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市場調查報告書
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1536917

零售市場中的人工智慧 -市場佔有率分析、行業趨勢和統計、成長預測（2024-2029）

AI In Retail - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 136 Pages | 商品交期: 2-3個工作天內

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簡介目錄

零售業人工智慧市場規模預計到 2024 年為 98.5 億美元，預計到 2029 年將達到 404.9 億美元，在預測期內（2024-2029 年）複合年成長率為 32.68%。

零售市場中的人工智慧

人工智慧是由大量可靠資料驅動的演算法集合，擴大被零售業採用，以實現個人化的購物體驗。透過利用客戶偏好，零售商可以提供量身訂製的產品推薦、改善客戶體驗並推動銷售。

主要亮點

  • 在先進資料分析和預測系統整合的推動下，零售業正在經歷一場重大的數位轉型。這種由人工智慧和物聯網融合推動的轉型為零售商提供了先進的見解，以最佳化業務並發現利潤豐厚的商機。零售商正在轉向人工智慧驅動的解決方案來應對不斷變化的消費行為、勞動力限制、供應鏈中斷和成本上升等挑戰。
  • 零售公司意識到人工智慧在降低成本和提高業務效率方面的潛力，擴大將人工智慧納入其流程中。隨著人工智慧驅動的聊天機器人徹底改變互動，這種轉變正在改變客戶服務的面貌。在線上購物時，聊天機器人可以根據客戶的偏好（例如價格分佈、功能和用戶評論）提案產品。透過結合建議演算法，零售商可以增加銷售額，同時客戶可以找到符合他們口味的產品。
  • 此外，零售商正在將數位元素引入銷售、支援、商品行銷和財務業務，以加深與客戶的關係。除了人工智慧之外，物聯網、自動化、區塊鏈和虛擬實境等技術正在以數位方式顛覆零售業格局。人工智慧驅動的零售商將利用敏銳的預測工具做出更明智的決策，而增強的視覺識別和擴增實境將重新定義網路購物，並讓客戶能夠虛擬地體驗產品。
  • 全球零售業人工智慧的使用激增，科技巨頭和小型企業都在加強。因此，對人工智慧工程師的需求正在迅速增加，但仍需要該領域經驗豐富的專業人員。
  • COVID-19 大流行加速了這些趨勢，零售商正在努力應對。隨著消費行為轉向線上，傳統零售商正在增強其技術力。疫情帶來了以客戶為中心的範式，採用數位轉型原則的公司加強了營運並獲得了顯著的效益。

零售市場的人工智慧趨勢

軟體領域將經歷顯著成長

  • 領先的零售公司正在採用人工智慧軟體來提供個人化的購物體驗。透過分析客戶資料和行為，這些零售商利用人工智慧演算法來支援複雜的建議引擎。這些引擎提案根據個人偏好製化產品，從而增加銷售量並提高客戶參與。
  • 隨著全通路零售的發展，零售商正在增加對人工智慧軟體的投資。該軟體整合了來自多個管道的資料，以創建無縫的線上、行動和店內購物體驗。人工智慧驅動的解決方案使零售商能夠統一客戶資料、個人化行銷訊息並最佳化所有管道的庫存管理。
  • 人工智慧軟體使零售商能夠創建有針對性的行銷宣傳活動和個人化廣告。透過分析大量客戶資料，人工智慧演算法可以識別趨勢、偏好和購買模式。這使得零售商可以客製化行銷訊息和促銷活動，從而提高參與度和銷售量。因此，越來越多的零售商正在採用基於人工智慧的軟體。
  • 由於電子商務採用率增加、網路普及率和智慧型手機使用率增加等因素，亞太地區對人工智慧軟體的需求正在迅速成長。根據 GSMA 的《2023 年行動經濟》，到 2030 年，亞太地區的智慧型手機普及率預計將增至 94%，數位付款選項將推動這一成長。該地區的零售商正在利用人工智慧軟體來改善網路購物體驗。這包括提供個人化的產品建議、最佳化定價策略、簡化訂單履行流程等等。

北美佔據主要市場佔有率

  • 由於個人化購物體驗、庫存管理和最佳化以及供應鏈最佳化等多種因素，北美零售市場對人工智慧的需求正在顯著成長。
  • 該地區的許多零售商正在實施基於人工智慧的解決方案來最佳化供應鏈業務和庫存。人工智慧幫助零售商管理和留住客戶並了解消費者的購買模式。線下和線上零售公司也正在部署人工智慧技術來吸引客戶並增加周轉率。
  • 美國和加拿大的許多零售商也正在實施預測分析和機器學習等人工智慧技術，以幫助零售商最佳化其供應鏈。透過分析來自供應商、物流提供者等的資料，人工智慧可以識別效率低下的情況，縮短前置作業時間，並提高整個供應鏈的績效。因此，零售商擴大採用這些技術。
  • 此外，許多美國零售商正在利用人工智慧來分析客戶資料和行為，以提供個人化的購物體驗。人工智慧驅動的建議引擎可以根據過去的購買歷史、瀏覽歷史和人口統計資訊提案產品，從而提高客戶滿意度和忠誠度。

零售市場人工智慧概述

零售市場的人工智慧是碎片化的。物聯網、電子商務行銷和巨量資料分析的日益普及為零售市場中的人工智慧提供了利潤豐厚的機會。現有競爭對手之間的競爭非常激烈。此外，SAP SE、微軟公司、IBM公司、Salesforce公司和Google有限責任公司等大公司預計將進行收購並與專注於創新的新興企業合作。

  • 2024 年 3 月，IBM 宣布擴大在印度的技術專業實驗室能力。 IBM 致力於協助客戶充分利用人工智慧、混合雲端和網路安全技術。
  • 2024 年 1 月， Oracle宣佈在 Oracle 雲端基礎架構 (OCI) 上全面推出生成式 AI 服務以及讓企業更輕鬆地利用生成式 AI 最新進展的創新。 OCI 生成式 AI 服務是一項完全託管的服務，可無縫整合 Cohere 和 Meta Llama 2 大型語言模型 (LLM)，以解決各種業務用例。

其他好處

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章 簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業相關人員分析
  • 產業吸引力－波特五力分析
    • 消費者議價能力
    • 供應商的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭公司之間的敵對關係

第5章市場動態

  • 市場促進因素
    • 零售連鎖店技術的快速進步
    • 零售業的新興企業趨勢
  • 市場限制因素
    • 缺乏文化準備的專業和內部知識
  • COVID-19 對市場的影響

第6章 重大技術投入

  • 雲端技術
  • 人工智慧
  • 網路安全
  • 數位服務

第7章 市場區隔

  • 按頻道
    • 全通路
    • 實體店面
    • 網路零售商
  • 按成分
    • 軟體
    • 服務（管理、專業）
  • 按發展
    • 雲
    • 本地
  • 按用途
    • 供應鍊和物流
    • 產品最佳化
    • 店內導航
    • 付款/價格分析
    • 庫存管理
    • 客戶關係管理（CRM）
  • 依技術
    • 機器學習
    • 自然語言處理
    • 聊天機器人
    • 影像/視訊分析
    • 群體智慧
  • 按地區
    • 北美洲
    • 歐洲
    • 亞洲
    • 澳洲和紐西蘭
    • 拉丁美洲
    • 中東/非洲

第8章 競爭格局

  • 公司簡介
    • SAP SE
    • IBM Corporation
    • Microsoft Corporation
    • Google LLC
    • Salesforce Inc.
    • Oracle Corporation
    • ViSenze Pte Ltd
    • Amazon Web Services Inc.
    • BloomReach Inc.
    • Symphony AI
    • Daisy Intelligence Corporation
    • Conversica Inc.

第9章投資分析

第10章市場機會與未來趨勢

簡介目錄
Product Code: 62327

The AI In Retail Market size is estimated at USD 9.85 billion in 2024, and is expected to reach USD 40.49 billion by 2029, growing at a CAGR of 32.68% during the forecast period (2024-2029).

AI In Retail - Market

Artificial intelligence, a collection of algorithms harnessing vast and reliable data, is increasingly adopted in retail to personalize the shopping experience. By leveraging customer preferences, retailers can offer tailored product recommendations, elevating the customer experience and driving sales.

Key Highlights

  • Retail has witnessed a profound digital transformation, propelled by the integration of advanced data analytics and forecasting systems. This, bolstered by the convergence of artificial intelligence and the Internet of Things, has empowered retailers with sophisticated insights to optimize operations and identify lucrative business opportunities. Retailers are turning to AI-powered solutions to tackle challenges like evolving consumer behavior, labor constraints, supply chain disruptions, and escalating costs.
  • Recognizing the potential of AI to reduce costs and enhance operational efficiency, retailers are increasingly integrating it into their processes. This shift is reshaping customer service, with AI-powered chatbots revolutionizing interactions. During online purchases, chatbots can suggest products based on customers' preferences, including price range, features, and user reviews. By incorporating recommendation algorithms, retailers can boost sales while customers find products tailored to their preferences.
  • Moreover, retailers are forging deeper customer relationships, infusing digital elements into sales, support, merchandising, and finance operations. Beyond AI, technologies like IoT, automation, blockchain, and virtual reality are digitally disrupting the retail landscape. AI-equipped retailers leverage sharp forecasting tools for smarter decision-making while enhanced visual recognition and augmented reality redefine online shopping, enabling customers to experience products virtually.
  • The global retail sector is witnessing a surge in AI applications, with both tech giants and SMBs ramping up their efforts. Consequently, the demand for AI engineers has soared, but more experienced professionals are still needed in this field.
  • The COVID-19 pandemic has accelerated these trends, leaving retailers grappling to adapt. As consumer behavior tilts toward online, traditional retailers are grappling to bolster their technological capabilities. The pandemic has ushered in a customer-centric paradigm, and companies embracing digital transformation principles are fortifying their operations and reaping significant profits.

AI in Retail Market Trends

Software Segment to Witness Major Growth

  • Leading retailers are adopting AI software to offer personalized shopping experiences. By analyzing customer data and behavior, these retailers leverage AI algorithms to power advanced recommendation engines. These engines suggest products tailored to individual preferences, driving sales and boosting customer engagement.
  • As omnichannel retailing gains prominence, retailers are increasingly investing in AI software. This software helps integrate data from multiple channels, ensuring a seamless shopping experience across online, mobile, and brick-and-mortar stores. With AI-driven solutions, retailers can unify customer data, personalize marketing messages, and optimize inventory management across all channels.
  • AI software equips retailers with the ability to craft targeted marketing campaigns and personalized advertisements. By analyzing vast amounts of customer data, AI algorithms identify trends, preferences, and buying patterns. This enables retailers to tailor marketing messages and promotions, resulting in higher engagement and sales. Consequently, an increasing number of retailers are embracing AI-based software.
  • Asia-Pacific is witnessing a surge in demand for AI software, driven by rising e-commerce adoption and factors such as increasing internet penetration and smartphone usage. According to GSMA, Mobile Economy 2023, Asia-Pacific is expected to see its smartphone adoption rate increase to 94% by 2030, and digital payment options are fueling this growth. Retailers in the region are leveraging AI software to enhance the online shopping experience. This includes offering personalized product recommendations, optimizing pricing strategies, and streamlining order fulfillment processes.

North America to Hold Significant Market Share

  • The demand for artificial intelligence (AI) in the retail sector in North America is experiencing significant growth driven by various factors such as personalized shopping experiences, inventory management and optimization, supply chain optimization, and others.
  • Many retailers in this region have deployed AI-based solutions to optimize their supply chain operations and inventory. AI helps retailers manage and maintain customers and understand consumers' buying patterns. Also, AI technologies are being adopted by offline and online retail businesses to engage customers and improve sales turnover.
  • Many retailers in the United States and Canada are also adopting AI technologies, such as predictive analytics and machine learning, helping retailers optimize their supply chains. AI can identify inefficiencies, reduce lead times, and improve overall supply chain performance by analyzing data from suppliers, logistics providers, and other sources. Due to this, retailers are focusing on the adoption of such technologies.
  • Furthermore, many retail companies in the US leverage AI to analyze customer data and behavior to offer personalized shopping experiences. AI-powered recommendation engines may suggest products based on past purchases, browsing history, and demographic information, enhancing customer satisfaction and loyalty.

AI in Retail Industry Overview

Artificial intelligence in the retail market is fragmented. The growing adoption of IoT, e-commerce marketing, and big data analytics provides lucrative opportunities for artificial intelligence in the retail market. The competitive rivalry among existing competitors is high. Moreover, large companies such as SAP SE, Microsoft Corporation, IBM Corporation, Salesforce Inc., and Google LLC are expected to make acquisitions and collaborate with startups focused on innovation.

  • In March 2024, IBM announced the expansion of its technical expert laboratory capacity in India to ensure that businesses remain strong in a highly competitive environment. It focuses on helping clients take full advantage of artificial intelligence, hybrid cloud, and cyber security technologies.
  • In January 2024, Oracle announced the general availability of the Oracle Cloud Infrastructure (OCI) Generative AI service and innovations that make it easier for enterprises to take advantage of the latest advancements in generative AI. OCI Generative AI service is a fully managed service that seamlessly integrates large language models (LLMs) from Cohere and Meta Llama 2 to address various business use cases.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Stakeholder Analysis
  • 4.3 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.3.1 Bargaining Power of Consumers
    • 4.3.2 Bargaining Power of Suppliers
    • 4.3.3 Threat of New Entrants
    • 4.3.4 Threat of Substitute Products
    • 4.3.5 Intensity of Competitive Rivalry

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Rapid Adoption of Advances in Technology Across Retail Chain
    • 5.1.2 Emerging Trend of Startups in the Retail Space
  • 5.2 Market Restraints
    • 5.2.1 Lack of Professionals as well as In-house Knowledge for Cultural Readiness
  • 5.3 Impact of COVID-19 on the Market

6 KEY TECHNOLOGY INVESTMENTS

  • 6.1 Cloud Technology
  • 6.2 Artificial Intelligence
  • 6.3 Cyber Security
  • 6.4 Digital Services

7 MARKET SEGMENTATION

  • 7.1 By Channel
    • 7.1.1 Omnichannel
    • 7.1.2 Brick and Mortar
    • 7.1.3 Pure-play Online Retailers
  • 7.2 By Component
    • 7.2.1 Software
    • 7.2.2 Service (Managed and Professional)
  • 7.3 By Deployment
    • 7.3.1 Cloud
    • 7.3.2 On-premise
  • 7.4 By Application
    • 7.4.1 Supply Chain and Logistics
    • 7.4.2 Product Optimization
    • 7.4.3 In-Store Navigation
    • 7.4.4 Payment and Pricing Analytics
    • 7.4.5 Inventory Management
    • 7.4.6 Customer Relationship Management (CRM)
  • 7.5 By Technology
    • 7.5.1 Machine Learning
    • 7.5.2 Natural Language Processing
    • 7.5.3 Chatbots
    • 7.5.4 Image and Video Analytics
    • 7.5.5 Swarm Intelligence
  • 7.6 By Geography***
    • 7.6.1 North America
    • 7.6.2 Europe
    • 7.6.3 Asia
    • 7.6.4 Australia and New Zealand
    • 7.6.5 Latin America
    • 7.6.6 Middle East and Africa

8 COMPETITIVE LANDSCAPE

  • 8.1 Company Profiles
    • 8.1.1 SAP SE
    • 8.1.2 IBM Corporation
    • 8.1.3 Microsoft Corporation
    • 8.1.4 Google LLC
    • 8.1.5 Salesforce Inc.
    • 8.1.6 Oracle Corporation
    • 8.1.7 ViSenze Pte Ltd
    • 8.1.8 Amazon Web Services Inc.
    • 8.1.9 BloomReach Inc.
    • 8.1.10 Symphony AI
    • 8.1.11 Daisy Intelligence Corporation
    • 8.1.12 Conversica Inc.

9 INVESTMENT ANALYSIS

10 MARKET OPPORTUNITIES AND FUTURE TRENDS