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U.S. Artificial Intelligence in Retail Market By Component (Solution, Services); By Business Function (Marketing & Sales, Human Resources, Finance & Accounting, Operations, Cybersecurity); By Technology (Machine Learning, Natural Language Processing, Chatbots, Image and Video Analytics, Swarm Intelligence); By Sales Channel (Omnichannel, Brick and Mortar) – Growth, Share, Opportunities & Competitive Analysis, 2024 – 2032

Summary
Table Of Content

REPORT ATTRIBUTE	DETAILS
Historical Period	2019-2022
Base Year	2023
Forecast Period	2024-2032
U.S. Artificial Intelligence in Retail Market Size 2023	USD 2,190.42 million
U.S. Artificial Intelligence in Retail Market, CAGR	31.33%
U.S. Artificial Intelligence in Retail Market Size 2032	USD 25,449.31 million

Market Overview

The U.S. Artificial Intelligence in Retail market is projected to grow from USD 2,190.42 million in 2023 to USD 25,449.31 million by 2032, reflecting an impressive CAGR of 31.33% during the forecast period.

The U.S. Artificial Intelligence in Retail market is driven by the growing adoption of AI-powered solutions to enhance customer experience, optimize supply chain operations, and enable personalized marketing strategies. Retailers increasingly leverage AI technologies such as machine learning, predictive analytics, and computer vision to improve inventory management, streamline logistics, and offer tailored shopping experiences. The rise of e-commerce, combined with advancements in data analytics and cloud computing, has further accelerated the integration of AI in retail operations. Additionally, the increasing demand for chatbots, virtual assistants, and AI-driven recommendation engines underscores the sector’s focus on improving customer engagement. Emerging trends such as the adoption of AI for real-time pricing, fraud detection, and autonomous checkout systems highlight the industry’s emphasis on operational efficiency and cost reduction. Overall, the growing importance of data-driven decision-making and enhanced consumer experiences continue to propel AI adoption in the U.S. retail sector.

The U.S. Artificial Intelligence in Retail market showcases significant geographical adoption across regions such as the Western, Southern, Northeastern, and Midwestern United States, each driving innovation in unique ways. The Western region leads as a hub for technological advancements, leveraging its vibrant tech ecosystem. The Southern and Northeastern regions focus on adopting AI-powered solutions for personalized customer experiences and operational efficiency. Meanwhile, the Midwest is emerging as a growing center for AI integration in retail operations. Key players in this market include Oracle Corporation, Salesforce, Microsoft Corporation, IBM Corporation, Google LLC, SAP SE, Accenture, ServiceNow, and innovative startups like Pathr.ai, Vue.AI, and Cresta. These companies are pivotal in developing cutting-edge AI-driven solutions, such as predictive analytics, virtual assistants, and smart store technologies, to enhance customer engagement and streamline operations. Their contributions underscore the dynamic evolution of AI in transforming the U.S. retail landscape.

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Market Insights

The U.S. Artificial Intelligence in Retail market was valued at USD 2,190.42 million in 2023 and is projected to reach USD 25,449.31 million by 2032, growing at a CAGR of 31.33%.
The growing demand for personalized shopping experiences is driving AI adoption in the retail sector.
AI-driven solutions, including predictive analytics and recommendation engines, are transforming retail strategies.
Major players like Oracle Corporation, Microsoft, and Google are leading the market with advanced AI technologies.
High implementation costs and complex integration processes remain significant challenges for AI adoption in retail.
The Western U.S. leads the market, with strong growth in the Southern and Northeastern regions driven by increasing AI adoption for customer engagement and operational efficiency.
AI-powered fraud detection and cybersecurity solutions are gaining traction across the retail industry for enhanced data protection and security.

Market Drivers

Growing Demand for Personalized Shopping Experiences

The increasing consumer demand for personalized shopping experiences significantly drives the adoption of artificial intelligence in the U.S. retail market. Retailers leverage AI-powered solutions, such as recommendation engines and predictive analytics, to analyze customer preferences, behavior, and purchasing history. For instance, a major U.S. retailer uses AI to analyze millions of customer interactions, enabling them to deliver tailored product recommendations and promotions. These insights enable businesses to deliver tailored product recommendations, promotions, and marketing campaigns, enhancing customer satisfaction and loyalty. As consumer expectations evolve, the role of AI in providing hyper-personalized experiences has become a critical competitive advantage for retailers.

Optimization of Supply Chain and Inventory Management

AI technologies play a pivotal role in optimizing supply chain operations and inventory management, contributing to their widespread adoption in the retail industry. Machine learning algorithms and real-time data analytics help retailers predict demand patterns, monitor stock levels, and reduce waste. For instance, a leading global retailer uses AI to forecast demand and optimize inventory, reducing stockouts and overstock situations. Furthermore, AI-powered forecasting tools assist in identifying supply chain inefficiencies and enhancing logistics processes, resulting in cost savings and improved operational efficiency. These capabilities are particularly valuable in managing disruptions and ensuring seamless product availability.

Rise of Automation in Retail Operations

The growing emphasis on automation in retail operations further propels the demand for AI-based solutions. Technologies such as autonomous checkout systems, robotic process automation (RPA), and smart shelf management streamline routine tasks, reduce labor costs, and improve efficiency. AI-driven automation also enhances customer convenience, enabling quicker and smoother in-store and online shopping experiences. As retailers seek to balance operational efficiency with superior customer service, automation powered by AI continues to gain traction across the sector.

Adoption of Advanced Analytics for Decision-Making

The increasing reliance on data-driven decision-making has fueled the integration of AI in retail operations. Advanced analytics powered by artificial intelligence enables retailers to gain actionable insights into market trends, customer behavior, and sales performance. These insights support strategic planning, pricing optimization, and targeted marketing initiatives. Moreover, the ability of AI to process large volumes of data in real time empowers retailers to make informed decisions, adapt to changing market dynamics, and maintain a competitive edge in the industry.

Market Trends

Increased Focus on Fraud Detection and Cybersecurity

The growing reliance on digital platforms in retail has heightened the importance of AI for fraud detection and cybersecurity. Retailers are deploying AI-driven systems to monitor transactions, detect anomalies, and prevent fraudulent activities. For example, AI-based fraud detection systems have significantly reduced the incidence of fraudulent transactions and improved overall security protocols. These systems leverage machine learning algorithms to identify patterns and enhance security protocols in real time. As e-commerce continues to expand, the need for robust, AI-based cybersecurity measures has become a critical aspect of safeguarding consumer trust and protecting business operations.

Surge in AI-Powered Customer Interaction Tools

The growing adoption of AI-powered customer interaction tools is a prominent trend in the U.S. Artificial Intelligence in Retail market. Chatbots, virtual assistants, and voice-enabled shopping solutions have become integral to enhancing customer engagement. These tools leverage natural language processing (NLP) to understand customer queries and provide instant, personalized responses. Retailers increasingly use AI-driven interfaces to offer seamless support across multiple touchpoints, including websites, mobile apps, and in-store kiosks. This trend underscores the industry’s focus on improving customer satisfaction and streamlining communication.

Expansion of Predictive Analytics in Retail Strategies

Predictive analytics continues to gain momentum as retailers prioritize data-driven strategies to optimize their operations. AI-powered tools enable businesses to anticipate customer preferences, forecast demand, and identify emerging market trends. These insights allow retailers to enhance product assortments, tailor marketing campaigns, and minimize inventory risks. By leveraging predictive analytics, companies can remain agile in responding to dynamic market conditions and meet evolving consumer demands effectively.

Integration of AI in Smart Store Technologies

The adoption of smart store technologies powered by AI is transforming the in-store shopping experience. Retailers are incorporating AI-based solutions such as smart shelves, automated checkout systems, and real-time inventory tracking to improve operational efficiency. Facial recognition and computer vision technologies also enable retailers to analyze customer behavior and preferences within physical stores. This trend reflects the growing emphasis on blending convenience, innovation, and personalization in brick-and-mortar retail environments.

Market Challenges Analysis

High Implementation Costs and Integration Complexities

The high costs associated with implementing AI technologies remain a significant challenge for the U.S. Artificial Intelligence in Retail market. Developing, deploying, and maintaining AI-driven solutions often require substantial investments in infrastructure, software, and skilled personnel. For instance, a survey by the National Retail Federation found that 45% of small and mid-sized retailers struggle to allocate the necessary resources to adopt these advanced technologies. Furthermore, integrating AI systems with existing retail operations and legacy platforms can be complex and time-consuming. Many businesses face difficulties in achieving seamless compatibility, which hinders the full-scale adoption of AI and delays the realization of its potential benefits.

Concerns Over Data Privacy and Ethical Use of AI

Data privacy and ethical considerations present another critical challenge in the adoption of AI in retail. AI-driven solutions rely heavily on collecting and analyzing vast amounts of customer data to generate actionable insights. However, this reliance raises concerns about data security, compliance with privacy regulations, and potential misuse of personal information. Retailers must navigate stringent regulatory frameworks, such as the California Consumer Privacy Act (CCPA) and General Data Protection Regulation (GDPR), to ensure customer data is handled responsibly. Additionally, ethical issues surrounding AI decision-making, such as algorithmic biases, further complicate adoption. Addressing these concerns is essential for building consumer trust and sustaining AI-driven innovation in the retail sector.

Market Opportunities

Expansion of AI-Driven Personalization and Customer Engagement

The increasing demand for hyper-personalized shopping experiences presents a significant growth opportunity in the U.S. Artificial Intelligence in Retail market. Retailers can harness advanced AI technologies to analyze customer behavior, preferences, and purchasing history, enabling tailored marketing strategies and product recommendations. As consumers increasingly expect personalized interactions across online and in-store channels, businesses that adopt AI-powered customer engagement tools, such as virtual assistants and recommendation engines, can gain a competitive edge. Additionally, advancements in natural language processing (NLP) and sentiment analysis open new avenues for enhancing customer service and loyalty through real-time, personalized interactions.

Growing Adoption of Autonomous and Predictive Technologies

The rising focus on operational efficiency and cost optimization creates opportunities for AI-driven autonomous and predictive solutions. Technologies such as automated checkout systems, robotic inventory management, and predictive analytics are revolutionizing retail operations by streamlining processes and reducing human error. Retailers are also leveraging AI for real-time demand forecasting, fraud detection, and supply chain optimization, allowing them to adapt swiftly to changing market dynamics. Furthermore, the integration of AI with Internet of Things (IoT) devices in smart stores offers opportunities to enhance inventory tracking, monitor shopper behavior, and create immersive retail experiences. These advancements position AI as a cornerstone for innovation and growth in the retail sector.

Market Segmentation Analysis:

By Component:

The U.S. Artificial Intelligence in Retail market is segmented by component into solutions and services. The solutions segment dominates the market as retailers increasingly adopt AI-driven tools for various applications, such as customer engagement, demand forecasting, and inventory optimization. AI-powered solutions, including chatbots, recommendation engines, and predictive analytics platforms, enable businesses to enhance customer experiences and streamline operations. On the other hand, the services segment is gaining momentum due to the growing demand for implementation, integration, and maintenance support. Service providers assist retailers in customizing AI solutions to align with specific business needs and ensure seamless integration with existing systems. The combination of robust solutions and dedicated support services is critical to maximizing the potential of AI technologies in the retail sector.

By Business Function:

Based on business function, the market is segmented into marketing & sales, human resources, finance & accounting, operations, and cybersecurity. Marketing & sales dominate this segment as AI enables retailers to deliver personalized promotions, optimize pricing strategies, and analyze customer preferences. Operations also hold a significant share, with AI being used for supply chain management, real-time inventory tracking, and automated checkout systems. Additionally, AI adoption in finance & accounting streamlines fraud detection and risk assessment processes, while human resources leverage AI for recruitment and workforce management. The growing focus on cybersecurity also drives AI adoption to monitor threats and enhance data protection, highlighting its transformative role across retail business functions.

Segments:

Based on Component:

Solution
Services

Based on Business Function:

Marketing & Sales
Human Resources
Finance & Accounting
Operations
Cybersecurity

Based on Technology:

Machine Learning
Natural Language Processing
Chatbots
Image and Video Analytics
Swarm Intelligence

Based on Sales Channel:

Omnichannel
Brick and Mortar

Based on the Geography:

Western United States
Midwestern United States
Southern United States
Northeastern United States

Regional Analysis

Western United States

The Western United States holds the largest market share in the U.S. Artificial Intelligence in Retail sector, accounting for over 35% of the total market in 2023. This dominance is primarily attributed to the region’s position as a hub for technological innovation and the presence of leading AI solution providers. States like California and Washington drive AI adoption in retail through a thriving tech ecosystem and substantial investments in R&D. Retailers in this region leverage AI-driven tools for personalized marketing, automated inventory management, and advanced customer analytics. The high concentration of e-commerce giants and startups in the West further accelerates the adoption of AI technologies, positioning the region as a trailblazer in retail transformation.

Southern United States

The Southern United States holds a significant market share, estimated at around 25% in 2023, and is experiencing rapid growth in AI adoption across retail operations. The region benefits from its expanding retail footprint and the increasing adoption of AI-powered solutions among both large-scale retailers and small businesses. States like Texas and Florida are at the forefront, driven by their diverse consumer base and growing e-commerce activities. AI applications in the South focus on enhancing customer engagement through chatbots, improving supply chain efficiency, and enabling real-time fraud detection. Additionally, the rise of smart store technologies and automation is propelling the demand for AI, making the Southern region a key contributor to the market’s overall growth.

Northeastern United States

The Northeastern United States accounts for approximately 20% of the market share, supported by a strong focus on innovation and advancements in AI-powered cybersecurity solutions. Retailers in states such as New York and Massachusetts adopt AI technologies to optimize marketing strategies, enhance consumer personalization, and strengthen data security protocols. The region is home to a highly educated workforce and prestigious research institutions, fostering the development and deployment of cutting-edge AI applications. The Northeastern market also witnesses significant investment in AI for operational efficiency, such as inventory tracking and demand forecasting, contributing to the region’s growing presence in the AI-driven retail sector.

Midwestern United States

The Midwestern United States represents around 20% of the market share, emerging as a promising region for AI adoption in retail. States like Illinois and Ohio are leading the charge, leveraging AI technologies to modernize traditional retail operations and address regional consumer needs. The Midwest focuses on implementing AI-driven solutions for supply chain optimization, personalized marketing, and automated checkout systems. Retailers in this region are also investing in predictive analytics and smart store technologies to remain competitive in the evolving market landscape. The region’s balanced growth in e-commerce and brick-and-mortar retail highlights its potential as an emerging hub for AI integration in the retail industry.

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Key Player Analysis

Oracle Corporation
Salesforce
Microsoft Corporation
IBM Corporation
Google LLC
SAP SE
Accenture
ServiceNow
Pathr.ai
Vue.AI
Cresta
Mason
Feedzai
AMD
Talkdesk
Others

Competitive Analysis

The U.S. Artificial Intelligence in Retail market is highly competitive, with several key players driving innovation and shaping market trends. Leading companies include Oracle Corporation, Salesforce, Microsoft Corporation, IBM Corporation, Google LLC, SAP SE, Accenture, ServiceNow, Pathr.ai, Vue.AI, Cresta, Mason, Feedzai, AMD, and Talkdesk. These players provide AI-driven solutions ranging from customer engagement tools and predictive analytics to smart store technologies and inventory management systems. These innovations are tailored to enhance the retail experience, streamline operations, and optimize inventory management, which are crucial for staying competitive in a rapidly evolving market. Additionally, the adoption of AI for personalized marketing and consumer insights continues to grow, with businesses looking to better understand customer behaviors and preferences to drive sales. In terms of competition, large tech companies are leveraging their robust infrastructure and expertise in cloud services, data analytics, and machine learning to dominate the market. Startups are also making significant strides by offering specialized AI solutions tailored to retail, focusing on areas such as visual search, product recommendations, and fraud detection. For instance, a study by the European Journal of Computer Science and Information Technology found that startups focusing on AI-driven visual search technologies are gaining traction among retailers. This mix of large-scale players and agile innovators creates a dynamic competitive environment, encouraging continuous advancement and improvements in AI technologies. The market is expected to see more partnerships and acquisitions as companies look to expand their AI portfolios and capabilities to meet the increasing demands of the retail industry.

Recent Developments

In January 2025, NVIDIA announced the NVIDIA AI Blueprint for retail shopping assistants, designed to transform shopping experiences both online and in stores. This blueprint helps developers create AI-powered digital assistants that can deliver personalized shopping experiences, drive higher conversion rates, and lower product return rates.
In April 2024, Oracle introduced new AI capabilities within Oracle Fusion Cloud Customer Experience (CX) to help marketers, sellers, and service agents accelerate deal cycles. These capabilities automate time-consuming tasks and enable more precise targeting, engagement, and service of buyers.
In January 2024, Microsoft unveiled new generative AI and data solutions at NRF 2024 to transform shopping experiences. These solutions span the retail shopper journey, from personalized shopping experiences to empowering store associates and unifying retail data.
In January 2024, Salesforce announced new data and AI-powered tools at NRF 2024 to transform shopping experiences. These tools, powered by the Einstein 1 Platform, include AI content creation, digital storefronts, and shopper insights to enhance customer interactions, increase loyalty, and drive revenue.
In January 2024, IBM reported at NRF 2024 that generative AI can bridge the consumer expectation gap by creating unified, integrated shopping experiences. The study showed dissatisfaction with current retail experiences and emphasized the role of AI in meeting consumer demands.

Market Concentration & Characteristics

The U.S. Artificial Intelligence in Retail market exhibits moderate to high market concentration, with a few dominant players holding substantial market shares while a growing number of emerging startups contribute innovative solutions. Large tech companies, particularly those specializing in cloud computing, data analytics, and machine learning, are the primary drivers of market growth, providing comprehensive AI platforms for retail applications such as predictive analytics, customer engagement, and inventory management. These companies leverage their strong infrastructure, financial resources, and R&D capabilities to develop AI technologies that cater to the diverse needs of the retail sector. Simultaneously, the market is characterized by the rapid emergence of specialized startups focusing on niche AI applications. These companies are innovating in areas such as visual search, personalized recommendations, and fraud detection, offering retailers advanced tools that are often more tailored to specific operational needs. The competition between large corporations and agile startups fosters continuous technological advancements, driving the overall growth of AI in the retail sector. Additionally, partnerships and collaborations between established firms and newer players are common, as both seek to enhance their AI capabilities and expand their reach. This dynamic landscape ensures that the U.S. Artificial Intelligence in Retail market remains highly competitive, with innovation and adaptation at its core.

Report Coverage

The research report offers an in-depth analysis based on Component, Business Function, Technology, Sales Channel and Geography. It details leading market players, providing an overview of their business, product offerings, investments, revenue streams, and key applications. Additionally, the report includes insights into the competitive environment, SWOT analysis, current market trends, as well as the primary drivers and constraints. Furthermore, it discusses various factors that have driven market expansion in recent years. The report also explores market dynamics, regulatory scenarios, and technological advancements that are shaping the industry. It assesses the impact of external factors and global economic changes on market growth. Lastly, it provides strategic recommendations for new entrants and established companies to navigate the complexities of the market.

Future Outlook

The U.S. Artificial Intelligence in Retail market is expected to experience substantial growth, driven by increasing demand for personalized shopping experiences.
AI-powered solutions will become more integrated into everyday retail operations, enhancing customer engagement, inventory management, and sales forecasting.
Retailers will increasingly rely on predictive analytics to better understand consumer behavior and optimize supply chain management.
The adoption of AI-driven chatbots and virtual assistants will continue to rise, improving customer service and reducing operational costs.
More retailers will implement AI for personalized recommendations and marketing campaigns, boosting customer loyalty and sales conversion rates.
The integration of AI with Internet of Things (IoT) technologies in smart stores will provide real-time data insights to improve customer experiences.
AI’s role in fraud detection and cybersecurity will expand, helping retailers better protect sensitive customer data and mitigate risks.
As competition intensifies, both established players and startups will focus on developing more specialized AI solutions tailored to niche retail needs.
Retailers will invest in AI-based tools to optimize pricing strategies, enhance product assortment, and improve decision-making processes.
Future advancements in AI will likely lead to more autonomous retail environments, reducing the need for human intervention in day-to-day operations.

CHAPTER NO. 1 : INTRODUCTION 18

1.1.1. Report Description 18

Purpose of the Report 18

USP & Key Offerings 18

1.1.2. Key Benefits for Stakeholders 19

1.1.3. Target Audience 19

1.1.4. Report Scope 19

CHAPTER NO. 2 : EXECUTIVE SUMMARY 20

2.1. U.S. Artificial Intelligence in Retail Market Snapshot 20

2.1.1. U.S. Artificial Intelligence in Retail Market, 2018 – 2032 (USD Million) 21

CHAPTER NO. 3 : GEOPOLITICAL CRISIS IMPACT ANALYSIS 22

3.1. Russia-Ukraine and Israel-Palestine War Impacts 22

CHAPTER NO. 4 : U.S. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET – INDUSTRY ANALYSIS 23

4.1. Introduction 23

4.2. Market Drivers 24

4.2.1. Driving Factor 1 Analysis 24

4.2.2. Driving Factor 2 Analysis 25

4.3. Market Restraints 26

4.3.1. Restraining Factor Analysis 26

4.4. Market Opportunities 27

4.4.1. Market Opportunity Analysis 27

4.5. Porter’s Five Forces Analysis 28

4.6. Value Chain Analysis 29

4.7. Buying Criteria 30

CHAPTER NO. 5 : ANALYSIS COMPETITIVE LANDSCAPE 31

5.1. Company Market Share Analysis – 2023 31

5.1.1. U.S. Artificial Intelligence in Retail Market: Company Market Share, by Revenue, 2023 31

5.1.2. U.S. Artificial Intelligence in Retail Market: Top 6 Company Market Share, by Revenue, 2023 31

5.1.3. U.S. Artificial Intelligence in Retail Market: Top 3 Company Market Share, by Revenue, 2023 32

5.2. U.S. Artificial Intelligence in Retail Market Company Revenue Market Share, 2023 33

5.3. Company Assessment Metrics, 2023 34

5.3.1. Stars 34

5.3.2. Emerging Leaders 34

5.3.3. Pervasive Players 34

5.3.4. Participants 34

5.4. Start-ups /SMEs Assessment Metrics, 2023 34

5.4.1. Progressive Companies 34

5.4.2. Responsive Companies 34

5.4.3. Dynamic Companies 34

5.4.4. Starting Blocks 34

5.5. Strategic Developments 35

5.5.1. Acquisitions & Mergers 35

New Product Launch 35

U.S. Expansion 35

5.6. Key Players Product Matrix 36

CHAPTER NO. 6 : PESTEL & ADJACENT MARKET ANALYSIS 37

6.1. PESTEL 37

6.1.1. Political Factors 37

6.1.2. Economic Factors 37

6.1.3. Social Factors 37

6.1.4. Technological Factors 37

6.1.5. Environmental Factors 37

6.1.6. Legal Factors 37

6.2. Adjacent Market Analysis 37

CHAPTER NO. 7 : U.S. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET – BY COMPONENT SEGMENT ANALYSIS 38

7.1. U.S. Artificial Intelligence in Retail Market Overview, by Component Segment 38

7.1.1. U.S. Artificial Intelligence in Retail Market Revenue Share, By Component, 2023 & 2032 39

7.1.2. U.S. Artificial Intelligence in Retail Market Attractiveness Analysis, By Component 40

7.1.3. Incremental Revenue Growth Opportunity, by Component, 2024 – 2032 40

7.1.4. U.S. Artificial Intelligence in Retail Market Revenue, By Component, 2018, 2023, 2027 & 2032 41

7.2. Solution 42

7.3. Services 43

CHAPTER NO. 8 : U.S. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET – BY BUSINESS FUNCTION SEGMENT ANALYSIS 44

8.1. U.S. Artificial Intelligence in Retail Market Overview, by Business Function Segment 44

8.1.1. U.S. Artificial Intelligence in Retail Market Revenue Share, By Business Function, 2023 & 2032 45

8.1.2. U.S. Artificial Intelligence in Retail Market Attractiveness Analysis, By Business Function 46

8.1.3. Incremental Revenue Growth Opportunity, by Business Function, 2024 – 2032 46

8.1.4. U.S. Artificial Intelligence in Retail Market Revenue, By Business Function, 2018, 2023, 2027 & 2032 47

8.2. Marketing & Sales 48

8.3. Human Resources 49

8.5. Finance & Accounting 50

8.6. Operations 51

8.8. Cybersecurity 52

CHAPTER NO. 9 : U.S. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET – BY TECHNOLOGY SEGMENT ANALYSIS 53

9.1. U.S. Artificial Intelligence in Retail Market Overview, by Technology Segment 53

9.1.1. U.S. Artificial Intelligence in Retail Market Revenue Share, By Technology, 2023 & 2032 54

9.1.2. U.S. Artificial Intelligence in Retail Market Attractiveness Analysis, By Technology 55

9.1.3. Incremental Revenue Growth Opportunity, by Technology, 2024 – 2032 55

9.1.4. U.S. Artificial Intelligence in Retail Market Revenue, By Technology, 2018, 2023, 2027 & 2032 56

9.2. Machine Learning Machine Learning 57

9.3. Natural Language Processing 58

9.4. Chatbots 59

9.5. Image and Video Analytics 60

9.6. Swarm Intelligence 61

CHAPTER NO. 10 : U.S. ARTIFICIAL INTELLIGENCE IN RETAIL MARKET – BY SALES CHANNEL SEGMENT ANALYSIS 62

10.1. U.S. Artificial Intelligence in Retail Market Overview, by Sales Channel Segment 62

10.1.1. U.S. Artificial Intelligence in Retail Market Revenue Share, By Sales Channel, 2023 & 2032 63

10.1.2. U.S. Artificial Intelligence in Retail Market Attractiveness Analysis, By Sales Channel 64

10.1.3. Incremental Revenue Growth Opportunity, by Sales Channel, 2024 – 2032 64

10.1.4. U.S. Artificial Intelligence in Retail Market Revenue, By Sales Channel, 2018, 2023, 2027 & 2032 65

10.2. Omnichannel 66

10.3. Brick and Mortar 67

10.4. Pure-play Online Retailers 68

CHAPTER NO. 13 : COMPANY PROFILES 73

13.1. Oracle Corporation 73

13.1.1. Company Overview 73

13.1.2. Product Portfolio 73

13.1.3. Swot Analysis 73

13.1.4. Business Strategy 74

13.1.5. Financial Overview 74

13.2. Salesforce 75

13.3. Microsoft Corporation 75

13.4. IBM Corporation 75

13.5. Google LLC 75

13.6. SAP SE 75

13.7. Accenture 75

13.8. ServiceNow 75

13.9. Pathr.ai 75

13.10. Vue.AI 75

13.11. Cresta 75

13.12. Mason 75

13.13. Feedzai 75

13.14. AMD 75

13.15. Talkdesk 75

13.16. Others 7

List of Figures

FIG NO. 1. U.S. Artificial Intelligence in Retail Market Revenue, 2018 – 2032 (USD Million) 22

FIG NO. 2. Porter’s Five Forces Analysis for U.S. ARTIFICIAL INTELLIGENCE IN RETAIL Market 29

FIG NO. 3. Value Chain Analysis for U.S. Artificial Intelligence in Retail Market 30

FIG NO. 4. Company Share Analysis, 2023 32

FIG NO. 5. Company Share Analysis, 2023 32

FIG NO. 6. Company Share Analysis, 2023 33

FIG NO. 7. Artificial Intelligence in Retail Market – Company Revenue Market Share, 2023 34

FIG NO. 8. U.S. Artificial Intelligence in Retail Market Revenue Share, By Component, 2023 & 2032 40

FIG NO. 9. Market Attractiveness Analysis, By Component 41

FIG NO. 10. Incremental Revenue Growth Opportunity by Component, 2024 – 2032 41

FIG NO. 11. U.S. Artificial Intelligence in Retail Market Revenue, By Component, 2018, 2023, 2027 & 2032 42

FIG NO. 12. U.S. Artificial Intelligence in Retail Market for Solution, Revenue (USD Million) 2018 – 2032 43

FIG NO. 13. U.S. Artificial Intelligence in Retail Market for Services, Revenue (USD Million) 2018 – 2032 44

FIG NO. 14. U.S. Artificial Intelligence in Retail Market Revenue Share, By Business Function, 2023 & 2032 46

FIG NO. 15. Market Attractiveness Analysis, By Business Function 47

FIG NO. 16. Incremental Revenue Growth Opportunity by Business Function, 2024 – 2032 47

FIG NO. 17. U.S. Artificial Intelligence in Retail Market Revenue, By Business Function, 2018, 2023, 2027 & 2032 48

FIG NO. 18. U.S. Artificial Intelligence in Retail Market for Marketing & Sales, Revenue (USD Million) 2018 – 2032 49

FIG NO. 19. U.S. Artificial Intelligence in Retail Market for Human Resources, Revenue (USD Million) 2018 – 2032 50

FIG NO. 20. U.S. Artificial Intelligence in Retail Market for Finance & Accounting, Revenue (USD Million) 2018 – 2032 51

FIG NO. 21. U.S. Artificial Intelligence in Retail Market for Operations, Revenue (USD Million) 2018 – 2032 52

FIG NO. 22. U.S. Artificial Intelligence in Retail Market for Cybersecurity, Revenue (USD Million) 2018 – 2032 53

FIG NO. 23. U.S. Artificial Intelligence in Retail Market Revenue Share, By Technology, 2023 & 2032 55

FIG NO. 24. Market Attractiveness Analysis, By Technology 56

FIG NO. 25. Incremental Revenue Growth Opportunity by Technology, 2024 – 2032 56

FIG NO. 26. U.S. Artificial Intelligence in Retail Market Revenue, By Technology, 2018, 2023, 2027 & 2032 57

FIG NO. 27. U.S. Artificial Intelligence in Retail Market for Machine Learning, Revenue (USD Million) 2018 – 2032 58

FIG NO. 28. U.S. Artificial Intelligence in Retail Market for Natural Language Processing, Revenue (USD Million) 2018 – 2032 59

FIG NO. 29. U.S. Artificial Intelligence in Retail Market for Chatbots, Revenue (USD Million) 2018 – 2032 60

FIG NO. 30. U.S. Artificial Intelligence in Retail Market for Image and Video Analytics, Revenue (USD Million) 2018 – 2032 61

FIG NO. 31. U.S. Artificial Intelligence in Retail Market for Swarm Intelligence, Revenue (USD Million) 2018 – 2032 62

FIG NO. 32. U.S. Artificial Intelligence in Retail Market Revenue Share, By Sales Channel, 2023 & 2032 64

FIG NO. 33. Market Attractiveness Analysis, By Sales Channel 65

FIG NO. 34. Incremental Revenue Growth Opportunity by Sales Channel, 2024 – 2032 65

FIG NO. 35. U.S. Artificial Intelligence in Retail Market Revenue, By Sales Channel, 2018, 2023, 2027 & 2032 66

FIG NO. 36. U.S. Artificial Intelligence in Retail Market for Omnichannel, Revenue (USD Million) 2018 – 2032 67

FIG NO. 37. U.S. Artificial Intelligence in Retail Market for Brick and Mortar, Revenue (USD Million) 2018 – 2032 68

FIG NO. 38. U.S. Artificial Intelligence in Retail Market for Pure-play Online Retailers, Revenue (USD Million) 2018 – 2032 69

Frequently Asked Questions

What is the current size of the U.S. Artificial Intelligence in Retail market?

The U.S. Artificial Intelligence in Retail market was valued at USD 2,190.42 million in 2023 and is projected to reach USD 25,449.31 million by 2032, growing at an impressive CAGR of 31.33% during the forecast period.

What factors are driving the growth of the U.S. Artificial Intelligence in Retail market?

The market’s growth is driven by the increasing adoption of AI-powered solutions to enhance customer experience, optimize supply chain operations, and enable personalized marketing strategies. Key factors include the rise of e-commerce, advancements in data analytics and cloud computing, and the growing demand for chatbots, virtual assistants, and AI-driven recommendation engines.

What are the key segments within the U.S. Artificial Intelligence in Retail market?

The market is segmented by component (solutions and services), business function (marketing & sales, human resources, finance & accounting, operations, and cybersecurity), technology (machine learning, natural language processing, chatbots, image and video analytics, and swarm intelligence), and sales channel (omnichannel and brick and mortar). Regionally, the market includes the Western, Southern, Northeastern, and Midwestern United States.

What are some challenges faced by the U.S. Artificial Intelligence in Retail market?

Challenges include high implementation costs, complex integration processes, concerns over data privacy, and ethical issues such as algorithmic bias. Many retailers face difficulties in integrating AI systems with existing platforms and navigating stringent data privacy regulations like the California Consumer Privacy Act (CCPA).

Who are the major players in the U.S. Artificial Intelligence in Retail market?

Key players include Oracle Corporation, Salesforce, Microsoft Corporation, IBM Corporation, Google LLC, SAP SE, Accenture, ServiceNow, Pathr.ai, Vue.AI, and Cresta, among others. These companies provide advanced AI-driven solutions such as predictive analytics, virtual assistants, and smart store technologies to enhance customer engagement and streamline retail operations.

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