Artificial Intelligence in Retail Market

Report Code TC 5669
Published in Oct, 2024, By MarketsandMarkets™
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Artificial Intelligence in Retail Market by Solution (Personalized Product Recommendation, Visual Search, Virtual Stores, Virtual Customer Assistant, CRM), Type (Generative AI, Other AI), End-user (Online, Offline) - Global Forecast to 2030

 

Overview

The AI in retail market is projected to expand from USD 31.12 billion in 2024 to USD 164.74 billion by 2030, at a CAGR of 32.0% during the forecast period.

The rapid growth of eCommerce and the increasing adoption of omnichannel retail strategies drive AI implementation in the sector. AI enhances the integration of online and offline channels, enabling retailers to provide a consistent and seamless shopping experience. AI tools support activities, such as dynamic pricing, real-time inventory tracking, and personalized promotions across channels, essential for staying competitive in a digital-first retail landscape. As more consumers engage with multiple touchpoints, retailers are turning to AI to optimize their operations and meet the growing demands of omnichannel shoppers.

AI in Retail Market

Attractive Opportunities in the AI in Retail Market

ASIA PACIFIC

Market growth in Asia Pacific can be attributed to the presence of key players in this region and the high growth in eCommerce and mobile shopping, particularly in China, India, and Japan.

Rapid economic expansion in countries such as China, India, and Southeast Asian nations has bolstered the adoption of AI in retail.

Increased funding from governments, venture capitalists, and corporations fuel the development and implementation of AI solutions in retail.

The primary factors driving the growth of the Asia Pacific AI in retail market are the region’s rapid economic growth and favorable government policies, funding, and initiatives.

Tech-savvy consumer base drives demand for AI-enhanced services, such as virtual assistants and recommendation systems, in Asia Pacific.

Use Cases of AI/ Generative AI on Artificial Intelligence in Retail Market

Generative AI is significantly changing the paradigm of AI in retail by driving innovation in personalized customer experiences and operational efficiency. Gen AI’s ability to generate new content, such as product descriptions, marketing campaigns, and visual designs, enables retailers to customize interactions, enhance engagement, and increase sales. Gen AI makes monitoring processes automated and more efficient. Al algorithms can diagnose problems from historical data and current performances and find solutions without human interference. This shift toward predictive management makes systems more reliable, operationally efficient, and less expensive. Al has become a critical tool for retailers to understand better and cater to evolving behaviors with consumer preferences shifting toward digital and on-demand experiences. Generative AI also plays a critical role in customer service by using AI-powered chatbots that offer real-time, context-aware responses, improving service delivery and satisfaction. Furthermore, retailers leverage generative AI for demand forecasting, supply chain optimization, and dynamic pricing strategies, enabling more accurate inventory management and cost savings.

AI in Retail Market Impact

Global AI in Retail Market Dynamics

Driver: Increasing adoption of conversational AI in retail for advice and recommendations

Advancements in technology have increasingly facilitated more natural and seamless communication, leading consumers to seek out conversational AI in retail for guidance actively. Conversational AI, such as chatbots and virtual assistants, enables retailers to take offers and shopping experiences at their fingertips and provide shoppers with personalized recommendations. AI-powered retail chatbots have proven to significantly reduce customer care costs, enhance the customer experience and the experience of customer service agents, and build stronger customer engagement. AI-driven chatbots can handle a large volume of customer inquiries, from answering common questions to providing personalized product recommendations. Retailers use conversational AI to streamline customer service, enhance the shopping experience, and improve overall operational efficiency. Conversational Al gives detailed advice, such as recommending the best fashion trends to go with or recommending shoes for a particular dress. Brands such as Sephora and H&M already use these tools to offer virtual assistance when buying a product.

Restraint: High implementation costs

The implementation of AI in retail often requires substantial investment, which remains a major barrier, particularly for smaller retailers. Al solutions often require hardware, software, and data management structures in even modest applications. The costs are further added because cloud computing services are required to process the large volumes of data required in training Al models. Moreover, using Al requires highly skilled labor, leading to higher employment and training costs. Despite the initial investment, the long-term benefits of AI implementation outweigh the costs for many retailers.

The ongoing operational costs associated with AI, such as system maintenance, updates, and data storage, add another layer of financial burden. Large enterprises are driven by long-term Return On Investment (ROI). At the same time, the sustainable route to profitability for small retail stores is not well highlighted, which may slow down the adoption of Al technology.

 

Opportunity: AI-powered customer engagement

Al technologies offer retailers a lucrative opportunity to enhance customer engagement. By utilizing Al-driven chatbots, recommendation engines, and virtual assistants, retailers can provide personalized, real-time support that significantly boosts customer satisfaction. Al-driven customer service tools, such as Sephora's Virtual Artist and H&M's chatbot, help guide customers through product selections. They provide customers with tailored suggestions based on personal preferences and previous shopping behavior. These Al systems are available 24/7, enabling retailers to engage with customers outside regular business hours and across multiple platforms, enhancing the customer journey.

H&M recently expanded its chatbot capabilities to improve customer interaction by providing personalized recommendations and fashion tips, showcasing how Al can transform retail engagement. Similarly, Amazon uses Al-driven personalization to offer customized product recommendations, contributing to its sales growth.

Challenge: Rising theft and fraud issues

AI technologies are transforming how retailers address theft and fraud, providing advanced tools to enhance security and minimize losses. Real-time surveillance, behavioral pattern analysis, and fraud detection systems powered by AI are used to prevent these issues. According to the 2023 National Retail Security Survey, retailers face an alarming increase in shrinkage, with losses amounting to USD 112.10 billion in 2022, up from USD 93.9 billion the previous year. Organized Retail Crime (ORC) is a major contributor, escalating by 26.5% in the same period. This surge has imposed pressure on Al-based loss prevention and fraud detection systems.

Al tools help enhance surveillance, identify theft patterns, and predict future incidents. However, it is challenging to balance effectiveness with privacy concerns and ensure that All systems do not result in false positives. Misidentification in theft prevention could lead to negative customer experiences, further complicating Al's role in security. Moreover, the National Retail Security Survey report suggests that 66.1% of retailers are allocating more resources to fight crime, signaling increased demand for AI-driven solutions. Yet, implementing Al for fraud detection and asset protection requires noteworthy upfront investment, ongoing training, and fine-tuning of algorithms to adapt to new theft strategies.

Global AI in Retail Market Ecosystem Analysis

The AI in retail market is highly competitive and comprises many vendors who offer solutions to a specific or niche segment of the market. Several changes in the AI in retail market have occurred in recent years. Currently, the vendors are involved in various partnerships and collaborations to develop comprehensive solutions that address a wide range of requirements. Microsoft (US), IBM (US), Google (US), Amazon (US), Oracle (US), Salesforce (US), and NVIDIA (US) are some of the major players operating in this ecosystem.

Top Companies in AI in Retail Market
 

Personalized product recommendations segment to account for largest market share during forecast period

Al-driven personalized product recommendations are essential for improving customer experience and increasing sales. By analyzing customer behavior, past purchases, and preferences, Al algorithms suggest products tailored to individual preferences. This helps retailers offer a more engaging and relevant shopping experience, increasing customer satisfaction and loyalty. Accurate product recommendations will increase the probability of repeated sales from the same customer.

Offline end users segment to register higher CAGR during forecast period

Al elevates functionality and customer experience of offline stores through the efficient layout of stores, integrated checkout processes, and order management in-store. Applications such as Amazon Go and Smart robotic services guide a customer in-store with smart checkout or help restock an item on the shelf. Such companies as Target and Carrefour are using Al to analyze customer behavior and stock management with the help of predictive analytics. Al has enhanced Point-Of-Sale (POS) systems that integrate various data points to recommend personalized in-store promotions. Supermarkets & hypermarkets such as Walmart and Carrefour use computer vision and predictive analytics to manage stock and minimize shortages. Al is also used in specialty and convenience stores to provide a better customer experience. In other offline channels, such as the department and the discount stores, Al applications comprise facial identification and customer flow analytics, which help manage foot traffic and improve store layouts for better shopping experiences.

By region, North America to Account for Largest Market Share During Forecast Period

North America holds the largest revenue share in the AI in retail market. Enterprises in this region are the early adopters of technologies. The region is experiencing rapid expansion due to several drivers, including increased awareness of AI's potential, the need for enhanced customer experiences, and productivity boosts through automation and data analytics. This region is expected to lead the AI retail sector, driven by heavy investments from tech giants and government support. The strong AI ecosystem in North America and innovation attract significant venture capital, boosting economic growth. Retailers are also forming key partnerships, such as Macy's collaboration with Rokt in August 2024, to improve customer engagement using AI solutions. Local governments, such as the US, with its "Partnership for Global Inclusivity on AI," aim to promote ethical AI practices, further accelerating AI adoption in retail. The presence of major AI vendors, such as Google, IBM, and Microsoft, is accelerating innovation in retail AI in the region.

LARGEST MARKET IN 2024- 2029
NORTH AMERICA FASTEST GROWING MARKET IN THE REGION
AI in Retail Market Size and Share

Recent Developments of AI in Retail Market

  • In October 2024, Microsoft and Rezolve AI partnered to enhance retail innovation through AI-powered commerce solutions. Rezolve's Brain Suite will be integrated with Microsoft Azure, providing retailers with advanced capabilities for digital engagement and operational efficiency.
  • In September 2024, Salesforce and Nvidia partnered to develop advanced AI capabilities, transforming customer and employee experiences. They aim to develop a new generation of AI agents and avatars that can operate autonomously, understand complex business contexts, and interact with humans more naturally and intuitively.
  • In June 2024, Bath & Body Works collaborated with Accenture to modernize, transform, and simplify its core digital and technology platforms. This multi-year program is part of Bath & Body Works’ strategy to elevate the brand and leverage the latest technologies in digital, MarTech, AI, and gen AI to drive growth.
  • In April 2024, Microsoft and Coca-Cola Company entered a five-year strategic partnership to advance Coca-Cola's technology strategy. The partnership leverages Microsoft Cloud and generative AI.

Key Market Players

List of Top AI in Retail Market Companies

The AI in Retail Market is dominated by a few major players that have a wide regional presence. The major players in the AI in Retail Market are

  • Microsoft (US)
  • IBM (US)
  • Google (US)
  • Amazon (US)
  • Oracle (US)
  • Salesforce (US)
  • NVIDIA (US)
  • SAP (Germany)
  • ServiceNow (US)
  • Accenture (Ireland)
  • Visenze (Singapore)
  • Pathr.ai (US)
  • Vue.AI (US)
  • Nextail (Spain)
  • Daisy Intelligence (Canada)
  • Cresta (US)
  • Mason (US)
  • Syte (Israel)
  • Trax (Singapore)
  • Feedzai (US)
  • Shopic (Israel).
  • Infosys (India)
  • Alibaba (China)
  • Intel (US)
  • AMD (US)
  • Fujitsu (Japan)
  • Capgemini (France)
  • TCS (India)
  • Talkdesk (US)
  • Symphony AI (US)
  • Bloomreach (US)
  • C3.AI (US)

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Scope of the Report

Report Attribute Details
Market size available for years 2019-2030
Base year considered 2023
Forecast period 2024–2030
Forecast units Value (USD) Million/Billion
Segments Covered By Offering, Type, Business Function, End-user and Region.
Regions covered North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

 

Key Questions Addressed by the Report

What is the definition of the artificial intelligenceAI in retail market?
AI in retail is the use of artificial intelligenceAI algorithms and technologies, such as computer vision, natural language processing, and machine learningNLP, and ML, in various aspects of the retail industry. Using artificial intelligenceAI helps to improve the operations’ efficiency, enhance decision-making processes, drive business growth, and improve overall customer experience. AI helps retailers understand customer behavior, optimize supply chains, and improve overall operational efficiency.
What is the size of the artificial intelligenceAI in retail market?
The artificial intelligenceAI in retail market is projected to grow from USD 316.142 billion in 2024 to USD 164.7432.52 billion by 2030, at a CAGR of 32.01.1% during the forecast period.
What are the major drivers in the artificial intelligenceAI in retail market?
Major drivers in AI in retail market are increasing adoption of conversational AI in retail for advice and recommendations, evolving consumer expectations and social commerce integration, enhancing checkout experiences with AI-powered automation, and data-driven decision decision-making.
Who are the key players operating in the artificial intelligenceAI in retail market?
The major players in the artificial intelligenceAI in retail market are Microsoft (US), IBM (US), Google (US), Amazon (US), Oracle (US), Salesforce (US), NVIDIA (US), SAP (Germany), Servicenow ServiceNow (US), Accenture (Ireland), Infosys (India), Alibaba (China), Intel (US), AMD (US), Fujitsu (Japan), Capgemini (France), TCS (India), Talkdesk (US), Symphony AI (US), Bloomreach (US), C3.AI (US), Visenze (Singapore), Pathr.ai (US), Vue.AI (US), Nextail (Spain), Daisy Intelligence (Canada), Cresta (US), Mason (US), Syte (Israel), Trax (Singapore), Feedzai (US), and Shopic (Israel). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, product launches/enhancements, and acquisitions to expand their footprint in the artificial intelligenceAI in retail market.
What are the opportunities for new entrants in the artificial intelligenceAI in retail market?
There are many opportunities for new players in AI in retail market as there is an increased need for a unique shopping experience, automation, and efficiency in retail operations. New players can focus on AI-driven customer service solutions encompassing chatbots, virtual assistants, and personalized marketing tools, which are enabled by AIAI enables to provide recommendations. Furthermore, the adoption of AI solutions in the supply chain optimization and demand forecasting spaces with smart inventory management will create growth opportunities. Retailers are also seeking AI-based visual search, smart checkout systems, and advanced fraud detection for retailers, which are growing areas where players can make investments.

 

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Table of Contents

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TITLE
PAGE NO
INTRODUCTION
34
RESEARCH METHODOLOGY
39
EXECUTIVE SUMMARY
48
PREMIUM INSIGHTS
50
MARKET OVERVIEW AND INDUSTRY TRENDS
54
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    DRIVERS
    - Increasing adoption of conversational AI in retail for advice and recommendations
    - Evolving consumer expectations and social media integration
    - Enhancing checkout experiences with AI-powered automation
    - Data-driven decision-making
    RESTRAINTS
    - High implementation costs
    - Data privacy and security
    OPPORTUNITIES
    - AI-powered customer engagement
    - Enhanced decision-making with predictive analytics
    - AI in supply chain optimization
    CHALLENGES
    - Rising theft and fraud issues
    - Complexity in integrating with legacy systems
    - Ethical concerns in AI
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.4 PRICING ANALYSIS
    AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
    INDICATIVE PRICING ANALYSIS OF ARTIFICIAL INTELLIGENCE IN RETAIL KEY PLAYERS
  • 5.5 SUPPLY CHAIN ANALYSIS
  • 5.6 ECOSYSTEM
  • 5.7 TECHNOLOGY ANALYSIS
    KEY TECHNOLOGIES
    - Conversational AI
    - Autonomous AI & autonomous agent
    - AutoML
    COMPLEMENTARY TECHNOLOGIES
    - Edge computing
    - Big data analytics
    - Cloud computing
    ADJACENT TECHNOLOGIES
    - Blockchain
    - Cybersecurity solutions
  • 5.8 PATENT ANALYSIS
    LIST OF MAJOR PATENTS
  • 5.9 TRADE ANALYSIS
    EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
    IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
  • 5.10 KEY CONFERENCES AND EVENTS, 2024–2026
  • 5.11 TARIFF AND REGULATORY LANDSCAPE
    TARIFF DATA (HSN: 854231) - PROCESSORS AND CONTROLLERS
    REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    KEY REGULATIONS
    - North America
    - Europe
    - Asia Pacific
    - Middle East & Africa
    - Latin America
    - Threat of new entrants
  • 5.12 PORTER’S FIVE FORCES’ ANALYSIS
    - Threat of substitutes
    - Bargaining power of buyers
    - Bargaining power of suppliers
    - Intensity of competitive rivalry
  • 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
    KEY STAKEHOLDERS IN BUYING PROCESS
    BUYING CRITERIA
  • 5.14 EVOLUTION OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • 5.15 CASE STUDY ANALYSIS
    TARGET LEVERAGED GOOGLE CLOUD TO ENHANCE CUSTOMER EXPERIENCES AND ACHIEVE SIGNIFICANT REVENUE GROWTH
    PRADA GROUP IMPROVED CUSTOMER EXPERIENCE USING ORACLE'S CLOUD SOLUTIONS FOR PERSONALIZED RETAIL STRATEGIES
    PEPE JEANS INDIA AUGMENTED ONLINE SHOPPING WITH SALESFORCE BY FOCUSING ON DIRECT CONSUMER ENGAGEMENT AND PERSONALIZATION
    WALMART ENHANCED DIGITAL SHOPPING WITH MICROSOFT’S GENERATIVE AI FOR PERSONALIZED SEARCH AND IMPROVED CX
    AI-POWERED CHECKOUT-FREE SHOPPING SOLUTION TRANSFORMED RETAIL OPERATIONS OF ITREX GROUP
ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING
91
  • 6.1 INTRODUCTION
    OFFERINGS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 6.2 SOLUTIONS
    PERSONALIZED PRODUCT RECOMMENDATIONS
    - AI to help tailor product suggestions based on customer behavior and drive engagement and sales in retail
    CUSTOMER RELATIONSHIP MANAGEMENT
    - AI-driven CRM to automate personalized marketing and customer segmentation and churn prevention strategies
    VISUAL SEARCH
    - Visual search to enable customers find products using images and enhance discovery and shopping experiences
    VIRTUAL CUSTOMER ASSISTANT
    - AI-powered virtual assistants to offer real-time customer support, improving response times and personalization
    PRICE OPTIMIZATION
    - AI-powered price optimization to help retailers adjust prices dynamically based on competition, demand, and market conditions
    SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING
    - AI to optimize retail supply chains by predicting demand and streamlining inventory management
    VIRTUAL STORES
    - AI to offer immersive shopping experiences with AR and VR technologies
    SMART CHECKOUT
    - AI to eliminate wait times and enable frictionless shopping experiences
    OTHER SOLUTIONS
  • 6.3 SERVICES
    PROFESSIONAL SERVICES
    - Professional services in AI for retail to help businesses effectively integrate advanced AI technologies into their operations
    - Training & consulting
    - System integration & deployment
    - Support & maintenance
    MANAGED SERVICES
    - Managed services in AI to provide continuous monitoring and management of AI systems for scalability and efficiency
ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE
110
  • 7.1 INTRODUCTION
    TYPES: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 7.2 GENERATIVE AI
  • 7.3 OTHER AI
    DISCRIMINATIVE MACHINE LEARNING
    - ML to optimize retail with personalized recommendations, dynamic pricing, and efficient demand forecasting
    NATURAL LANGUAGE PROCESSING
    - NLP to enhance customer service with AI chatbots and sentiment analysis for personalized, real-time engagement
    COMPUTER VISION
    - Computer vision to revolutionize retail with smart checkouts, visual search, and in-store analytics to boost efficiency
    PREDICTIVE ANALYTICS
    - Predictive analytics to improve demand forecasting, price optimization, and customer targeting in retail operations
ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY BUSINESS FUNCTION
116
  • 8.1 INTRODUCTION
    BUSINESS FUNCTIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 8.2 MARKETING & SALES
    AI TO IMPROVE PERSONALIZED CAMPAIGNS, PRODUCT RECOMMENDATIONS, AND DYNAMIC PRICING IN RETAIL
  • 8.3 HUMAN RESOURCES
    AI TO AUTOMATE RECRUITMENT, WORKFORCE OPTIMIZATION, AND PERSONALIZED TRAINING IN RETAIL HR
  • 8.4 FINANCE & ACCOUNTING
    AI TO SYSTEMATIZE FINANCIAL PROCESSES, SUCH AS BILLING, FORECASTING, AND FRAUD DETECTION IN RETAIL
  • 8.5 OPERATIONS
    AI TO ENHANCE SUPPLY CHAIN OPTIMIZATION, INVENTORY MANAGEMENT, AND LOGISTICS IN RETAIL OPERATIONS
  • 8.6 CYBERSECURITY
    AI TO STRENGTHEN FRAUD DETECTION, DATA SECURITY, AND BIOMETRIC AUTHENTICATION IN RETAIL CYBERSECURITY
ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY END USER
124
  • 9.1 INTRODUCTION
    END USERS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET DRIVERS
  • 9.2 ONLINE
    AI TO REVOLUTIONIZE ONLINE RETAIL BY IMPROVING SHOPPING EXPERIENCE THROUGH PERSONALIZATION, INVENTORY MANAGEMENT, AND REAL-TIME CUSTOMER SUPPORT
  • 9.3 OFFLINE
    ESSENTIAL SECURITY TOOLS TO MONITOR NETWORK TRAFFIC FOR THREATS
    SUPERMARKETS & HYPERMARKETS
    - AI to improve inventory management, customer experience, and operational efficiency with smart checkout and predictive analytics
    SPECIALTY STORES
    - AI to personalize shopping experiences and optimize inventory management in specialty stores
    CONVENIENCE STORES
    - Smart checkout, dynamic pricing, and improved inventory management to ensure operational efficiency and quick service in convenience stores
    OTHER OFFLINE STORES
    ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION
ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION
133
  • 10.1 INTRODUCTION
  • 10.2 NORTH AMERICA
    NORTH AMERICA: MACROECONOMIC OUTLOOK
    US
    - Technological advancements and strategic partnerships to propel market
    CANADA
    - Need for predicting product demand, optimizing inventory, and enhancing personalized customer experiences to drive market
  • 10.3 EUROPE
    EUROPE: MACROECONOMIC OUTLOOK
    UK
    - Need to enhance customer experiences, streamline operations, and optimize inventory management to accelerate market growth
    ITALY
    - Increasing demand for enhanced customer experiences, operational efficiency, and data-driven decision-making to fuel market growth
    GERMANY
    - Need to enhance operational efficiency, customer engagement, and government initiatives to enhance market growth
    FRANCE
    - Integration of AI to enhance customer experiences through personalized recommendations, dynamic pricing, and improved inventory management
    SPAIN
    - Strong emphasis on predictive analytics and focus on mitigating risks and enhancing decision-making investments in retail sector to boost market growth
    NORDIC COUNTRIES
    - Increasing consumer expectations for personalized experiences and operational efficiency to foster market growth
    REST OF EUROPE
  • 10.4 ASIA PACIFIC
    ASIA PACIFIC: MACROECONOMIC OUTLOOK
    CHINA
    - Strong government support for AI technology, rapid digitalization, and growing consumer demand for personalized and efficient retail experiences to fuel market growth
    JAPAN
    - Labor shortages arising due to aging population, push for operational efficiency in retail sector, and government investments and initiatives to bolster market
    INDIA
    - Rapid eCommerce growth, increasing smartphone penetration, and demand for personalized customer experiences to augment market growth
    AUSTRALIA & NEW ZEALAND
    - Increasing eCommerce activity and need for enhanced customer experience to propel market
    SOUTH KOREA
    - Advanced technological infrastructure, high internet penetration, and implementation of AI National Strategy to accelerate market
    ASEAN COUNTRIES
    REST OF ASIA PACIFIC
  • 10.5 MIDDLE EAST & AFRICA
    MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
    - UAE
    - KSA
    - Kuwait
    - Bahrain
    SOUTH AFRICA
    - Rise of AI and related technologies during COVID-19 to fuel market growth
    REST OF MIDDLE EAST & AFRICA
  • 10.6 LATIN AMERICA
    LATIN AMERICA: MACROECONOMIC OUTLOOK
    BRAZIL
    - Influx of foreign eCommerce platforms to boost demand for AI in retail market
    MEXICO
    - Embracing emerging technologies with notable funding from both domestic and international investors to bolster market growth
    ARGENTINA
    - Focus on advancing digital infrastructure to drive market
    REST OF LATIN AMERICA
COMPETITIVE LANDSCAPE
207
  • 11.1 INTRODUCTION
  • 11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
    OVERVIEW OF STRATEGIES ADOPTED BY KEY ARTIFICIAL INTELLIGENCE IN RETAIL MARKET VENDORS
  • 11.3 REVENUE ANALYSIS
  • 11.4 MARKET SHARE ANALYSIS
    MARKET RANKING ANALYSIS
  • 11.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2023
    - Company footprint
    - Type footprint
    - Offering footprint
    - Regional footprint
  • 11.6 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023
    - Key start-ups/SMEs
    - Competitive benchmarking of key start-ups/SMEs
  • 11.7 COMPETITIVE SCENARIOS AND TRENDS
    PRODUCT LAUNCHES & ENHANCEMENTS
    DEALS
  • 11.8 BRAND/PRODUCT COMPARISON
  • 11.9 COMPANY VALUATION AND FINANCIAL METRICS
COMPANY PROFILES
223
  • 12.1 KEY PLAYERS
    IBM
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    AMAZON
    - Business overview
    - Products/Solutions/Services offered
    - MnM view
    SALESFORCE, INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    ORACLE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    MICROSOFT
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    GOOGLE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    NVIDIA
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    ACCENTURE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    SAP SE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    SERVICENOW
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    INFOSYS
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    INTEL CORPORATION
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    AMD
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    HUAWEI
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    ALIBABA
    FUJITSU
    CAPGEMINI
    TCS
    TALKDESK
    SYMPHONY AI
    BLOOMREACH
    C3.AI
  • 12.2 START-UPS/SMES
    VISENZE
    PATHR.AI
    VUE.AI
    NEXTAIL
    DAISY INTELLIGENCE
    CRESTA
    MASON
    SYTE
    TRAX RETAIL
    FEEDZAI
    SHOPIC
ADJACENT/RELATED MARKETS
290
  • 13.1 INTRODUCTION
  • 13.2 ARTIFICIAL INTELLIGENCE MARKET – GLOBAL FORECAST TO 2030
    MARKET DEFINITION
    MARKET OVERVIEW
    - Artificial intelligence market, by offering
    - Artificial intelligence market, by technology
    - Artificial intelligence market, by business function
    - Artificial intelligence market, by vertical
    - Artificial intelligence market, by region
  • 13.3 RETAIL ANALYTICS MARKET – GLOBAL FORECAST TO 2029
    MARKET DEFINITION
    MARKET OVERVIEW
    - Retail analytics market, by offering
    - Retail analytics market, by business function
    - Retail analytics market, by application
    - Retail analytics market, by end user
    - Retail analytics market, by region
APPENDIX
300
  • 14.1 DISCUSSION GUIDE
  • 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
  • 14.3 CUSTOMIZATION OPTIONS
  • 14.4 RELATED REPORTS
  • 14.5 AUTHOR DETAILS
LIST OF TABLES
 
  • TABLE 1 USD EXCHANGE RATES, 2021–2023
  • TABLE 2 PRIMARY INTERVIEWS WITH EXPERTS
  • TABLE 3 RESEARCH ASSUMPTIONS
  • TABLE 4 FACTOR ANALYSIS
  • TABLE 5 AVERAGE SELLING PRICE OF ARTIFICIAL INTELLIGENCE IN RETAIL SOLUTIONS
  • TABLE 6 INDICATIVE PRICING ANALYSIS OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • TABLE 7 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: ECOSYSTEM
  • TABLE 8 MARKET: DETAILED LIST OF CONFERENCES AND EVENTS, 2024–2026
  • TABLE 9 TARIFF RELATED TO PROCESSORS AND CONTROLLERS (HSN: 854231), 2023
  • TABLE 10 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 11 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 12 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 13 REST OF THE WORLD: REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • TABLE 14 IMPACT OF EACH FORCE ON ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • TABLE 15 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE SOLUTIONS
  • TABLE 16 KEY BUYING CRITERIA FOR TOP THREE SOLUTIONS
  • TABLE 17 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 18 MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 19 MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 20 MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 21 SOLUTIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 22 SOLUTIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 23 PERSONALIZED PRODUCT RECOMMENDATIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 24 PERSONALIZED PRODUCT RECOMMENDATIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 25 CUSTOMER RELATIONSHIP MANAGEMENT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 26 CUSTOMER RELATIONSHIP MANAGEMENT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 27 VISUAL SEARCH: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 28 VISUAL SEARCH: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 29 VIRTUAL CUSTOMER ASSISTANT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 30 VIRTUAL CUSTOMER ASSISTANT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 31 PRICE OPTIMIZATION: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 32 PRICE OPTIMIZATION: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 33 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 34 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 35 VIRTUAL STORES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 36 VIRTUAL STORES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 37 SMART CHECKOUT: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 38 SMART CHECKOUT: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 39 OTHER SOLUTIONS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 40 OTHER SOLUTIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 41 MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 42 MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 43 SERVICES: ARTIFICIAL INTELLIGENCE IN RETAILMARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 44 SERVICES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 45 MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 46 MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 47 PROFESSIONAL SERVICES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 48 PROFESSIONAL SERVICES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 49 MANAGED SERVICES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 50 MANAGED SERVICES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 51 MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 52 MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 53 GENERATIVE AI: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 54 GENERATIVE AI: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 55 OTHER AI: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 56 OTHER AI: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 57 MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 58 MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 59 MARKETING & SALES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 60 MARKETING & SALES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 61 HUMAN RESOURCES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 62 HUMAN RESOURCES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 63 FINANCE & ACCOUNTING: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 64 FINANCE & ACCOUNTING: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 65 OPERATIONS: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 66 OPERATIONS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 67 CYBERSECURITY: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 68 CYBERSECURITY: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 69 MARKET, BY END USER, 2019–2023 (USD MILLION)
  • TABLE 70 MARKET, BY END USER, 2024–2030 (USD MILLION)
  • TABLE 71 ONLINE: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 72 ONLINE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 73 MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 74 MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 75 OFFLINE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 76 OFFLINE: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 77 SUPERMARKETS & HYPERMARKETS: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 78 SUPERMARKETS & HYPERMARKETS: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 79 SPECIALTY STORES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 80 SPECIALTY STORES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 81 CONVENIENCE STORES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 82 CONVENIENCE STORES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 83 OTHER OFFLINE STORES: MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 84 OTHER OFFLINE STORES: MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 85 MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 86 MARKET, BY REGION, 2024–2030 (USD MILLION)
  • TABLE 87 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 88 NORTH AMERICA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 89 NORTH AMERICA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 90 NORTH AMERICA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 91 NORTH AMERICA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 92 NORTH AMERICA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 93 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 94 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 95 NORTH AMERICA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 96 NORTH AMERICA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 97 NORTH AMERICA: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 98 NORTH AMERICA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 99 NORTH AMERICA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 100 NORTH AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 101 NORTH AMERICA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 102 NORTH AMERICA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 103 NORTH AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 104 NORTH AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 105 US: MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 106 US: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 107 US: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 108 US: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 109 US: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 110 US: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 111 US: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 112 US: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 113 US: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 114 US: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 115 US: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 116 US: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 117 US: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 118 US: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 119 US: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 120 US: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 121 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 122 EUROPE: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 123 EUROPE: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 124 EUROPE: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 125 EUROPE: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 126 EUROPE: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 127 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 128 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 129 EUROPE: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 130 EUROPE: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 131 EUROPE: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 132 EUROPE: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 133 EUROPE: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 134 EUROPE: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 135 EUROPE: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 136 EUROPE: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 137 EUROPE: MARKET, BY COUNTRY/SUBREGION, 2019–2023 (USD MILLION)
  • TABLE 138 EUROPE: MARKET, BY COUNTRY/SUBREGION, 2024–2030 (USD MILLION)
  • TABLE 139 UK: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 140 UK: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 141 UK: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 142 UK: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 143 UK: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 144 UK: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 145 UK: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 146 UK: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 147 UK: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 148 UK: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 149 UK: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 150 UK: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 151 UK: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 152 UK: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 153 UK: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 154 UK: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 155 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 156 ITALY: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 157 ITALY: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 158 ITALY: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 159 ITALY: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 160 ITALY: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 161 ITALY: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 162 ITALY: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 163 ITALY: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 164 ITALY: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 165 ITALY: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 166 ITALY: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 167 ITALY: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 168 ITALY: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 169 ITALY: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 170 ITALY: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 171 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 172 ASIA PACIFIC: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 173 ASIA PACIFIC: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 174 ASIA PACIFIC: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 175 ASIA PACIFIC: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 176 ASIA PACIFIC: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 177 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 178 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 179 ASIA PACIFIC: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 180 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 181 ASIA PACIFIC: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 182 ASIA PACIFIC: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 183 ASIA PACIFIC: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 184 ASIA PACIFIC: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 185 ASIA PACIFIC: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 186 ASIA PACIFIC: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 187 ASIA PACIFIC: MARKET, BY COUNTRY/SUBREGION, 2019–2023 (USD MILLION)
  • TABLE 188 ASIA PACIFIC: MARKET, BY COUNTRY/SUBREGION, 2024–2030 (USD MILLION)
  • TABLE 189 CHINA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 190 CHINA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 191 CHINA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 192 CHINA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 193 CHINA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 194 CHINA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 195 CHINA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 196 CHINA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 197 CHINA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 198 CHINA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 199 CHINA: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 200 CHINA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 201 CHINA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 202 CHINA: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 203 CHINA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 204 CHINA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 205 INDIA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 206 INDIA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 207 INDIA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 208 INDIA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 209 INDIA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 210 INDIA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 211 INDIA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 212 INDIA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 213 INDIA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 214 INDIA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 215 INDIA: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 216 INDIA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 217 INDIA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 218 INDIA: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 219 INDIA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 220 INDIA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 221 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 222 MIDDLE EAST & AFRICA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 223 MIDDLE EAST & AFRICA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 224 MIDDLE EAST & AFRICA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 225 MIDDLE EAST & AFRICA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 226 MIDDLE EAST & AFRICA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 227 MIDDLE EAST & AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 228 MIDDLE EAST & AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 229 MIDDLE EAST & AFRICA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 230 MIDDLE EAST & AFRICA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 231 MIDDLE EAST & AFRICA: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 232 MIDDLE EAST & AFRICA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 233 MIDDLE EAST & AFRICA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 234 MIDDLE EAST & AFRICA: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 235 MIDDLE EAST & AFRICA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 236 MIDDLE EAST & AFRICA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 237 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 238 MIDDLE EAST & AFRICA: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 239 KSA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 240 KSA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 241 KSA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 242 KSA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 243 KSA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 244 KSA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 245 KSA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 246 KSA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 247 KSA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 248 KSA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 249 KSA: AI IN RETAIL MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 250 KSA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 251 KSA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 252 KSA: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 253 KSA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 254 KSA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 255 LATIN AMERICA: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 256 LATIN AMERICA: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 257 LATIN AMERICA: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 258 LATIN AMERICA: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 259 LATIN AMERICA: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 260 LATIN AMERICA: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 261 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 262 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 263 LATIN AMERICA: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 264 LATIN AMERICA: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 265 LATIN AMERICA: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 266 LATIN AMERICA: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 267 LATIN AMERICA: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 268 LATIN AMERICA: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 269 LATIN AMERICA: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 270 LATIN AMERICA: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 271 LATIN AMERICA: MARKET, BY COUNTRY, 2019–2023 (USD MILLION)
  • TABLE 272 LATIN AMERICA: MARKET, BY COUNTRY, 2024–2030 (USD MILLION)
  • TABLE 273 BRAZIL: ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 274 BRAZIL: MARKET, BY OFFERING, 2024–2030 (USD MILLION)
  • TABLE 275 BRAZIL: MARKET, BY SOLUTION, 2019–2023 (USD MILLION)
  • TABLE 276 BRAZIL: MARKET, BY SOLUTION, 2024–2030 (USD MILLION)
  • TABLE 277 BRAZIL: MARKET, BY SERVICE, 2019–2023 (USD MILLION)
  • TABLE 278 BRAZIL: MARKET, BY SERVICE, 2024–2030 (USD MILLION)
  • TABLE 279 BRAZIL: MARKET, BY PROFESSIONAL SERVICE, 2019–2023 (USD MILLION)
  • TABLE 280 BRAZIL: MARKET, BY PROFESSIONAL SERVICE, 2024–2030 (USD MILLION)
  • TABLE 281 BRAZIL: MARKET, BY TYPE, 2019–2023 (USD MILLION)
  • TABLE 282 BRAZIL: MARKET, BY TYPE, 2024–2030 (USD MILLION)
  • TABLE 283 BRAZIL: MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 284 BRAZIL: MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD MILLION)
  • TABLE 285 BRAZIL: MARKET, BY CHANNEL TYPE, 2019–2023 (USD MILLION)
  • TABLE 286 BRAZIL: MARKET, BY CHANNEL TYPE, 2024–2030 (USD MILLION)
  • TABLE 287 BRAZIL: MARKET, BY OFFLINE, 2019–2023 (USD MILLION)
  • TABLE 288 BRAZIL: MARKET, BY OFFLINE, 2024–2030 (USD MILLION)
  • TABLE 289 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DEGREE OF COMPETITION
  • TABLE 290 MARKET: TYPE FOOTPRINT
  • TABLE 291 MARKET: OFFERING FOOTPRINT
  • TABLE 292 MARKET: REGIONAL FOOTPRINT
  • TABLE 293 MARKET: DETAILED LIST OF KEY START-UPS/SMES
  • TABLE 294 MARKET: COMPETITIVE BENCHMARKING OF KEY START-UPS/SMES
  • TABLE 295 MARKET: PRODUCT LAUNCHES & ENHANCEMENTS, JUNE 2022–OCTOBER 2024
  • TABLE 296 MARKET: DEALS, JUNE 2022–OCTOBER 2024
  • TABLE 297 IBM: COMPANY OVERVIEW
  • TABLE 298 IBM: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 299 IBM: PRODUCT ENHANCEMENTS
  • TABLE 300 IBM: DEALS
  • TABLE 301 AMAZON: COMPANY OVERVIEW
  • TABLE 302 AMAZON: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 303 AMAZON: DEALS
  • TABLE 304 AMAZON: OTHER DEALS/DEVELOPMENTS
  • TABLE 305 SALESFORCE: COMPANY OVERVIEW
  • TABLE 306 SALESFORCE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 307 SALESFORCE: PRODUCT LAUNCHES AND ENHANCEMENTS
  • TABLE 308 SALESFORCE: DEALS
  • TABLE 309 ORACLE: COMPANY OVERVIEW
  • TABLE 310 ORACLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 311 ORACLE: DEALS
  • TABLE 312 MICROSOFT: COMPANY OVERVIEW
  • TABLE 313 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 314 MICROSOFT: PRODUCT ENHANCEMENTS
  • TABLE 315 MICROSOFT: DEALS
  • TABLE 316 GOOGLE: COMPANY OVERVIEW
  • TABLE 317 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 318 GOOGLE: PRODUCT LAUNCHES
  • TABLE 319 GOOGLE: DEALS
  • TABLE 320 NVIDIA: COMPANY OVERVIEW
  • TABLE 321 NVIDIA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 322 NVIDIA: DEALS
  • TABLE 323 ACCENTURE: COMPANY OVERVIEW
  • TABLE 324 ACCENTURE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 325 ACCENTURE: DEALS
  • TABLE 326 SAP SE: COMPANY OVERVIEW
  • TABLE 327 SAP SE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 328 SAP SE: DEALS
  • TABLE 329 SERVICENOW: COMPANY OVERVIEW
  • TABLE 330 SERVICENOW: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 331 SERVICENOW: PRODUCT ENHANCEMENTS
  • TABLE 332 SERVICENOW: DEALS
  • TABLE 333 INFOSYS: COMPANY OVERVIEW
  • TABLE 334 INFOSYS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 335 INFOSYS: DEALS
  • TABLE 336 INTEL: COMPANY OVERVIEW
  • TABLE 337 INTEL: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 338 INTEL: PRODUCT LAUNCHES
  • TABLE 339 INTEL: DEALS
  • TABLE 340 AMD: COMPANY OVERVIEW
  • TABLE 341 AMD: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 342 AMD: PRODUCT ENHANCEMENTS
  • TABLE 343 AMD: DEALS
  • TABLE 344 HUAWEI: COMPANY OVERVIEW
  • TABLE 345 HUAWEI: PRODUCTS/SOLUTIONS/SERVICES OFFERED
  • TABLE 346 HUAWEI: PRODUCT LAUNCHES
  • TABLE 347 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2019–2023 (USD BILLION)
  • TABLE 348 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2024–2030 (USD BILLION)
  • TABLE 349 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2019–2023 (USD BILLION)
  • TABLE 350 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2024–2030 (USD BILLION)
  • TABLE 351 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD BILLION)
  • TABLE 352 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2024–2030 (USD BILLION)
  • TABLE 353 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2019–2023 (USD BILLION)
  • TABLE 354 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2024–2030 (USD BILLION)
  • TABLE 355 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2019–2023 (USD BILLION)
  • TABLE 356 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2024–2030 (USD BILLION)
  • TABLE 357 RETAIL ANALYTICS MARKET, BY OFFERING, 2019–2023 (USD MILLION)
  • TABLE 358 RETAIL ANALYTICS MARKET, BY OFFERING, 2024–2029 (USD MILLION)
  • TABLE 359 RETAIL ANALYTICS MARKET, BY BUSINESS FUNCTION, 2019–2023 (USD MILLION)
  • TABLE 360 RETAIL ANALYTICS MARKET, BY BUSINESS FUNCTION, 2024–2029 (USD MILLION)
  • TABLE 361 RETAIL ANALYTICS MARKET, BY APPLICATION, 2019–2023 (USD MILLION)
  • TABLE 362 RETAIL ANALYTICS MARKET, BY APPLICATION, 2024–2029 (USD MILLION)
  • TABLE 363 RETAIL ANALYTICS END-USER MARKET, BY PRODUCT TYPE, 2019–2023 (USD MILLION)
  • TABLE 364 RETAIL ANALYTICS END-USER MARKET, BY PRODUCT TYPE, 2024–2029 (USD MILLION)
  • TABLE 365 RETAIL ANALYTICS MARKET, BY REGION, 2019–2023 (USD MILLION)
  • TABLE 366 RETAIL ANALYTICS MARKET, BY REGION, 2024–2029 (USD MILLION)
LIST OF FIGURES
 
  • FIGURE 1 MARKET: RESEARCH DESIGN
  • FIGURE 2 BREAKUP OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION
  • FIGURE 3 TOP-DOWN APPROACH
  • FIGURE 4 APPROACH 1 (SUPPLY SIDE): REVENUE OF VENDORS IN ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 5 BOTTOM-UP APPROACH
  • FIGURE 6 DEMAND-SIDE ANALYSIS
  • FIGURE 7 BOTTOM-UP (SUPPLY SIDE) ANALYSIS: COLLECTIVE REVENUE FROM SOLUTIONS/SERVICES OF ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 8 DATA TRIANGULATION
  • FIGURE 9 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, 2022–2030 (USD MILLION)
  • FIGURE 10 MARKET: REGIONAL SNAPSHOT
  • FIGURE 11 GROWING DEMAND FOR ENHANCING PERSONALIZED EXPERIENCES, OPTIMIZING INVENTORY MANAGEMENT, AND DYNAMIC PRICING TO DRIVE MARKET
  • FIGURE 12 SOLUTIONS SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024
  • FIGURE 13 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 14 MARKETING & SALES SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2024
  • FIGURE 15 GENERATIVE AI SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 16 PERSONALIZED PRODUCT RECOMMENDATIONS SEGMENT TO ACCOUNT FOR LARGEST MARKET SHARE IN 2024
  • FIGURE 17 ONLINE SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE IN 2024
  • FIGURE 18 PERSONALIZED PRODUCT RECOMMENDATIONS AND PROFESSIONAL SERVICES SEGMENTS TO ACCOUNT FOR SIGNIFICANT MARKET SHARES IN 2024
  • FIGURE 19 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 20 CONSUMER LIKELIHOOD OF USING CONVERSATIONAL AI FOR ADVICE AND RECOMMENDATIONS
  • FIGURE 21 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • FIGURE 22 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOLUTION
  • FIGURE 23 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: SUPPLY CHAIN ANALYSIS
  • FIGURE 24 MARKET: ECOSYSTEM
  • FIGURE 25 LIST OF MAJOR PATENTS FOR ARTIFICIAL INTELLIGENCE IN RETAIL
  • FIGURE 26 PROCESSORS AND CONTROLLERS EXPORT, BY KEY COUNTRY, 2016–2023 (USD BILLION)
  • FIGURE 27 PROCESSORS AND CONTROLLERS IMPORT, BY KEY COUNTRY, 2016–2023 (USD BILLION)
  • FIGURE 28 PORTER’S FIVE FORCES IMPACT ON ARTIFICIAL INTELLIGENCE IN RETAIL MARKET
  • FIGURE 29 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE SOLUTIONS
  • FIGURE 30 KEY BUYING CRITERIA FOR TOP THREE SOLUTIONS
  • FIGURE 31 EVOLUTION OF ARTIFICIAL INTELLIGENCE IN RETAIL
  • FIGURE 32 SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 33 VISUAL SEARCH SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 34 MANAGED SERVICES SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 35 GENERATIVE AI SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 36 CYBERSECURITY SEGMENT TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
  • FIGURE 37 OFFLINE SEGMENT TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
  • FIGURE 38 NORTH AMERICA: MARKET SNAPSHOT
  • FIGURE 39 MIDDLE EAST & AFRICA: MARKET SNAPSHOT
  • FIGURE 40 REVENUE ANALYSIS FOR KEY COMPANIES IN PAST THREE YEARS
  • FIGURE 41 SHARE OF LEADING COMPANIES IN ARTIFICIAL INTELLIGENCE IN RETAIL MARKET, 2023
  • FIGURE 42 MARKET RANKING ANALYSIS OF TOP FIVE PLAYERS
  • FIGURE 43 ARTIFICIAL INTELLIGENCE IN RETAIL MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2023
  • FIGURE 44 MARKET: COMPANY FOOTPRINT
  • FIGURE 45 MARKET: COMPANY EVALUATION MATRIX (START-UPS/SMES), 2023
  • FIGURE 46 BRAND/PRODUCT COMPARISON
  • FIGURE 47 FINANCIAL METRICS OF KEY ARTIFICIAL INTELLIGENCE IN RETAIL MARKET VENDORS
  • FIGURE 48 COMPANY VALUATION OF KEY MARKET VENDORS
  • FIGURE 49 IBM: COMPANY SNAPSHOT
  • FIGURE 50 AMAZON: COMPANY SNAPSHOT
  • FIGURE 51 SALESFORCE: COMPANY SNAPSHOT
  • FIGURE 52 ORACLE: COMPANY SNAPSHOT
  • FIGURE 53 MICROSOFT: COMPANY SNAPSHOT
  • FIGURE 54 GOOGLE: COMPANY SNAPSHOT
  • FIGURE 55 NVIDEA: COMPANY SNAPSHOT
  • FIGURE 56 ACCENTURE: COMPANY SNAPSHOT
  • FIGURE 57 SAP SE: COMPANY SNAPSHOT
  • FIGURE 58 SERVICENOW: COMPANY SNAPSHOT
  • FIGURE 59 INFOSYS: COMPANY SNAPSHOT
  • FIGURE 60 INTEL: COMPANY SNAPSHOT
  • FIGURE 61 AMD: COMPANY SNAPSHOT

 

The research study involved four major activities in estimating the AI in retail market size. Exhaustive secondary research has been done to collect important information about the market and peer markets. The next step has been to validate these findings and assumptions and size them with the help of primary research with industry experts across the value chain. Both top-down and bottom-up approaches have been used to estimate the market size. Post which the market breakdown and data triangulation have been adopted to estimate the market sizes of segments and sub-segments.

Secondary Research

The market size of the companies offering AI in retail solutions to various end users was arrived at based on the secondary data available through paid and unpaid sources and by analyzing the product portfolios of major companies in the ecosystem and rating the companies based on their performance and quality. In the secondary research process, various sources were referred to identify and collect information for the study. The secondary sources included annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases.

Secondary research was mainly used to obtain critical information about industry insights, the market’s monetary chain, the overall pool of key players, market classification and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from both market-oriented and technology-oriented perspectives.

Primary Research

In the primary research process, various sources from the supply and demand sides were interviewed to obtain qualitative and quantitative information for the report, Such as Chief Experience Officers (CXOs), Vice Presidents (VPs), directors from business development, marketing, and product development/innovation teams, and related key executives from AI in retail solutions vendors, system integrators, professional and managed service providers, industry associations, independent consultants, and key opinion leaders.

Primary interviews were conducted to gather insights, such as market statistics, data on revenue collected from platforms and services, market breakups, market size estimations, market forecasts, and data triangulation. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Finance Officers (CFOs), Chief Strategy Officers (CSOs), and the installation team of end users who use AI in retail solutions, were interviewed to understand buyers’ perspectives on suppliers, products, service providers, and their current usage of AI in retail solutions which is expected to affect the overall AI in retail market growth.

Artificial Intelligence in Retail Market Size, and Share

Note 1: Tier 1 companies have revenues over USD 1 billion, Tier 2 companies range between USD 500 million and 1 billion in overall revenues, and Tier 3 companies have revenues less than USD 500 million.
Other designations include sales managers, marketing managers, and product managers.
Source: Industry Experts

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both top-down and bottom-up approaches were used to estimate and validate the total size of the AI in retail market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:

Artificial Intelligence in Retail Market : Top-Down and Bottom-Up Approach

Artificial Intelligence in Retail Market Top Down and Bottom Up Approach

Data Triangulation

After arriving at the overall market size from the above estimation process, the AI in retail market has been split into several segments and sub-segments. To complete the overall market engineering process and arrive at the exact statistics for all segments and sub-segments, data triangulation and market breakdown procedures have been used, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides. The AI in retail market size has been validated using top-down and bottom-up approaches.

Market Definition

AI in retail is the use of artificial intelligence algorithms and technologies, such as computer vision, natural language processing, and machine learning, in various aspects of the retail industry. Using artificial intelligence helps to improve the operations’ efficiency, enhance decision-making processes, drive business growth, and improve overall customer experience. AI helps retailers understand customer behavior, optimize supply chains, and improve overall operational efficiency.

Stakeholders

  • Artificial intelligence software developers
  • Cloud service providers
  • Consulting service providers
  • Enterprise end users
  • Distributors and Value-added Resellers (VARs)
  • Government agencies
  • Independent Software Vendors (ISV)
  • Managed service providers
  • Support & maintenance service providers
  • System Integrators (SIs)/Migration service providers
  • Technology providers

Report Objectives

  • To determine, segment, and forecast the AI in Retail market based on offering, type, business functions, end-user, and region
  • To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
  • To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the growth of the market
  • To study the complete value chain and related industry segments and perform a value chain analysis of the market landscape
  • To strategically analyze the macro and micromarkets with respect to individual growth trends, prospects, and contributions to the total market
  • To analyze the industry trends, pricing data, patents, and innovations related to the market
  • To analyze the opportunities for stakeholders by identifying the high-growth segments of the market
  • To profile the key players in the market and comprehensively analyze their market share/ranking and core competencies
  • To track and analyze competitive developments, such as mergers & acquisitions, product launches & developments, partnerships, and collaborations, in the market

Available Customizations

With the given market data, MarketsandMarkets offers customizations per the company’s specific needs. The following customization options are available for the report:

Geographic Analysis

  • Further break-up of the Asia Pacific market into countries contributing 75% to the regional market size
  • Further break-up of the North American market into countries contributing 75% to the regional market size
  • Further break-up of the Latin American market into countries contributing 75% to the regional market size
  • Further break-up of the Middle East African market into countries contributing 75% to the regional market size
  • Further break-up of the European market into countries contributing 75% to the regional market size

Company Information

  • Detailed analysis and profiling of additional market players (up to 5)

Previous Versions of this Report

Artificial Intelligence in Retail Market by Type (Online, Offline), Technology (Machine Learning and Deep Learning, NLP), Solution, Service (Professional, Managed), Deployment Mode (Cloud, On-Premises), Application, Region - Global Forecast to 2022

Report Code TC 5669
Published in Oct, 2017, By MarketsandMarkets™
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Growth opportunities and latent adjacency in Artificial Intelligence in Retail Market

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