Artificial Intelligence in Retail Market Size, Share, Forecast, & Trends by Offering (Solutions, Services), Technology, Type, Deployment Mode, End User, Geography- Global Forecasts to 2031

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Artificial Intelligence (AI) in Retail Market by Offering (Solutions (Supply Chain Management, Predictive Merchandising, Others), Services), Technology, Type (Online Retail, Offline Retail), Deployment Mode, End User, Geography-Global Forecast to 2031

The research report titled, 'Artificial Intelligence (AI) in Retail Market by Offering (Solutions (Supply Chain Management, Predictive Merchandising, Others), Services), Technology, Type (Online Retail, Offline Retail), Deployment Mode, End User, Geography-Global Forecast to 2031, provides an in-depth analysis of the artificial intelligence in retail market across five major geographies and emphasizes on the current market trends, market sizes, market shares, recent developments, and forecasts till 2031.

The artificial intelligence in retail market is projected to reach $92.7 billion by 2031, at a CAGR of 38.6% from 2024 to 2031.

The increasing number of smart stores, the growing need to enhance end-user experience and improve productivity, and the rising use of AI in retail for inventory management are factors driving the growth of artificial intelligence in the retail market. However, the market growth is restrained by a lack of technology adoption in the unorganized retail sector and a lack of skilled workforce. In addition, the increasing adoption of AI-powered voice-enabled devices and the rising demand for AI-powered personal shopping services are expected to create growth opportunities for market players. However, legal concerns, data privacy issues, and integration of AI systems with existing infrastructure.

The global artificial intelligence in retail market is segmented by offering (solutions (supply chain management, predictive merchandising, customer experience management, sentiment analysis, payment processing, price optimization, and other solutions and services (managed services, professional services)); technology (machine learning, natural language processing, computer vision, and other technologies); type (offline retail (supermarkets, hypermarkets, specialty stores, department stores, other offline retailers), online retail); deployment mode (cloud-based deployments, on-premise deployments); and end user (food & groceries, health & wellness, automotive, fashion & clothing, electronics & white goods, general utility products, cosmetics & personal care and other end users). This study also evaluates industry competitors and analyses the regional and country-level markets.

Based on offering, the artificial intelligence in retail market is segmented into solutions and services. In 2024, the solutions segment is expected to account for the larger share of over 72.0% of the global artificial intelligence in retail market. The increased importance of AI in the retail sector, increased adoption of AI in retail solutions to improve retail operations for personalized shopping experiences, and increased focus of key market players on product launches and enhancements are factors contributing to the segment's dominant position in the artificial intelligence in the retail market. However, the services segment is expected to grow at the highest CAGR during the forecast period.

Based on technology, the artificial intelligence in retail market is segmented into machine learning, natural language processing, computer vision, and other technologies. In 2024, the machine learning segment is expected to account for the largest share of over 36.0% of the artificial intelligence in retail market. The increasing adoption of machine learning by retailers to enhance operational efficiency, improve customer experiences, and drive strategic decision-making are factors contributing to the segment's dominant position in the artificial intelligence in the retail market. Moreover, the machine learning segment is anticipated to register the highest CAGR during the forecast period.

Based on type, the artificial intelligence in retail market is segmented into online retail and offline retail. In 2024, the online retail segment is expected to account for a larger share of the artificial intelligence in retail market. This segment's large market share is primarily attributed to the growing use of AI-powered solutions by online retailers to improve efficiency, enhance customer satisfaction, and maintain a competitive edge in a rapidly evolving marketplace. Moreover, the online retail segment is expected to record a higher CAGR during the forecast period.

Based on deployment mode, the artificial intelligence in retail market is segmented into on-premise deployments and cloud-based deployments. In 2024, the on-premise deployments segment is expected to account for a larger share of the artificial intelligence in retail market. The higher preference for on-premise deployments among large enterprises due to the availability of trained IT professionals & infrastructure and to ensure data security and compliance are factors contributing to the segment's dominant position in the artificial intelligence in retail market. Moreover, the cloud-based Deployments segment is expected to record a higher CAGR during the forecast period.

Based on end user, the artificial intelligence in retail market is segmented into food & groceries, health & wellness, automotive, fashion & clothing, electronics & white goods, general utility products, cosmetics & personal care, and other end users. In 2024, the food & groceries segment is expected to account for the largest share of over 22.0% of the artificial intelligence in retail market. The rising adoption of AI by food & grocery retailers to enhance inventory management, to provide personalized shopping experiences to customers and ensure quality control throughout the supply chain are factors contributing to the segment's dominant position in the artificial intelligence in retail market. However, the fashion & clothing segment is expected to grow at the highest CAGR during the forecast period.

Based on geography, the artificial intelligence in retail market is majorly segmented into five regions: North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. In 2024, North America is expected to account for the largest share of over 32.0% of the artificial intelligence in retail market, followed by Asia-Pacific and Europe. The high adoption of emerging technologies, the presence of the key market players, increasing investments in AI technology, and the rising focus of retail enterprises for providing better shopping experiences to customers are factors contributing to the region's dominant position in the artificial intelligence in the retail market. However, Asia-Pacific is expected to record the highest CAGR of 40.6% during the forecast period.

The artificial intelligence in retail market is characterized by a moderately competitive scenario due to the presence of many large- and small-sized global, regional, and local players. The key players operating in the artificial intelligence in retail market are Amazon.com, Inc. (U.S.), Google LLC (U.S.), IBM Corporation (U.S.), Intel Corporation (U.S.), Microsoft Corporation (U.S.), Nvidia Corporation (U.S.), Oracle Corporation (U.S.), SAP SE (Germany), BloomReach, Inc. (U.S.), Salesforce.com, Inc. (U.S.), ViSenze (Singapore), SymphonyAI LLC (U.S.), Daisy Intelligence Corporation (Canada), Conversica (U.S.), and RetailNext Inc. (U.S.).

Key questions answered in the report:

Which are the high-growth market segments based on offering, technology, type, deployment mode, and end user?
What was the historical market for artificial intelligence in retail?
What are the market forecasts and estimates for the period 2024-2031?
What are the major drivers, restraints, and opportunities in the artificial intelligence in retail market?
Who are the major players, and what shares do they hold in the artificial intelligence in retail market?
What is the competitive landscape like in the artificial intelligence in retail market?
What are the recent developments in the artificial intelligence in retail market?
What are the different strategies adopted by the major players in the artificial intelligence in retail market?
What are the key geographic trends, and which are the high-growth countries?
Who are the local emerging players in the artificial intelligence in retail market, and how do they compete with the other players?

Scope of the report:

Artificial Intelligence in Retail Market Assessment-by Offering

Solutions
Supply Chain Management
Predictive Merchandising
Customer Experience Management
Sentiment Analysis
Payment Processing
Price Optimization
Other Solutions
Services
Managed Services
Professional Services

Artificial Intelligence in Retail Market Assessment-by Technology

Machine Learning
Natural Language Processing
Computer Vision
Other Technologies

Artificial Intelligence in Retail Market Assessment-by Type

Offline Retail
Supermarkets
Hypermarkets
Specialty Stores
Department Stores
Other Offline Retailers
Online Retail

Artificial Intelligence in Retail Market Assessment-by Deployment Mode

Cloud-based Deployments
On-premise Deployments

Artificial Intelligence in Retail Market Assessment-by End User

Food & Groceries
Health & Wellness
Automotive
Fashion & Clothing
Electronics & White Goods
General Utility Products
Cosmetics & Personal Care
Other End Users

Artificial Intelligence in Retail Market Assessment-by Geography

North America
- U.S.
- Canada
Europe
- U.K.
- Germany
- France
- Italy
- Spain
- Switzerland
- Netherlands
- Rest of Europe
Asia-Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Malaysia
- Rest of Asia-Pacific
Latin America
- Mexico
- Brazil
- Rest of Latin America
Middle East & Africa
- UAE
- Israel
- Rest of Middle East & Africa

Product Code: MRICT - 104227

1. Introduction

1.1. Market Definition
1.2. Currency & Limitations
- 1.2.1. Currency
- 1.2.2. Limitations

2. Research Methodology

2.1. Research Approach
2.2. Process of Data Collection and Validation
- 2.2.1. Secondary Research
- 2.2.2. Primary Research/Interviews with Key Opinion Leaders of the Industry
2.3. Market Sizing and Forecast
- 2.3.1. Market Size Estimation Approach
- 2.3.2. Growth Forecast Approach
2.4. Assumption for the Study

3. Executive Summary

3.1. Market Overview
3.2. Market Analysis, by Offering
3.3. Market Analysis, by Application
3.4. Market Analysis, by Technology
3.5. Market Analysis, by Retail Type
3.6. Market Analysis, by Deployment Mode
3.7. Market Analysis, by End User
3.8. Market Analysis, by Geography
3.9. Competitive Analysis

4. Market Insights

4.1. Overview
4.2. Factors Affecting Market Growth
- 4.2.1. Drivers
  - 4.2.1.1. Increasing Number of Smart Stores
  - 4.2.1.2. Growing Need to Enhance Customer Experience and Improve Productivity
  - 4.2.1.3. Rising Use of AI for Inventory Management
- 4.2.2. Restraints
  - 4.2.2.1. Low Technology Adoption Rate in the Unorganized Retail Sector
  - 4.2.2.2. Shortage of Skilled Professionals
- 4.2.3. Opportunities
  - 4.2.3.1. Rising Adoption of AI-based Voice Assistants
  - 4.2.3.2. Growing Demand for AI-powered Personal Shopping Services
- 4.2.4. Challenges
  - 4.2.4.1. Legal Concerns and Data Privacy Issues
  - 4.2.4.2. Complexities Associated with Integrating AI Technologies into Existing Systems
4.3. Trends
4.4. Case Studies
4.5. Porter's Five Forces Analysis
4.6. Vendor Selection Criteria/Factors Affecting Buying Decisions
4.7. Product/Technology Adoption Trends Across Different Customer/End User/Industry Segments

5. Artificial Intelligence in Retail Market Assessment-by Offering

5.1. Overview
5.2. Solutions
- 5.2.1. Supply Chain Management
- 5.2.2. Predictive Merchandising
- 5.2.3. Customer Experience Management
- 5.2.4. Sentiment Analysis
- 5.2.5. Payment Processing
- 5.2.6. Price Optimization
- 5.2.7. Other Solutions
5.3. Services
- 5.3.1. Managed Services
- 5.3.2. Professional Services

6. Artificial Intelligence in Retail Market Assessment-by Technology

6.1. Overview
6.2. Machine Learning
6.3. Natural Language Processing
6.4. Computer Vision
6.5. Other Technologies

7. Artificial Intelligence in Retail Market Assessment-by Type

7.1. Overview
7.2. Offline Retail
- 7.2.1. Supermarkets
- 7.2.2. Hypermarkets
- 7.2.3. Specialty Stores
- 7.2.4. Department Stores
- 7.2.5. Other Offline Retailers
7.3. Online Retail

8. Artificial Intelligence in Retail Market Assessment-by Deployment Mode

8.1. Overview
8.2. Cloud-based Deployments
8.3. On-premise Deployments

9. Artificial Intelligence in Retail Market Assessment-by End User

9.1. Overview
9.2. Food & Groceries
9.3. Health & Wellness
9.4. Automotive
9.5. Fashion & Clothing
9.6. Electronics & White Goods
9.7. General Utility Products
9.8. Cosmetics & Personal Care
9.9. Other End Users

10. Artificial Intelligence in Retail Market Assessment-by Geography

10.1. North America
- 10.1.1. U.S.
- 10.1.2. Canada
10.2. Europe
- 10.2.1. Germany
- 10.2.2. U.K.
- 10.2.3. France
- 10.2.4. Italy
- 10.2.5. Spain
- 10.2.6. Switzerland
- 10.2.7. Netherlands
- 10.2.8. Rest of Europe
10.3. Asia-Pacific
- 10.3.1. Japan
- 10.3.2. China
- 10.3.3. India
- 10.3.4. South Korea
- 10.3.5. Singapore
- 10.3.6. Malaysia
- 10.3.7. Rest of Asia-Pacific
10.4. Latin America
- 10.4.1. Mexico
- 10.4.2. Brazil
- 10.4.3. Rest of Latin America
10.5. Middle East & Africa
- 10.5.1. UAE
- 10.5.2. Israel
- 10.5.3. Rest of Middle East & Africa

11. Artificial Intelligence in Retail Market Assessment-Competitive Analysis

11.1. Overview
11.2. Key Growth Strategies
11.3. Competitive Dashboard
- 11.3.1. Industry Leaders
- 11.3.2. Market differentiators
- 11.3.3. Vanguards
- 11.3.4. Contemporary Stalwarts
11.4. Vendor Market Positioning
11.5. Market Share/Ranking by the Key Players

12. Company Profiles (Company Overview, Financial Overview, Product Portfolio, Strategic Developments, and SWOT Analysis)

12.1. Amazon.com, Inc.
12.2. Google LLC
12.3. IBM Corporation
12.4. Intel Corporation
12.5. Microsoft Corporation
12.6. Nvidia Corporation
12.7. Oracle Corporation
12.8. SAP SE
12.9. BloomReach, Inc.
12.10. Salesforce.com, Inc.
12.11. ViSenze
12.12. SymphonyAI LLC
12.13. Daisy Intelligence Corporation
12.14. Conversica
12.15. RetailNext Inc.

(Note: SWOT analysis of the top 5 companies will be provided)

13. Appendix

13.1. Available Customizations
13.2. Related Reports