Artificial Intelligence in Retail Market

Artificial Intelligence in Retail Market Size and Share:

The global artificial intelligence in retail market size was valued at USD 14.16 Billion in 2024. Looking forward, IMARC Group estimates the market to reach USD 76.44 Billion by 2033, exhibiting a CAGR of 18.70% from 2025-2033. North America currently dominates the market, holding a market share of over 35.6% in 2024. The growth of the North American region is driven by advanced technology infrastructure, high AI adoption rates, and the presence of leading tech companies fostering retail innovation.

Shoppers are expecting tailored experiences, prompting retailers to adopt artificial intelligence (AI) technologies like recommendation engines, dynamic pricing, and personalized marketing to enhance user engagement and loyalty. Furthermore, the rise of online shopping is accelerating the need for AI to improve digital experiences, such as personalized product recommendations, chatbots for individual support, and streamlined online transactions. Additionally, AI helps retailers optimize supply chains, automate inventory management, predict demand, and enhance operational workflows, leading to cost savings and better resource utilization. Besides this, retailers are adopting AI to deliver seamless omnichannel experiences, integrating physical and digital touchpoints. AI helps synchronize inventory management, pricing strategies, and personalized marketing across all client engagement channels.

The United States plays a crucial role in the market, driven by the presence of leading tech companies, which are driving innovations in AI solutions for retail. These advancements enable retailers to adopt cutting-edge AI technologies such as machine learning (ML), natural language processing (NLP), and computer vision to enhance client experiences and optimize operations. Moreover, the increasing availability of AI-powered tools designed specifically for small and medium-sized enterprises (SMEs) to enhance their marketing efforts, reduce operational costs, and improve user engagement is bolstering the market growth. In 2024, Alibaba International launched Pic Copilot, an AI-powered e-commerce design tool tailored for SMEs in the USA. The tool includes 12 functions, like background changing for images and virtual fitting, to assist SMEs in enhancing product visuals and increasing sales effectiveness. Pic Copilot leverages AI and sales data to improve marketing effectiveness, helping merchants save time and resources.

Artificial Intelligence in Retail Market Trends:

Personalized User Experience and Recommendations

Retailers are using AI-powered algorithms to analyze individual behavior, preferences, and past interactions to deliver personalized product recommendations and tailored shopping experiences. This not only improves client satisfaction but also increases sales and brand loyalty. AI tools such as ML and NLP allow retailers to predict what clients are likely to purchase next, offer discounts or promotions at the right time, and even provide personalized user service through chatbots. By understanding individual needs and providing relevant recommendations, retailers can engage people more effectively, making their shopping experience seamless and customized. This shift towards personalization is a key driver in the AI retail sector, as individuals expect tailored experiences and brands strive to meet these evolving expectations to stay competitive in the market. In 2024, Salesforce introduced a new generation of its AI-driven Commerce Cloud, integrating B2B and B2C sales, order management, and payments into one platform. The upgraded system utilizes AI-powered "Agentforce" agents to tailor interactions, improve user connections, and streamline sales processes. This cohesive strategy seeks to enhance client experiences, boost loyalty, and create new revenue possibilities for companies.

Automation of Routine Tasks and Operational Efficiency

AI is driving significant operational improvements in the retail industry by automating routine tasks, allowing businesses to reduce costs and improve efficiency. AI-driven solutions like robotic process automation (RPA), chatbots, and virtual assistants help streamline client service, process transactions, and handle administrative duties.  This frees up staff to focus on more complex tasks, enhancing overall productivity. Moreover, AI-driven technologies improve in-store operations by automating tasks such as inventory tracking, visual merchandising, and checkout processes. The efficiency gained from these automation solutions allows retailers to better allocate resources, minimize human error, and improve both employee and user experiences. In 2024, UST introduced its 'UST Retail GenAI platform' at the London Innovation Lab, aimed at revolutionizing retail operations with generative AI. The platform incorporates essential AI functionalities such as search, summarization, automation, and creation to enhance retail operations, allowing retailers to experiment with and apply AI-powered solutions. Its goal is to speed up innovation, refine decision-making, and boost operational efficiency within the retail sector.

Enhanced Inventory and Supply Chain Management

AI plays a crucial role in optimizing inventory and supply chain management within the retail sector. Predictive analytics, powered by AI, helps retailers forecast demand more accurately, reducing both overstocking and stockouts. AI algorithms evaluate past sales figures, seasonal patterns, and current market circumstances to develop accurate inventory control tactics. By using AI for demand forecasting and optimizing the replenishment process, retailers can lower operational costs, streamline logistics, and reduce waste. Furthermore, AI improves supply chain efficiency by enabling smarter route planning for delivery and predicting potential disruptions, thus enhancing overall operational efficiency. In 2024, ChannelEngine announced an integration with SAP Order Management Services (OMS) to enhance AI-driven marketplace management across 950+ global sales channels. This collaboration streamlines inventory synchronization, order management, and AI-powered automation, helping businesses expand efficiently across multiple platforms. The integration supports businesses in optimizing their supply chain and financial processes, boosting eCommerce growth.

Artificial Intelligence in Retail Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global artificial intelligence in retail market, along with forecast at the global, regional, and country levels from 2025-2033. The market has been categorized based on component, technology, type, and application.

Analysis by Component:

• Solution
• Service

Solution stand as the largest component in 2024, holding 62% of the market share. The solution segment leads the market attributed to the growing demand for comprehensive AI tools and platforms that address specific retail needs. These solutions, including ML algorithms, customer relationship management (CRM) systems, and inventory management software, empower retailers to enhance operational efficiency and deliver personalized client experiences. AI-based solutions provide deep insights from individual data, enabling retailers to optimize marketing campaigns, improve product recommendations, and predict purchasing behavior. Additionally, these solutions help streamline the supply chain by forecasting demand and managing stock levels. The integration of AI-driven solutions into various aspects of retail operations allows businesses to remain competitive, reduce costs, and improve overall performance. As retailers increasingly rely on advanced technologies to drive business growth, the demand for robust, scalable AI solutions continues to rise, positioning this segment as the dominant segment in the market.

Analysis by Technology:

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

Machine learning (ML) holds the biggest market share due to its ability to analyze vast amounts of data and derive actionable insights that drive decision-making. Retailers are leveraging ML algorithms to personalize user experiences, predict demand, and optimize supply chains. ML models can identify patterns in individual behavior, allowing retailers to offer tailored product recommendations, promotions, and content. Additionally, ML helps retailers forecast trends and inventory needs with remarkable accuracy, reducing the risk of overstocking or stockouts. The technology is also essential for pricing optimization, adjusting prices in real-time based on factors such as demand, competition, and client preferences. Furthermore, ML is used in fraud detection systems, helping retailers identify suspicious activities and protect transactions. By continuously learning from new data, ML offers a scalable solution that enhances operational efficiency, drives individual satisfaction, and supports innovation across various retail sectors.

Analysis by Type:

• Online Retail
• Offline Retail

The online retail segment holds a significant share in the market, primarily driven by the increasing demand for enhanced client experiences in e-commerce. AI technologies are heavily integrated into online retail platforms to personalize shopping experiences, recommend products, and optimize search functions. AI also helps in streamlining logistics, managing inventory, and analyzing individual behavior, providing businesses with insights to tailor marketing strategies. Moreover, online retailers use AI for pricing optimization, fraud detection, and chatbots for client support, which contribute to improving the overall user journey and boosting sales.

The offline retail segment also experiences considerable use of AI technologies, though its applications frequently focus on improving in-store experiences and operational efficiencies. AI is employed in offline retail for activities like in-store navigation, managing inventory, and engaging clients via virtual assistants or intelligent displays. Retailers utilize AI-driven analytics to forecast demand patterns and enhance product positioning within brick-and-mortar stores. Moreover, AI technologies, such as facial recognition and instant user feedback tools, enhance the shopping experience and elevate service quality. As brick-and-mortar stores adopt AI to rival online competitors, the incorporation of these technologies is becoming more essential to boost customer visits and enhance sales in physical locations.

Analysis by Application:

• Customer Relationship Management (CRM)
• Supply Chain and Logistics
• Inventory Management
• Product Optimization
• In-Store Navigation
• Payment and Pricing Analytics
• Virtual Assistant
• Others

Customer relationship management (CRM)represents the largest segment, accounting 27.6% of market share in 2024. CRM dominates market because of the increasing need for personalized user experiences and improved individual engagement. AI-powered CRM systems enable retailers to collect and analyze vast amounts of user data, helping them understand buying patterns, preferences, and behaviors. This data-driven insight allows retailers to create targeted marketing strategies, personalized offers, and tailored product recommendations, enhancing client loyalty and satisfaction. Additionally, AI enhances individual interactions through automated communication channels, such as chatbots and virtual assistants, which can resolve queries and provide real-time assistance. By predicting client needs and behaviors, AI-driven CRM systems help retailers improve their sales and user retention rates. These technologies also enable retailers to measure individual sentiment, monitor feedback, and optimize the overall user journey, positioning CRM as a critical tool in driving business growth and delivering exceptional shopping experiences in the competitive retail landscape.

Regional Analysis:

• North America
  • United States
  • Canada
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Others
• Latin America
  • Brazil
  • Mexico
  • Others
• Middle East
• Africa

In 2024, North America accounted for the largest artificial intelligence in retail market share of 35.6%. North America is the largest segment, driven by a strong technology infrastructure and a high rate of AI adoption across retail businesses. The region's robust e-commerce growth also accelerates the demand for AI, as retailers seek to differentiate themselves through tailored shopping experiences and enhanced client service. In addition, North American retailers are investing in AI to improve user experiences, streamline supply chains, and enhance personalization. AI-powered tools such as chatbots, predictive analytics, and inventory management systems are extensively used to drive efficiency and individual satisfaction. The region also benefits from the presence of major tech companies and startups focused on AI solutions, which enables the development and integration of cutting-edge technologies in the retail sector. In 2024, NVIDIA announced partnerships with major US technology leaders, including AT&T, Lowe’s, and the University of Florida, to use NVIDIA's NeMo and NIM microservices for developing custom generative AI applications. These innovations aim to enhance industries such as retail, telecommunications, and healthcare by creating tailored AI agents and improving operational efficiency. NVIDIA’s microservices and Agent Blueprints help organizations rapidly deploy AI solutions to boost productivity and innovation across various sectors.

Key Regional Takeaways:

United States Artificial Intelligence in Retail Market Analysis

The United States holds a significant position in the market due to its robust technological infrastructure and rapid adoption of AI by retail businesses. Leading tech companies and startups in the US are continuously innovating and developing cutting-edge AI solutions that enhance client experiences, optimize supply chains, and drive personalization. Furthermore, the integration of AI technologies into mobile apps and in-store experiences is enhancing user convenience and engagement. By leveraging vast product datasets and ML, retailers can offer real-time access to product information, competitive prices, and reviews, creating a seamless, personalized shopping experience for individuals. This trend is encouraging wider adoption of AI solutions, as it improves client satisfaction and supports more informed purchasing decisions. In 2024, Google enhanced its AI features with an update for Google Lens, enabling US users to obtain product details, price comparisons, and reviews by just taking a picture while shopping. This function, backed by Google's extensive product database, enriches the in-store shopping experience, particularly in the beauty, toys, and electronics domains. It is accessible to US users who choose to share their location via the Google app on both Android and iOS.

Europe Artificial Intelligence in Retail Market Analysis

Europe is an essential part of the market, noted for its emphasis on innovation and sustainable methods. Retailers in the region are progressively embracing AI to improve their operations, boost personalization, and simplify supply chains. The regulatory framework in the region promotes responsible AI development, enhancing trust between individuals and businesses. Solutions powered by AI are increasingly utilized to boost user engagement, enhance shopping experiences, and facilitate data-driven decision-making. Moreover, the heightened emphasis on enhancing operational efficiency and security via AI-driven solutions is supporting the market growth in the area. Retailers are utilizing sophisticated AI solutions, including video monitoring for theft deterrence and AI-based communication tools, to improve security and employee efficiency. These advancements not only enhance store functions but also promote a better user experience by providing a safer and more effective shopping atmosphere. In 2024, x-hoppers announced its soft launch in France at Tech for Retail 2024, introducing an AI-powered retail communication platform aimed at reducing theft and improving workforce efficiency. The platform integrates AI Video Alert (AIVA) for theft prevention, employee training tools, and smart communication systems to enhance the client experience.

Asia Pacific Artificial Intelligence in Retail Market Analysis

Asia Pacific is experiencing rapid growth in market, supported by an expanding digital ecosystem and increasing investments in AI technologies. Countries like China, Japan, and India are becoming major hubs for AI innovation in retail, with AI helping retailers improve personalization, inventory management, and client service. The region's high mobile penetration and the growing shift toward e-commerce also contribute to the rising demand for AI-powered solutions in the retail sector. Furthermore, the emergence of innovative AI solutions that make it easier for businesses to integrate and customize AI tools is bolstering the market growth in the region. Startups and tech companies in the region are developing platforms that provide ready-to-deploy AI agents and tools, enabling businesses to enhance productivity and streamline operations. For instance, a Bengaluru-based startup KOGO launched an AI agent store designed for enterprises in 2024, offering advanced tools and plugins for businesses to integrate AI into their operations. The platform offers pre-built AI agents and tools for sectors such as retail, healthcare, and finance, enabling businesses and developers to develop, tailor, and commercialize AI agents. This project seeks to boost growth and improve productivity by facilitating easy AI adoption and smooth integration.

Latin America Artificial Intelligence in Retail Market Analysis

Latin America is steadily growing as a significant market, with businesses increasingly embracing digital transformation to enhance client experiences. The rising popularity of e-commerce, along with the growing need for data analytics, personalized recommendations, and efficient inventory management, is driving the demand for advanced solutions. Retailers in the region are utilizing technology to optimize pricing strategies, predict consumer behavior, and offer improved user service. In 2024, Walmart Mexico enhanced its retail media capabilities by integrating its demand-side platform (DSP) with Infillion’s data management and flexible supply chain technology, allowing for improved operations, cookie-free data application, and enhanced targeting via Walmart’s first-party audience.

Middle East and Africa Artificial Intelligence in Retail Market Analysis

The Middle East and Africa are emerging as key regions for technology adoption in retail, driven by a focus on digitalization and innovation. Retailers in the region are enhancing operational efficiency, personalizing shopping experiences, and optimizing supply chains. The growing e-commerce market, alongside the increasing interest in smart retail technologies, is driving the demand for advanced solutions. In 2024, SAP Emarsys launched its Product Finder tool in the UAE, designed to improve product recommendations and personalize client experiences. The tool responds to rising user expectations, with 91% of UAE shoppers stating that personalized recommendations enhance their retail experiences. This initiative supports the region’s broader push towards integrating advanced technologies in retail.

Competitive Landscape:

Major players in the market are concentrating on creating cutting-edge AI-powered solutions to improve user experiences and optimize operations. They are making substantial investments in research activities to develop tailored retail experiences using ML, predictive analytics, and automation technologies. These firms are likewise enhancing their AI abilities in domains such as inventory control, supply chain improvement, and pricing tactics. Additionally, strategic alliances and purchases are being sought to incorporate new AI technologies and broaden market access. Companies are providing scalable, cloud-driven AI solutions to meet the needs of businesses of different sizes, facilitating wider acceptance of AI technologies. Moreover, numerous organizations are concentrating on enhancing client interaction via virtual assistants, chatbots, and various client service advancements, with the goal of delivering smooth, effective, and data-informed solutions. In 2024, Central Food Retail Group partnered with Google Cloud to introduce Thailand's inaugural AI-driven shopping assistant, the "Tops Chef Bot," at Tops Food Hall. This smart assistant leverages generative AI to provide tailored shopping, meal planning, and product suggestions through the LINE app. The service combines Google Cloud's data analytics and AI features, with the goal of improving user experience and simplifying shopping for those with busy lifestyles.

The report provides a comprehensive analysis of the competitive landscape in the artificial intelligence in retail market with detailed profiles of all major companies, including:

• Accenture plc
• Capgemini SE
• Cognizant Technology Solutions Corporation
• Google LLC
• Intel Corporation
• International Business Machines Corporation
• NVIDIA Corporation
• Oracle Corporation
• Salesforce, Inc
• SAP SE

Latest News and Developments:

• January 2025: Tredence launched its GenAI Suite for the Retail and CPG sectors at NRF 2025. The suite utilizes generative AI and Agentic AI to optimize supply chains, marketing, and customer experiences.
• August 2024: Amazon launched Rufus, its generative AI-powered shopping assistant chatbot, in India. The tool helps Indian shoppers with product recommendations, shopping advice, comparisons, and gift ideas, making it easier to understand their needs and discover products. Rufus is available in beta to select customers on the Amazon.in mobile app.
• September 2024: Salesforce announced its AI Use Case Library, featuring over 100 tailored AI capabilities for 15 industries, including retail, healthcare, and life sciences. These sector-specific AI solutions aim to address complex challenges, with features like inventory checks for consumer goods businesses. The capabilities will be generally available in October 2024 and February 2025, enhancing Salesforce's industry clouds with targeted, generative AI-driven tools.
• May 2024: IBM and SAP revealed an enhanced partnership through the "Value Generation" initiative, concentrating on generative AI and tailored cloud solutions for various industries. The collaboration seeks to enhance business workflows and promote innovation in areas such as retail, manufacturing, and consumer packaged goods. Utilizing AI technologies, such as IBM's Watson AI, the initiative will assist clients in speeding up their transition to next-generation enterprises.
• April 2024: SAP Emarsys introduced its AI Product Finder, a generative AI solution aimed at improving e-commerce marketing through the automation of product recommendations and the creation of campaign content. This tool helps marketers quickly process large product catalogs and generate targeted campaign ideas, improving efficiency and relevancy.

Artificial Intelligence in Retail Market Report Scope:

Key Benefits for Stakeholders:

• IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the artificial intelligence in retail market from 2019-2033.
• The research study provides the latest information on the market drivers, challenges, and opportunities in the global artificial intelligence in retail market.
• The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
• Porter's Five Forces analysis assists stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the artificial intelligence in retail industry and its attractiveness.
• Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.