)
  • TABLE 355 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2019-2023 (USD BILLION)
  • TABLE 356 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2024-2030 (USD BILLION)
  • TABLE 357 RETAIL ANALYTICS MARKET, BY OFFERING, 2019-2023 (USD MILLION)
  • TABLE 358 RETAIL ANALYTICS MARKET, BY OFFERING, 2024-2029 (USD MILLION)
  • TABLE 359 RETAIL ANALYTICS MARKET, BY BUSINESS FUNCTION, 2019-2023 (USD MILLION)
  • TABLE 360 RETAIL ANALYTICS MARKET, BY BUSINESS FUNCTION, 2024-2029 (USD MILLION)
  • TABLE 361 RETAIL ANALYTICS MARKET, BY APPLICATION, 2019-2023 (USD MILLION)
  • TABLE 362 RETAIL ANALYTICS MARKET, BY APPLICATION, 2024-2029 (USD MILLION)
  • TABLE 363 RETAIL ANALYTICS END-USER MARKET, BY PRODUCT TYPE, 2019-2023 (USD MILLION)
  • TABLE 364 RETAIL ANALYTICS END-USER MARKET, BY PRODUCT TYPE, 2024-2029 (USD MILLION)
  • TABLE 365 RETAIL ANALYTICS MARKET, BY REGION, 2019-2023 (USD MILLION)
  • TABLE 366 RETAIL ANALYTICS MARKET, BY REGION, 2024-2029 (USD MILLION)

List of Figures

  • FIGURE 1 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: RESEARCH DESIGN
  • FIGURE 2 BREAKUP OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION
  • FIGURE 3 TOP-DOWN APPROACH
  • FIGURE 4 APPROACH 1 (SUPPLY SIDE): REVENUE OF VENDORS IN ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 5 BOTTOM-UP APPROACH
  • FIGURE 6 DEMAND-SIDE ANALYSIS
  • FIGURE 7 BOTTOM-UP (SUPPLY SIDE) ANALYSIS: COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 8 DATA TRIANGULATION
  • FIGURE 9 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, 2022-2030 (USD MILLION)
  • FIGURE 10 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: REGIONAL SNAPSHOT
  • FIGURE 11 GROWING DEMAND FOR ENHANCING PERSONALIZED EXPERIENCES, OPTIMIZING INVENTORY MANAGEMENT, AND DYNAMIC PRICING TO DRIVE MARKET
  • FIGURE 12 SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024
  • FIGURE 13 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 14 MARKETING & SALES SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2024
  • FIGURE 15 GENERATIVE AI SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 16 PERSONALIZED PRODUCT RECOMMENDATIONS SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2024
  • FIGURE 17 ONLINE SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024
  • FIGURE 18 PERSONALIZED PRODUCT RECOMMENDATIONS AND PROFESSIONAL SERVICES SEGMENTS TO ACCOUNT FOR SIGNIFICANT MARKET SHARES IN 2024
  • FIGURE 19 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 20 CONSUMER LIKELIHOOD OF USING CONVERSATIONAL AI FOR ADVICE AND RECOMMENDATIONS
  • FIGURE 21 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • FIGURE 22 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
  • FIGURE 23 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 24 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: ECOSYSTEM
  • FIGURE 25 LIST OF MAJOR PATENTS FOR ARTIFICIAL INTELLIGENCE IN RETAIL
  • FIGURE 26 PROCESSORS AND CONTROLLERS EXPORT, BY KEY COUNTRY, 2016-2023 (USD BILLION)
  • FIGURE 27 PROCESSORS AND CONTROLLERS IMPORT, BY KEY COUNTRY, 2016-2023 (USD BILLION)
  • FIGURE 28 PORTER'S FIVE FORCES IMPACT ON ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 29 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE SOLUTIONS
  • FIGURE 30 KEY BUYING CRITERIA FOR TOP THREE SOLUTIONS
  • FIGURE 31 EVOLUTION OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • FIGURE 32 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 33 VISUAL SEARCH SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 34 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 35 GENERATIVE AI SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 36 CYBERSECURITY SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 37 OFFLINE SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 38 NORTH AMERICA: MARKET SNAPSHOT
  • FIGURE 39 MIDDLE EAST & AFRICA: MARKET SNAPSHOT
  • FIGURE 40 REVENUE ANALYSIS FOR KEY COMPANIES IN PAST THREE YEARS
  • FIGURE 41 SHARE OF LEADING COMPANIES IN ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, 2023
  • FIGURE 42 MARKET RANKING ANALYSIS OF TOP FIVE PLAYERS
  • FIGURE 43 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2023
  • FIGURE 44 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: COMPANY FOOTPRINT
  • FIGURE 45 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: COMPANY EVALUATION MATRIX (START-UPS/SMES), 2023
  • FIGURE 46 BRAND/PRODUCT COMPARISON
  • FIGURE 47 FINANCIAL METRICS OF KEY ARTIFICIAL INTELLIGENCE IN RETAIL MARKET VENDORS
  • FIGURE 48 COMPANY VALUATION OF KEY ARTIFICIAL INTELLIGENCE IN RETAIL MARKET VENDORS
  • FIGURE 49 IBM: COMPANY SNAPSHOT
  • FIGURE 50 AMAZON: COMPANY SNAPSHOT
  • FIGURE 51 SALESFORCE: COMPANY SNAPSHOT
  • FIGURE 52 ORACLE: COMPANY SNAPSHOT
  • FIGURE 53 MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 54 GOOGLE: COMPANY SNAPSHOT
  • FIGURE 55 NVIDEA: COMPANY SNAPSHOT
  • FIGURE 56 ACCENTURE: COMPANY SNAPSHOT
  • FIGURE 57 SAP SE: COMPANY SNAPSHOT
  • FIGURE 58 SERVICENOW: COMPANY SNAPSHOT
  • FIGURE 59 INFOSYS: COMPANY SNAPSHOT
  • FIGURE 60 INTEL: COMPANY SNAPSHOT
  • FIGURE 61 AMD: COMPANY SNAPSHOT