Product Code: BWC23281
Global Artificial Intelligence (AI) in Retail Market Size Zooming More Than 6X to Touch USD 39.4 Billion by 2029
Global artificial intelligence (AI) in retail market is flourishing because of increasing advancements in AI technology, a growing demand for personalized shopping experiences, and increasing competition among retailers.
BlueWeave Consulting, a leading strategic consulting and market research firm, in its recent study, estimated global artificial intelligence (AI) in retail market size at USD 6.21 billion in 2022. During the forecast period between 2023 and 2029, BlueWeave expects global artificial intelligence (AI) in retail market size to grow at a robust CAGR of 30.33% reaching a value of USD 39.35 billion by 2029. Major growth factors of global artificial intelligence (AI) in retail market include growing number of internet users and smart device usage, heightened awareness of AI, big data, and analytics, and government efforts to promote digitization. Also, the adoption of omnichannel retailing tactics, unexplored prospects for boosting sales efficiency, the drive for enterprises to streamline their business processes, and the desire to improve end-user experience and capitalize on market trends are all contributing to the expansion of the global artificial intelligence in retail market. However, high implementation and maintenance costs associated with AI solutions, particularly for small and medium-sized retailers, are anticipated to restrain the overall market growth during the period in analysis.
Global Artificial Intelligence (AI) in Retail Market - Overview
Global artificial intelligence (AI) in retail market refers to the application of advanced technologies, such as machine learning (ML), natural language processing (NLP), and computer vision, to improve the efficiency, accuracy, and effectiveness of various retail operations. The use of AI in the retail industry enables retailers to gain insights into consumer behavior and preferences, optimize inventory and supply chain management, enhance customer engagement, and deliver personalized shopping experiences. The market encompasses AI-powered software, platforms, and services designed to automate and streamline retail operations, including sales forecasting, inventory management, demand planning, customer service, and marketing. The AI in retail market is witnessing significant growth, due to the increasing adoption of advanced technologies, the proliferation of e-commerce, and the growing demand for innovative retail solutions that enhance productivity, profitability, and customer satisfaction.
Impact of COVID-19 on Global Artificial Intelligence (AI) in Retail Market
COVID-19 had a negative impact on the global economy, causing governments to shut down retail operations and import-export activities, disrupting supply chains. The pandemic has also resulted in significant changes in consumer behavior and product demand, affecting retail stores, factories, and logistics services. Many non-essential businesses have temporarily closed, leaving only food and grocery stores and pharmacies open, greatly impacting brick-and-mortar retail stores. Consequently, online shopping channels have become more significant, prompting retailers to adopt sustainability initiatives that integrate with their digital presence. As a result, organizations in the retail sector are increasingly using AI solutions to improve their operations and meet customer demands. They are employing online platforms to provide personalized customer engagement, inventory management, supply chain management, programmatic advertising, smart recommendations, and chatbots. The COVID-19 crisis has also allowed leading retail players to restructure and revisit their existing strategies and product portfolios. However, the situation is constantly evolving, and companies in this market are adapting to this new reality and planning for various scenarios.
Global Artificial Intelligence (AI) in Retail Market - By Technology
Based on technology, global artificial intelligence (AI) in retail market is segmented into Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision. The machine learning segment dominates the global artificial intelligence (AI) in retail market. Machine learning is capable of swiftly analyzing large volumes of data and can provide personalized experiences to customers, making it a valuable tool for retailers. It can also enhance supply chain systems and demand forecasts, leading to improved inventory efficiency. For instance, Amazon SageMaker, a fully-managed service offered by Amazon Inc., utilizes ML for various applications, ranging from predictive analytics to improving the customer experience. The NLP segment is expected to witness significant growth during the forecast period. The increasing demand for AI-powered chatbots and the rise of data analysis are expected to drive advancements in NLP. NLP-powered chatbots can improve customer interactions, including mobile interfaces and touchscreen, providing a more interactive and engaging experience. Additionally, NLP can aid in sentiment analysis for evaluating call center interactions, customer messages, social media posts, and online reviews.
Competitive Landscape
Major players operating in global artificial intelligence (AI) in retail market include IBM Corporation, Amazon Web Services, Inc., Microsoft Corporation, Salesforce.com, Inc., Symphony RetailAI, RetailNext, Oracle Corporation, Infosys Limited, HCL Technologies Limited, Manthan Software Services Pvt. Ltd., Capillary Technologies, Numenta, and Sentient Technologies Holdings Limited. To further enhance their market share, these companies employ various strategies, including mergers and acquisitions, partnerships, joint ventures, license agreements, and new product launches.
The in-depth analysis of the report provides information about growth potential, upcoming trends, and statistics of Global Artificial Intelligence (AI) in Retail Market. It also highlights the factors driving forecasts of total market size. The report promises to provide recent technology trends in Global Artificial Intelligence (AI) in Retail Market and industry insights to help decision-makers make sound strategic decisions. Furthermore, the report also analyzes the growth drivers, challenges, and competitive dynamics of the market.
Table of Contents
1. Research Framework
- 1.1. Research Objective
- 1.2. Product Overview
- 1.3. Market Segmentation
2. Executive Summary
3. Global Artificial Intelligence (AI) in Retail Market Insights
- 3.1. Industry Value Chain Analysis
- 3.2. DROC Analysis
- 3.2.1. Growth Drivers
- 3.2.1.1. Growing demand for personalized shopping experiences and increasing competition among retailers
- 3.2.1.2. Advancements in AI technology, that enable retailers to analyze and interpret large volumes of data more accurately and efficiently
- 3.2.2. Restraints
- 3.2.2.1. High implementation and maintenance costs associated with AI solutions, particularly for small and mid-sized retailers
- 3.2.3. Opportunities
- 3.2.3.1. Increasing adoption of cloud-based AI solutions and the emergence of AI-as-a-service models that make AI more accessible to small and mid-sized retailers
- 3.2.3.2. Growth in e-commerce and omnichannel retailing, which provide new opportunities for retailers to leverage AI to enhance customer experiences
- 3.2.4. Challenges
- 3.2.4.1. Competition and consolidation within the AI market
- 3.3. Technology Advancements/Recent Developments
- 3.4. Regulatory Framework
- 3.5. Porter's Five Forces Analysis
- 3.5.1. Bargaining Power of Suppliers
- 3.5.2. Bargaining Power of Buyers
- 3.5.3. Threat of New Entrants
- 3.5.4. Threat of Substitutes
- 3.5.5. Intensity of Rivalry
4. Global Artificial Intelligence (AI) in Retail Market Overview
- 4.1. Market Size & Forecast, 2019-2029
- 4.1.1. By Value (USD Million)
- 4.2. Market Share and Forecast
- 4.2.1. By Offerings
- 4.2.1.1. Solution
- 4.2.1.2. Service
- 4.2.2. By Technology
- 4.2.2.1. Machine Learning
- 4.2.2.2. Natural Language Processing (NLP)
- 4.2.2.3. Computer Vision
- 4.2.3. By Application
- 4.2.3.1. Automated Merchandising
- 4.2.3.2. Programmatic Advertising
- 4.2.3.3. Market Forecasting
- 4.2.3.4. In-Store AI & Location Optimization
- 4.2.3.5. Data Science
- 4.2.4. By Region
- 4.2.4.1. North America
- 4.2.4.2. Europe
- 4.2.4.3. Asia Pacific (APAC)
- 4.2.4.4. Latin America (LATAM)
- 4.2.4.5. Middle East and Africa (MEA)
5. North America Artificial Intelligence (AI) in Retail Market
- 5.1. Market Size & Forecast, 2019-2029
- 5.1.1. By Value (USD Million)
- 5.2. Market Share & Forecast
- 5.2.1. By Offerings
- 5.2.2. By Technology
- 5.2.3. By Application
- 5.2.4. By Country
- 5.2.4.1. United States
- 5.2.4.1.1. By Offerings
- 5.2.4.1.2. By Technology
- 5.2.4.1.3. By Application
- 5.2.4.2. Canada
- 5.2.4.2.1. By Offerings
- 5.2.4.2.2. By Technology
- 5.2.4.2.3. By Application
6. Europe Artificial Intelligence (AI) in Retail Market
- 6.1. Market Size & Forecast, 2019-2029
- 6.1.1. By Value (USD Million)
- 6.2. Market Share & Forecast
- 6.2.1. By Offerings
- 6.2.2. By Technology
- 6.2.3. By Application
- 6.2.4. By Country
- 6.2.4.1. Germany
- 6.2.4.1.1. By Offerings
- 6.2.4.1.2. By Technology
- 6.2.4.1.3. By Application
- 6.2.4.2. United Kingdom
- 6.2.4.2.1. By Offerings
- 6.2.4.2.2. By Technology
- 6.2.4.2.3. By Application
- 6.2.4.3. Italy
- 6.2.4.3.1. By Offerings
- 6.2.4.3.2. By Technology
- 6.2.4.3.3. By Application
- 6.2.4.4. France
- 6.2.4.4.1. By Offerings
- 6.2.4.4.2. By Technology
- 6.2.4.4.3. By Application
- 6.2.4.5. Spain
- 6.2.4.5.1. By Offerings
- 6.2.4.5.2. By Technology
- 6.2.4.5.3. By Application
- 6.2.4.6. Belgium
- 6.2.4.6.1. By Offerings
- 6.2.4.6.2. By Technology
- 6.2.4.6.3. By Application
- 6.2.4.7. Russia
- 6.2.4.7.1. By Offerings
- 6.2.4.7.2. By Technology
- 6.2.4.7.3. By Application
- 6.2.4.8. The Netherlands
- 6.2.4.8.1. By Offerings
- 6.2.4.8.2. By Technology
- 6.2.4.8.3. By Application
- 6.2.4.9. Rest of Europe
- 6.2.4.9.1. By Offerings
- 6.2.4.9.2. By Technology
- 6.2.4.9.3. By Application
7. Asia-Pacific Artificial Intelligence (AI) in Retail Market
- 7.1. Market Size & Forecast, 2019-2029
- 7.1.1. By Value (USD Million)
- 7.2. Market Share & Forecast
- 7.2.1. By Offerings
- 7.2.2. By Technology
- 7.2.3. By Application
- 7.2.4. By Country
- 7.2.4.1. China
- 7.2.4.1.1. By Offerings
- 7.2.4.1.2. By Technology
- 7.2.4.1.3. By Application
- 7.2.4.2. India
- 7.2.4.2.1. By Offerings
- 7.2.4.2.2. By Technology
- 7.2.4.2.3. By Application
- 7.2.4.3. Japan
- 7.2.4.3.1. By Offerings
- 7.2.4.3.2. By Technology
- 7.2.4.3.3. By Application
- 7.2.4.4. South Korea
- 7.2.4.4.1. By Offerings
- 7.2.4.4.2. By Technology
- 7.2.4.4.3. By Application
- 7.2.4.5. Australia & New Zealand
- 7.2.4.5.1. By Offerings
- 7.2.4.5.2. By Technology
- 7.2.4.5.3. By Application
- 7.2.4.6. Indonesia
- 7.2.4.6.1. By Offerings
- 7.2.4.6.2. By Technology
- 7.2.4.6.3. By Application
- 7.2.4.7. Malaysia
- 7.2.4.7.1. By Offerings
- 7.2.4.7.2. By Technology
- 7.2.4.7.3. By Application
- 7.2.4.8. Singapore
- 7.2.4.8.1. By Offerings
- 7.2.4.8.2. By Technology
- 7.2.4.8.3. By Application
- 7.2.4.9. Vietnam
- 7.2.4.9.1. By Offerings
- 7.2.4.9.2. By Technology
- 7.2.4.9.3. By Application
- 7.2.4.10. Rest of APAC
- 7.2.4.10.1. By Offerings
- 7.2.4.10.2. By Technology
- 7.2.4.10.3. By Application
8. Latin America Artificial Intelligence (AI) in Retail Market
- 8.1. Market Size & Forecast, 2019-2029
- 8.1.1. By Value (USD Million)
- 8.2. Market Share & Forecast
- 8.2.1. By Offerings
- 8.2.2. By Technology
- 8.2.3. By Application
- 8.2.4. By Country
- 8.2.4.1. Brazil
- 8.2.4.1.1. By Offerings
- 8.2.4.1.2. By Technology
- 8.2.4.1.3. By Application
- 8.2.4.2. Mexico
- 8.2.4.2.1. By Offerings
- 8.2.4.2.2. By Technology
- 8.2.4.2.3. By Application
- 8.2.4.3. Argentina
- 8.2.4.3.1. By Offerings
- 8.2.4.3.2. By Technology
- 8.2.4.3.3. By Application
- 8.2.4.4. Peru
- 8.2.4.4.1. By Offerings
- 8.2.4.4.2. By Technology
- 8.2.4.4.3. By Application
- 8.2.4.5. Rest of LATAM
- 8.2.4.5.1. By Offerings
- 8.2.4.5.2. By Technology
- 8.2.4.5.3. By Application
9. Middle East & Africa Artificial Intelligence (AI) in Retail Market
- 9.1. Market Size & Forecast, 2019-2029
- 9.1.1. By Value (USD Million)
- 9.2. Market Share & Forecast
- 9.2.1. By Offerings
- 9.2.2. By Technology
- 9.2.3. By Application
- 9.2.4. By Country
- 9.2.4.1. Saudi Arabia
- 9.2.4.1.1. By Offerings
- 9.2.4.1.2. By Technology
- 9.2.4.1.3. By Application
- 9.2.4.2. UAE
- 9.2.4.2.1. By Offerings
- 9.2.4.2.2. By Technology
- 9.2.4.2.3. By Application
- 9.2.4.3. Qatar
- 9.2.4.3.1. By Offerings
- 9.2.4.3.2. By Technology
- 9.2.4.3.3. By Application
- 9.2.4.4. Kuwait
- 9.2.4.4.1. By Offerings
- 9.2.4.4.2. By Technology
- 9.2.4.4.3. By Application
- 9.2.4.5. South Africa
- 9.2.4.5.1. By Offerings
- 9.2.4.5.2. By Technology
- 9.2.4.5.3. By Application
- 9.2.4.6. Nigeria
- 9.2.4.6.1. By Offerings
- 9.2.4.6.2. By Technology
- 9.2.4.6.3. By Application
- 9.2.4.7. Algeria
- 9.2.4.7.1. By Offerings
- 9.2.4.7.2. By Technology
- 9.2.4.7.3. By Application
- 9.2.4.8. Rest of MEA
- 9.2.4.8.1. By Offerings
- 9.2.4.8.2. By Technology
- 9.2.4.8.3. By Application
10. Competitive Landscape
- 10.1. List of Key Players and Their Offerings
- 10.2. Global Artificial Intelligence (AI) in Retail Market Share Analysis, 2022
- 10.3. Competitive Benchmarking, By Operating Parameters
- 10.4. Key Strategic Developments (Mergers, Acquisitions, Partnerships, etc.)
11. Impact of Covid-19 on Global Artificial Intelligence (AI) in Retail Market
12. Company Profile (Company Overview, Financial Matrix, Competitive Landscape, Key Personnel, Key Competitors, Contact Address, Strategic Outlook, SWOT Analysis)
- 12.1. IBM Corporation
- 12.2. Amazon Web Services, Inc.
- 12.3. Microsoft Corporation
- 12.4. Salesforce.com, Inc.
- 12.5. Symphony RetailAI
- 12.6. RetailNext
- 12.7. Oracle Corporation
- 12.8. Infosys Limited
- 12.9. HCL Technologies Limited
- 12.10. Manthan Software Services Pvt. Ltd.
- 12.11. Capillary Technologies
- 12.12. Numenta
- 12.13. Sentient Technologies Holdings Limited
- 12.14. Other Prominent Players
13. Key Strategic Recommendations
14. Research Methodology
- 14.1. Qualitative Research
- 14.1.1. Primary & Secondary Research
- 14.2. Quantitative Research
- 14.3. Market Breakdown & Data Triangulation
- 14.3.1. Secondary Research
- 14.3.2. Primary Research
- 14.4. Breakdown of Primary Research Respondents, By Region
- 14.5. Assumptions & Limitations