AI in Retail Market Size & Share 2023 to 2032
Market Size by Component (Solution [Chatbot, Customer Behavior Tracking, CRM, Inventory Management, Price Optimization, Recommendation Engine, Supply Chain Management, Visual Search], Service), by Technology, Application & Forecast.Download Free PDF
Report Content
Chapter 1 Methodology & Scope
1.1 Market Definitions
1.2 Base estimates & calculations
1.3 Forecast calculation
1.4 Data sources
1.4.1 Primary
1.4.2 Secondary
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 AI in Retail market 360º synopsis, 2018 – 2032
2.2 Business Trends
2.2.1 Total addressable market(TAM)
2.3 Regional trends
2.4 Component trends
2.5 Technology trends
2.6 Application trends
Chapter 3 AI in Retail Market Insights
3.1 Introduction
3.2 Impact of COVID-19 outbreak
3.2.1 North America
3.2.2 Europe
3.2.3 Asia Pacific
3.2.4 South America
3.2.5 MEA
3.3 Russia- Ukraine war impact on AI in Retail market
3.4 Evolution of AI in Retail
3.5 Industry ecosystem analysis
3.5.1 AI component provider
3.5.2 Software providers
3.5.3 Application developers
3.5.4 Profit margin
3.5.5 Vendor matrix
3.5.5.1 Hardware vendors
3.5.5.2 Service vendors
3.5.5.3 Data-analytics vendors
3.6 Technology & innovation landscape
3.6.1 Gesture Recognition
3.6.2 Robots
3.7 Patent analysis
3.8 Investment portfolio
3.9 Key initiatives and news
3.10 Regulatory landscape
3.10.1 North America
3.10.2 Europe
3.10.3 Asia Pacific
3.10.4 Latin America
3.10.5 MEA
3.11 Use cases
3.12 Industry impact forces
3.12.1 Growth drivers
3.12.1.1 Growing investments in AI
3.12.1.2 Increasingly empowered consumer
3.12.1.3 Rising disruptive technologies
3.12.1.4 Advent of new business models
3.12.1.5 Advancement in data science
3.12.2 Industry pitfalls & challenges
3.12.2.1 Limited public-private partnership to address social implications directly
3.12.2.2 Privacy issues associated with the use of AI Growth potential analysis
3.13 Growth potential analysis
3.14 Porter’s analysis
3.15 PESTEL analysis
Chapter 4 Competitive Landscape, 2022
4.1 Introduction
4.2 Company market share, 2022
4.3 Competitive analysis of major market players, 2022
4.3.1 Amazon Web Services (AWS)
4.3.2 Alphabet Inc
4.3.3 International Business Machines Corporation(IBM)
4.3.4 Microsoft Corporation
4.3.5 Intel Corporation
4.4 Competitive analysis of innovative market players, 2022
4.4.1 Symbotic
4.4.2 Interactions LLC
4.4.3 Lexalytics
4.4.4 Fujitsu
4.4.5 Ibenta Technologies
4.5 Competitive positioning matrix
4.6 Stratgic outlook matrix
Chapter 5 AI in Retail Market, By Component
5.1 Key trends, by component
5.2 Solution
5.2.1 Market estimates and forecast, 2018 – 2032
5.2.2 Chatbots
5.2.2.1 Market estimates and forecast, 2018 – 2032
5.2.3 Customer Behavior Tracking
5.2.3.1 Market estimates and forecast, 2018 – 2032
5.2.4 CRM
5.2.4.1 Market estimates and forecast, 2018 – 2032
5.2.5 Inventory Management
5.2.5.1 Market estimates and forecast, 2018 – 2032
5.2.6 Price Optimization
5.2.6.1 Market estimates and forecast, 2018 – 2032
5.2.7 Recommendation Engines
5.2.7.1 Market estimates and forecast, 2018 – 2032
5.2.8 Supply Chain Management
5.2.8.1 Market estimates and forecast, 2018 – 2032
5.2.9 Visual Search & Visual Listen
5.2.9.1 Market estimates and forecast, 2018 – 2032
5.2.10 Others
5.2.10.1 Market estimates and forecast, 2018 – 2032
5.3 Services
5.3.1 Market estimates and forecast, 2018 – 2032
5.3.2 Professional Service
5.3.2.1 Market estimates and forecast, 2018 – 2032
5.3.3 Managed Service
5.3.3.1 Market estimates and forecast, 2018 – 2032
Chapter 6 AI in Retail Market, By Technology
6.1 Key trends, by technology
6.2 Machine Learning
6.2.1 Market estimates and forecast, 2018 – 2032
6.3 Natural Language Processing
6.3.1 Market estimates and forecast, 2018 – 2032
6.4 Computer Vision
6.4.1 Market estimates and forecast, 2018 – 2032
6.5 Others
6.5.1 Market estimates and forecast, 2018 – 2032
Chapter 7 AI in Retail Market, By Application
7.1 Key trends, by application
7.2 Automated Merchandising
7.2.1 Market estimates and forecast, 2018 – 2032
7.3 Programmatic Advertising
7.3.1 Market estimates and forecast, 2018 – 2032
7.4 Market Forecasting
7.4.1 Market estimates and forecast, 2018 – 2032
7.5 In Store AI & location optimization
7.5.1 Market estimates and forecast, 2018 – 2032
7.6 Data Science
7.6.1 Market estimates and forecast, 2018 – 2032
7.7 Others
7.7.1 Market estimates and forecast, 2018 – 2032
Chapter 8 AI in Retail Market, By Region
8.1 Key trends, by region
8.2 North America
8.2.1 Market estimates and forecast, by component, 2018 – 2032
8.2.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.2.1.2 Market estimates and forecast, by services, 2018 – 2032
8.2.2 Market estimates and forecast, by technology, 2018 – 2032
8.2.3 Market estimates and forecast, by application, 2018 – 2032
8.2.4 U.S.
8.2.4.1 Market estimates and forecast, by component, 2018 – 2032
8.2.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.2.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.2.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.2.4.3 Market estimates and forecast, by application 2018 – 2032
8.2.5 Canada
8.2.5.1 Market estimates and forecast, by component, 2018 – 2032
8.2.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.2.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.2.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.2.5.3 Market estimates and forecast, by application 2018 – 2032
8.3 Europe
8.3.1 Market estimates and forecast, by component, 2018 – 2032
8.3.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.3 Market estimates and forecast, by application, 2018 – 2032
8.3.4 UK
8.3.4.1 Market estimates and forecast, by component, 2018 – 2032
8.3.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.4.3 Market estimates and forecast, by application 2018 – 2032
8.3.5 Germany
8.3.5.1 Market estimates and forecast, by component, 2018 – 2032
8.3.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.5.3 Market estimates and forecast, by application 2018 – 2032
8.3.6 France
8.3.6.1 Market estimates and forecast, by component, 2018 – 2032
8.3.6.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.6.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.6.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.6.3 Market estimates and forecast, by application 2018 – 2032
8.3.7 Spain
8.3.7.1 Market estimates and forecast, by component, 2018 – 2032
8.3.7.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.7.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.7.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.7.3 Market estimates and forecast, by application 2018 – 2032
8.3.8 Sweden
8.3.8.1 Market estimates and forecast, by component, 2018 – 2032
8.3.8.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.8.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.8.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.8.3 Market estimates and forecast, by application 2018 – 2032
8.3.9 Switzerland
8.3.9.1 Market estimates and forecast, by component, 2018 – 2032
8.3.9.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.3.9.1.2 Market estimates and forecast, by services, 2018 – 2032
8.3.9.2 Market estimates and forecast, by technology, 2018 – 2032
8.3.9.3 Market estimates and forecast, by application 2018 – 2032
8.4 Asia Pacific
8.4.1 Market estimates and forecast, by component, 2018 – 2032
8.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.3 Market estimates and forecast, by application, 2018 – 2032
8.4.4 China
8.4.4.1 Market estimates and forecast, by component, 2018 – 2032
8.4.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.4.3 Market estimates and forecast, by application 2018 – 2032
8.4.5 India
8.4.5.1 Market estimates and forecast, by component, 2018 – 2032
8.4.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.5.3 Market estimates and forecast, by application 2018 – 2032
8.4.6 Japan
8.4.6.1 Market estimates and forecast, by component, 2018 – 2032
8.4.6.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.6.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.6.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.6.3 Market estimates and forecast, by application 2018 – 2032
8.4.7 Australia
8.4.7.1 Market estimates and forecast, by component, 2018 – 2032
8.4.7.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.7.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.7.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.7.3 Market estimates and forecast, by application 2018 – 2032
8.4.8 South Korea
8.4.8.1 Market estimates and forecast, by component, 2018 – 2032
8.4.8.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.8.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.8.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.8.3 Market estimates and forecast, by application 2018 – 2032
8.4.9 Singapore
8.4.9.1 Market estimates and forecast, by component, 2018 – 2032
8.4.9.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.4.9.1.2 Market estimates and forecast, by services, 2018 – 2032
8.4.9.2 Market estimates and forecast, by technology, 2018 – 2032
8.4.9.3 Market estimates and forecast, by application 2018 – 2032
8.5 Latin America
8.5.1 Market estimates and forecast, by component, 2018 – 2032
8.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.5.3 Market estimates and forecast, by application, 2018 – 2032
8.5.4 Brazil
8.5.4.1 Market estimates and forecast, by component, 2018 – 2032
8.5.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.5.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.5.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.5.4.3 Market estimates and forecast, by application 2018 – 2032
8.5.5 Mexico
8.5.5.1 Market estimates and forecast, by component, 2018 – 2032
8.5.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.5.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.5.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.5.5.3 Market estimates and forecast, by application 2018 – 2032
8.6 MEA
8.6.1 Market estimates and forecast, by component, 2018 – 2032
8.6.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.6.1.2 Market estimates and forecast, by services, 2018 – 2032
8.6.2 Market estimates and forecast, by technology, 2018 – 2032
8.6.3 Market estimates and forecast, by application, 2018 – 2032
8.6.4 UAE
8.6.4.1 Market estimates and forecast, by component, 2018 – 2032
8.6.4.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.6.4.1.2 Market estimates and forecast, by services, 2018 – 2032
8.6.4.2 Market estimates and forecast, by technology, 2018 – 2032
8.6.4.3 Market estimates and forecast, by application 2018 – 2032
8.6.5 Israel
8.6.5.1 Market estimates and forecast, by component, 2018 – 2032
8.6.5.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.6.5.1.2 Market estimates and forecast, by services, 2018 – 2032
8.6.5.2 Market estimates and forecast, by technology, 2018 – 2032
8.6.5.3 Market estimates and forecast, by application 2018 – 2032
8.6.6 South Africa
8.6.6.1 Market estimates and forecast, by component, 2018 – 2032
8.6.6.1.1 Market estimates and forecast, by solution, 2018 – 2032
8.6.6.1.2 Market estimates and forecast, by services, 2018 – 2032
8.6.6.2 Market estimates and forecast, by technology, 2018 – 2032
8.6.6.3 Market estimates and forecast, by application 2018 – 2032
Chapter 9 Company Profiles
9.1 Amazon Web Services (AWS)
9.1.1 Business Overview
9.1.2 Financial Data
9.1.3 Product Landscape
9.1.4 Strategic Outlook
9.1.5 SWOT Analysis
9.2 Baidu Inc
9.2.1 Business Overview
9.2.2 Financial Data
9.2.3 Product Landscape
9.2.4 Strategic Outlook
9.2.5 SWOT Analysis
9.3 BloomReach Inc
9.3.1 Business Overview
9.3.2 Financial Data
9.3.3 Product Landscape
9.3.4 Strategic Outlook
9.3.5 SWOT Analysis
9.4 CognitiveScale Inc
9.4.1 Business Overview
9.4.2 Financial Data
9.4.3 Product Landscape
9.4.4 Strategic Outlook
9.4.5 SWOT Analysis
9.5 Google Inc.
9.5.1 Business Overview
9.5.2 Financial Data
9.5.3 Product Landscape
9.5.4 Strategic Outlook
9.5.5 SWOT Analysis
9.6 IBM Corporation
9.6.1 Business Overview
9.6.2 Financial Data
9.6.3 Product Landscape
9.6.4 Strategic Outlook
9.6.5 SWOT Analysis
9.7 Ibenta Technologies
9.7.1 Business Overview
9.7.2 Financial Data
9.7.3 Product Landscape
9.7.4 Strategic Outlook
9.7.5 SWOT Analysis
9.8 Intel Corporation
9.8.1 Business Overview
9.8.2 Financial Data
9.8.3 Product Landscape
9.8.4 Strategic Outlook
9.8.5 SWOT Analysis
9.9 Interactions LLC
9.9.1 Business Overview
9.9.2 Financial Data
9.9.3 Product Landscape
9.9.4 Strategic Outlook
9.9.5 SWOT Analysis
9.10 Lexalytics Inc.
9.10.1 Business Overview
9.10.2 Financial Data
9.10.3 Product Landscape
9.10.4 Strategic Outlook
9.10.5 SWOT Analysis
9.11 Microsoft Corporation
9.11.1 Business Overview
9.11.2 Financial Data
9.11.3 Product Landscape
9.11.4 Strategic Outlook
9.11.5 SWOT Analysis
9.12 Next IT Corp.
9.12.1 Business Overview
9.12.2 Financial Data
9.12.3 Product Landscape
9.12.4 Strategic Outlook
9.12.5 SWOT Analysis
9.13 Nvidia Corporation
9.13.1 Business Overview
9.13.2 Financial Data
9.13.3 Product Landscape
9.13.4 Strategic Outlook
9.13.5 SWOT Analysis
9.14 Oracle Corporation
9.14.1 Business Overview
9.14.2 Financial Data
9.14.3 Product Landscape
9.14.4 Strategic Outlook
9.14.5 SWOT Analysis
9.15 RetailNext Inc.
9.15.1 Business Overview
9.15.2 Financial Data
9.15.3 Product Landscape
9.15.4 Strategic Outlook
9.15.5 SWOT Analysis
9.16 Salesforce.com Inc.
9.16.1 Business Overview
9.16.2 Financial Data
9.16.3 Product Landscape
9.16.4 Strategic Outlook
9.16.5 SWOT Analysis
9.17 SAP SE
9.17.1 Business Overview
9.17.2 Financial Data
9.17.3 Product Landscape
9.17.4 Strategic Outlook
9.17.5 SWOT Analysis
9.18 Sentient Technologies
9.18.1 Business Overview
9.18.2 Financial Data
9.18.3 Product Landscape
9.18.4 Strategic Outlook
9.18.5 SWOT Analysis
9.19 Visenze
9.19.1 Business Overview
9.19.2 Financial Data
9.19.3 Product Landscape
9.19.4 Strategic Outlook
9.19.5 SWOT Analysis
9.20 Symbotic
9.20.1 Business Overview
9.20.2 Financial Data
9.20.3 Product Landscape
9.20.4 Strategic Outlook
9.20.5 SWOT Analysis
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Base Year: 2022
Companies covered: 20
Tables & Figures: 392
Countries covered: 20
Pages: 280
Download Free PDF
Base Year: 2022
Companies covered: 20
Tables & Figures: 392
Countries covered: 20
Pages: 280
Download Free PDF
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Preeti Wadhwani. 2023, January. AI in Retail Market Size, By Component (Solution [Chatbot, Customer Behavior Tracking, CRM, Inventory Management, Price Optimization, Recommendation Engine, Supply Chain Management, Visual Search], Service), By Technology, Application & Forecast, 2023-2032 (Report ID: GMI2568). Global Market Insights Inc. Retrieved March 30, 2026, from https://www.gminsights.com/toc/details/artificial-intelligence-ai-retail-market
AI in Retail Market
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AI in Retail Market Size
AI in Retail Market size valued at USD 6 billion in 2022 and is slated to witness over 30% CAGR from 2023 to 2032. Driven by the extensive use of product identification and computer vision technologies in retail warehouses.
Artificial intelligence (AI) has wide-ranging applications and has become a future tool for advancement. Healthcare, automotive, manufacturing, and several other booming industries are increasingly integrating AI technologies for everyday tasks. The increased inclination of Gen Z toward online shopping trends in the new era of advanced businesses is accelerating the use of AI in the retail market. The expanding Gen Z population has created the most technology-savvy and mobile-friendly consumer base. Their strong preference to shop online is set to encourage traditional retailers to adopt AI solutions and services.
Furthermore, cashier-less checkouts are another major benefit of integrating AI in the retail sector that is fueling the industry growth. Using computer vision and big data analytics, retailers are transforming routine shopping into intelligent shopping. For instance, in February 2022, Amazon rolled out its Just Walk Out cashier-less technology at its new Amazon Fresh grocery store in Ventura County, California, to offer customers a fully autonomous checkout option.
Complex organizational structures may restrain industry progression
The organizational framework of retailers is a major factor restraining the AI in retail market growth. Administrative culture can hinder the adoption of AI in businesses, especially in companies with underdeveloped analytical decision-making and digital transformation processes that create suspicion in algorithmic decision-making, fueled by the perception that studies and recommendations are unclear. As per KPMG’s Living in an AI World 2020 report, 62 percent of retail participants were not supportive of AI adoption due to a loss of job security. Nevertheless, artificial intelligence offers the potential to help individuals with tedious, time-consuming tasks, which is speculated to prompt retailers to adopt AI services.
AI in Retail Market Analysis
According to the report, the computer vision technology segment held more than a 15% share of the AI in retail market in 2022. The prevalent utilization of computer vision technology by merchants for several in-store applications to compete with their online rivals is driving the market demand. For instance, in September 2022, Kroger Co., an American retailer, rolled out its visual AI-based self-checkout solution that uses Nvidia’s computer vision and AI capabilities with Evergreen’s Visual AI.
With respect to components, the solution segment is expected to grow at 30% CAGR through 2032. The widespread adoption of analytics solutions by online retailers to widen their client base and offer better customer experience is set to facilitate the industry expansion. For instance, in October 2022, Wayfair, a store-commerce firm, completed a full digital transformation by migrating its data center applications and services to Google Cloud Foundation.
In terms of application, the programmatic advertising segment is projected to cross USD 25 billion by 2032. Today's omnichannel consumers can be more effectively reached through programmatic advertising that delivers continually tailored messaging at a massive scale, which is foreseen to propel segment development. According to the Journal of Service Management, consumer preference for programmatic advertising is directly related to their attitude toward the retailer and perceived ad relevance, which generates real-time ads that match their interests.
Under solution, the AI in retail market size from the price optimization segment is poised to amass substantial gains by 2032, as firms are becoming increasingly competitive to extend their customer reach due to declining product differentiation resulting from the rising use of e-commerce platforms. Moreover, with the e-commerce boom, firms are leveraging AI to determine optimal prices in order to bolster their sales, which is foreseen to drive price optimization solutions uptake.
Regionally, the Europe Artificial Intelligence in retail market is estimated to hold more than 15% revenue share by 2032, attributed to rapid digitalization, shifting customer preferences, and product innovation efforts by industry participants operating in the region. For instance, French retail behemoth Carrefour unveiled its first AI-powered store in Paris – the Flash 10/10 (10 seconds to shop & 10 seconds to pay).
AI in Retail Market Share
Some of the leading companies involved in the AI in retail market include
These companies majorly engage in product innovation and collaborate with retail firms to remain ahead in the competitive landscape.
For instance, in May 2022, Symbotic, a robotics warehouse automation company, announced the deployment of its automation technology at Walmart’s 42 Regional Distribution Centers to improve the accuracy of the retail giant’s inventory and expand the capacity of its warehouses.
Impact of COVID-19 pandemic
The COVID-19 pandemic had a favorable impact on the growth of artificial intelligence in the retail sector. According to IBM, a technology corporation, the emergence of the COVID-19 pandemic pushed many in-store retailers to adopt e-commerce solutions, such as the Salesforce commerce cloud solution, which aids merchants in achieving unified customer experience, omnichannel strategies, and automated market analytics. This enables no-contact pickup services, reservation systems in online stores, delivery of meals, and the development of autonomous online businesses, which has positively influenced the market revenue.
This Artificial Intelligence (AI) in Retail Market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue in USD from 2018 to 2032 for the following segments:
Market, By Component
Market, By Technology
Market, By Application
The above information has been provided for the following regions and countries: