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市场调查报告书
商品编码
1604530

零售业人工智慧市场：未来预测（2024-2029）

AI In Retail Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 148 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

零售人工智慧市场预计将以36.60%的复合年增长率成长，市场规模从2024年的195.08亿美元增至2029年的532.71亿美元。

实体店监控的出现、网路用户和智慧型装置的持续成长以及政府对数位化的态度正在促进零售人工智慧产业的成长。

此外，零售业的人工智慧是过去几十年来企业营运方式的核心。人工智慧和巨量资料分析是数位化业务的核心要素，因为它们可以增强服务、流程甚至整个业务。物联网、机器学习服务等技术进步以及应用程式和智慧设备使用的增加也推动了零售业对巨量资料分析和人工智慧应用程式的日益认识和采用。

零售人工智慧市场的驱动因素

  • 电子商务的成长有助于零售人工智慧市场的成长

电子商务和数位体验的繁荣呼唤着人工智慧在零售业的应用。大多数线上零售商使用基于人工智慧的建议系统、聊天机器人和虚拟助理来增强网路购物体验并吸引消费者促进对话。此外，甚至实体店也在利用人工智慧增强业务，以填补客户购物体验的空白。

此外，BYOB（建立你自己的大脑）是一种所有资料和决策流程均由人工智慧支援的工具。减少分析师的工作量。不繫统地挖掘、管理和开发储存库。根据关键指标和统计趋势提供即时分析和可行的见解。

电子商务的成长也推动了人工智慧在零售业的应用。新市场带来了丰富的资料，有望改善服务、提高业务效率和提高安全性。这种商业环境为更有效地利用人工智慧促进零售业创造了机会。

零售人工智慧市场的地域展望

  • 北美在预测期内将经历指数级增长

北美拥有许多推动人工智慧和零售创新的领先科技公司和研究机构，包括英特尔、英伟达和埃森哲。这些改进正在支持零售业人工智慧的创建和利用。

北美零售商正在采用人工智慧技术来改善个人化广告、客户服务、库存管理和价格优化等业务。该地区零售业蓬勃发展，以传统零售商、电子商务企业和实体店的存在为特征，使其成为采用人工智慧在不断变化的环境中保持竞争优势的好地方。

北美庞大的客户资料对于人工智慧演算法和预测分析至关重要，使商家能够创造更个人化的购物体验。该地区拥有促进人工智慧和零售业创新和成长的环境，包括创业投资投资、政府措施、大学研究和训练有素的劳动力。

为什么要购买这份报告？

  • 富有洞察力的分析：获得涵盖主要和新兴地区的深入市场洞察，重点关注客户细分、政府政策和社会经济因素、消费者偏好、行业明智以及其他子区隔。
  • 竞争格局：了解世界主要企业采取的策略策略，并了解透过正确的策略渗透市场的潜力。
  • 市场驱动因素和未来趋势：探索动态因素和关键市场趋势以及它们将如何塑造未来市场发展。
  • 可行的建议：利用洞察力做出策略决策，以在动态环境中发现新的业务流和收益。
  • 受众广泛：对于新兴企业、研究机构、顾问、中小企业和大型企业有用且具有成本效益。

它有什么用？

产业与市场考量、商机评估、产品需求预测、打入市场策略、地理扩张、资本投资决策、法律规范与影响、新产品开发、竞争影响

分析范围

  • 历史资料与预测（2022-2029）
  • 成长机会、挑战、供应链前景、法规结构、顾客行为、趋势分析
  • 竞争对手定位、策略和市场占有率分析
  • 收益成长率与预测分析：按细分市场/地区（按国家）
  • 公司概况（策略、产品、财务资讯、主要趋势等）

零售人工智慧市场分为以下几个部分：

依部署方式

  • 云
  • 本地

依技术

  • 大语言模型
  • 机器学习
  • 聊天机器人
  • 其他的

按用途

  • 需求预测
  • 建议
  • 库存管理
  • 情绪分析
  • 其他的

按地区

  • 北美洲
  • 美国
  • 加拿大
  • 墨西哥
  • 南美洲
  • 巴西
  • 阿根廷
  • 其他的
  • 欧洲
  • 德国
  • 法国
  • 英国
  • 西班牙
  • 其他的
  • 中东 中东/非洲
  • 沙乌地阿拉伯
  • UAE
  • 以色列
  • 其他的
  • 亚太地区
  • 中国
  • 日本
  • 印度
  • 韩国
  • 印尼
  • 台湾
  • 其他的

目录

第一章简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关利益者的主要利益

第二章调查方法

  • 研究设计
  • 调查过程

第三章执行摘要

  • 主要发现
  • CXO观点

第四章市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章：零售业人工智慧市场：依部署方式

  • 介绍
  • 云
  • 本地

第六章零售业人工智慧市场：依技术分类

  • 介绍
  • 大语言模型
  • 机器学习
  • 聊天机器人
  • 其他的

第七章零售业人工智慧市场：依应用分类

  • 介绍
  • 需求预测
  • 建议
  • 库存管理
  • 情绪分析
  • 其他的

第八章零售人工智慧市场：按地区

  • 介绍
  • 北美洲
    • 依部署方式
    • 依技术
    • 按用途
    • 按国家/地区
  • 南美洲
    • 依部署方式
    • 依技术
    • 按用途
    • 按国家/地区
  • 欧洲
    • 依部署方式
    • 依技术
    • 按用途
    • 按国家/地区
  • 中东/非洲
    • 依部署方式
    • 依技术
    • 按用途
    • 按国家/地区
  • 亚太地区
    • 依部署方式
    • 依技术
    • 按用途
    • 按国家/地区

第九章竞争环境及分析

  • 主要企业及策略分析
  • 新兴企业和市场盈利
  • 企业合併（M&A）、合约、业务合作
  • 供应商竞争力矩阵

第十章 公司简介

  • Hitachi Solutions
  • BYOB
  • Intel
  • Accenture
  • Nvidia
  • Kustomer
  • HPE
  • Adeppto
  • H2O.ai
  • Matellio
  • BCG
简介目录
Product Code: KSI061616758

The AI in the retail market is expected to grow at a CAGR of 36.60%, reaching a market size of US$53.271 billion in 2029 from US$19.508 billion in 2024.

The emergence of surveillance and monitoring at a physical retail location, the constant rise of internet users and smart gadgets, and the government's stance toward digitization are contributing to AI in the retail industry's growth.

Moreover, the way companies have operated in the past few decades lies at the heart of artificial intelligence in the retail industry. AI and big data analytics are the core components of any digitalized business, as they can enhance services, processes, and even the entire business. The growing awareness and adoption of big data analytics and AI applications in retail is also driven by the advancement of technology such as IoT, machine learning services, and increased usage of applications and smart devices, among others.

AI in retail market drivers

  • E-commerce growth is contributing to the AI in retail market growth

With the boom of e-commerce and digital experiences, there has been a call for using Artificial Intelligence in the retail sector. Most online retailers use AI-based recommendation systems, chatbots, and virtual assistants to enhance the online shopping experience while engaging consumers to drive conversations. Additionally, even physical stores are enhancing their operations with artificial intelligence to bridge the gap left in the customers' shopping trips.

Moreover, Build Your Own Brain (BYOB) is an AI-supportive tool for all data and decision-making processes. It extends your analyst's workload. It will unsystematically deep dive, curate, and develop a repository. It presents analytics and actionable insights in real-time according to key metrics and statistical trends.

The growth of e-commerce also promotes the use of artificial intelligence in the retail sector. New markets are accompanied by a wealth of data, leading to expectations for improved service, greater operational efficiency, and enhanced security. This business environment creates opportunities for more effective use of AI in retail.

AI in the retail market geographical outlook

  • North America is witnessing exponential growth during the forecast period

North America is home to many leading technology companies and research institutions driving innovation in AI and retail, like Intel, Nvidia, and Accenture. These improvements aid in creating and using artificial intelligence in the retail industry.

Retailers in North America are employing AI technology to improve operations such as personalized advertising, customer service, inventory management, and price optimization. As this region is characterized by a buoyant retail industry, the presence of traditional retailers, e-commerce players, and brick-and-mortar shops, it offers a perfect ground for adopting AI to stay ahead of the competition in an ever-dynamic environment.

North America's vast customer data is critical for AI algorithms and predictive analytics, allowing merchants to create more personalized shopping experiences. The region's enabling environment, which includes venture capital investment, government initiatives, university research, and a trained workforce, fosters innovation and growth in the AI and retail industries.

Reasons for buying this report:-

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The AI in retail market is analyzed into the following segments:

By Deployment Type

  • Cloud
  • On-Premise

By Technology

  • Large language model
  • Machine Learning
  • Chatbots
  • Others

By Application

  • Demand forecasting
  • Recommendations
  • Inventory management
  • Sentiment analysis
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • Germany
  • France
  • UK
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Israel
  • Others
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Indonesia
  • Taiwan
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base and Forecast Years Timeline
  • 1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Processes

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings
  • 3.2. CXO Perspective

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. AI IN THE RETAIL MARKET BY DEPLOYMENT TYPE

  • 5.1. Introduction
  • 5.2. Cloud
  • 5.3. On-Premise

6. AI IN THE RETAIL MARKET BY TECHNOLOGY

  • 6.1. Introduction
  • 6.2. Large language model
  • 6.3. Machine Learning
  • 6.4. Chatbots
  • 6.5. Others

7. AI IN THE RETAIL MARKET BY APPLICATION

  • 7.1. Introduction
  • 7.2. Demand forecasting
  • 7.3. Recommendations
  • 7.4. Inventory management
  • 7.5. Sentiment analysis
  • 7.6. Others

8. AI IN THE RETAIL MARKET BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Deployment Type
    • 8.2.2. By Technology
    • 8.2.3. By Application
    • 8.2.4. By Country
      • 8.2.4.1. USA
      • 8.2.4.2. Canada
      • 8.2.4.3. Mexico
  • 8.3. South America
    • 8.3.1. By Deployment Type
    • 8.3.2. By Technology
    • 8.3.3. By Application
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
      • 8.3.4.2. Argentina
      • 8.3.4.3. Others
  • 8.4. Europe
    • 8.4.1. By Deployment Type
    • 8.4.2. By Technology
    • 8.4.3. By Application
    • 8.4.4. By Country
      • 8.4.4.1. Germany
      • 8.4.4.2. France
      • 8.4.4.3. UK
      • 8.4.4.4. Spain
      • 8.4.4.5. Others
  • 8.5. Middle East and Africa
    • 8.5.1. By Deployment Type
    • 8.5.2. By Technology
    • 8.5.3. By Application
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
      • 8.5.4.2. UAE
      • 8.5.4.3. Others
  • 8.6. Asia Pacific
    • 8.6.1. By Deployment Type
    • 8.6.2. By Technology
    • 8.6.3. By Application
    • 8.6.4. By Country
      • 8.6.4.1. China
      • 8.6.4.2. Japan
      • 8.6.4.3. India
      • 8.6.4.4. South Korea
      • 8.6.4.5. Indonesia
      • 8.6.4.6. Taiwan
      • 8.6.4.7. Others

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. Hitachi Solutions
  • 10.2. BYOB
  • 10.3. Intel
  • 10.4. Accenture
  • 10.5. Nvidia
  • 10.6. Kustomer
  • 10.7. HPE
  • 10.8. Adeppto
  • 10.9. H2O.ai
  • 10.10. Matellio
  • 10.11. BCG