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零售業人工智能

市場調查報告書

商品編碼

1604530

零售業人工智慧市場：未來預測（2024-2029）

AI In Retail Market - Forecasts from 2024 to 2029

出版日期: 2024年11月05日 | 出版商:

Knowledge Sourcing Intelligence | 英文 148 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

零售人工智慧市場預計將以36.60%的複合年成長率成長，市場規模從2024年的195.08億美元增至2029年的532.71億美元。

實體店監控的出現、網路用戶和智慧型裝置的持續成長以及政府對數位化的態度正在促進零售人工智慧產業的成長。

此外，零售業的人工智慧是過去幾十年來企業營運方式的核心。人工智慧和巨量資料分析是數位化業務的核心要素，因為它們可以增強服務、流程甚至整個業務。物聯網、機器學習服務等技術進步以及應用程式和智慧設備使用的增加也推動了零售業對巨量資料分析和人工智慧應用程式的日益認知和採用。

零售人工智慧市場的促進因素

電子商務的成長有助於零售人工智慧市場的成長

電子商務和數位體驗的繁榮呼喚著人工智慧在零售業的應用。大多數線上零售商使用基於人工智慧的建議系統、聊天機器人和虛擬助理來增強網路購物體驗並吸引消費者促進對話。此外，甚至實體店也在利用人工智慧增強業務，以填補客戶購物體驗的空白。

此外，BYOB（建立你自己的大腦）是一種所有資料和決策流程均由人工智慧支援的工具。減少分析師的工作量。不系統地挖掘、管理和開發儲存庫。根據關鍵指標和統計趨勢提供即時分析和可行的見解。

電子商務的成長也推動了人工智慧在零售業的應用。新市場帶來了豐富的資料，有望改善服務、提高業務效率和提高安全性。這種商業環境為更有效地利用人工智慧促進零售業創造了機會。

零售人工智慧市場的地域展望

北美在預測期內將經歷指數級成長

北美擁有許多推動人工智慧和零售創新的領先科技公司和研究機構，包括英特爾、英偉達和埃森哲。這些改進正在支持零售業人工智慧的創建和利用。

北美零售商正在採用人工智慧技術來改善個人化廣告、客戶服務、庫存管理和價格最佳化等業務。該地區零售業蓬勃發展，以傳統零售商、電子商務企業和實體店的存在為特徵，使其成為採用人工智慧在不斷變化的環境中保持競爭優勢的好地方。

北美龐大的客戶資料對於人工智慧演算法和預測分析至關重要，使商家能夠創造更個人化的購物體驗。該地區擁有促進人工智慧和零售業創新和成長的環境，包括創業投資投資、政府措施、大學研究和訓練有素的勞動力。

為什麼要購買這份報告？

富有洞察力的分析：獲得涵蓋主要和新興地區的深入市場洞察，重點關注客戶細分、政府政策和社會經濟因素、消費者偏好、行業明智以及其他子區隔。
競爭格局：了解世界主要企業採取的策略策略，並了解透過正確的策略滲透市場的潛力。
市場促進因素和未來趨勢：探索動態因素和關鍵市場趨勢以及它們將如何塑造未來市場發展。
可行的建議：利用洞察力做出策略決策，以在動態環境中發現新的業務流和收益。
受眾廣泛：對於新興企業、研究機構、顧問、中小企業和大型企業有用且具有成本效益。

它有什麼用？

產業與市場考量、商機評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開發、競爭影響

分析範圍

歷史資料與預測（2022-2029）
成長機會、挑戰、供應鏈前景、法規結構、顧客行為、趨勢分析
競爭對手定位、策略和市場佔有率分析
收益成長率與預測分析：按細分市場/地區（按國家）
公司概況（策略、產品、財務資訊、主要趨勢等）

零售人工智慧市場分為以下幾個部分：

依部署方式

雲
本地

依技術

大語言模型
機器學習
聊天機器人
其他

按用途

需求預測
建議
庫存管理
情緒分析
其他

按地區

北美洲
美國
加拿大
墨西哥
南美洲
巴西
阿根廷
其他
歐洲
德國
法國
英國
西班牙
其他
中東中東/非洲
沙烏地阿拉伯
UAE
以色列
其他
亞太地區
中國
日本
印度
韓國
印尼
台灣
其他

介紹
北美洲
- 依部署方式
- 依技術
- 按用途
- 按國家/地區
南美洲
- 依部署方式
- 依技術
- 按用途
- 按國家/地區
歐洲
- 依部署方式
- 依技術
- 按用途
- 按國家/地區
中東/非洲
- 依部署方式
- 依技術
- 按用途
- 按國家/地區
亞太地區
- 依部署方式
- 依技術
- 按用途
- 按國家/地區

第9章競爭環境及分析

主要企業及策略分析
新興企業和市場盈利
企業合併（M&A）、合約、業務合作
供應商競爭力矩陣

第10章公司簡介

Hitachi Solutions
BYOB
Intel
Accenture
Nvidia
Kustomer
HPE
Adeppto
H2O.ai
Matellio
BCG

簡介目錄

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

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