The Global AI in Retail Market report analyzes the global market size, shares, recent trends, competitive intelligence, and future market outlook.

The AI in Retail market involves the application of artificial intelligence technologies to enhance and automate various aspects of the retail industry, from back-end operations to customer-facing experiences. These AI-driven systems analyze vast amounts of data to provide personalized recommendations, optimize inventory management, improve supply chain efficiency, and enable new experiences like cashier-less checkout and virtual shopping assistants. The market covers both online and physical stores, transforming how retailers operate and how consumers shop.

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Recent Global News 

• July 2025 (U.S.): A new report projected that the U.S. AI in retail market is being fueled by investments in hyper-personalization and intelligent supply chain management.

• August 2025 (Japan): A Japanese AI-SaaS startup raised a large funding round to automate enterprise back-office functions, with a focus on serving the retail industry.

• September 2025 (U.S. and Japan): Companies in both the U.S. and Japan are reportedly collaborating on new AI-powered visual recognition and in-store analytics to enhance the physical retail experience.

Segmentation

• By Anchor Deployment Type: Online, Offline.

• By Technology: Interactive AI, Functional AI, Analytical AI, Text-based AI, Visual AI.

• By Application: Supply Chain Logistics and Production, Sales and Marketing, Delivery Services, Payment Services, Customer Relationship Management, Security and Surveillance, Planning and Inventory.

• By End User: Supermarket, Hypermarkets, Other Sales Channels.

Leading Companies 

• AWS(Amazon)

• Google LLC

• IBM Corporation

• Intel

• Lexalytics

• Microsoft Corporation

• Nvidia

• Oracle Corporation

• SAP SE

• Visenze

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Market Trends 

• Hyper-Personalization and Predictive AI: Retailers are moving beyond basic personalization to create highly customized shopping experiences. This involves using AI to analyze a wide range of customer data, including browsing history, past purchases, and real-time behavior, to deliver tailored product recommendations, marketing messages, and even dynamic pricing.

• Generative AI and Conversational Commerce: The rise of generative AI is enabling more sophisticated chatbots and virtual assistants that can have human-like conversations. These tools are being used to guide customers through their shopping journey, answer complex product questions, and provide a new form of conversational commerce, including voice-activated shopping.

Business Opportunities:

• AI-as-a-Service (AIaaS) Platforms: There is a strong opportunity to develop and provide specialized, cloud-based AI platforms for retailers. These platforms can offer a suite of tools for demand forecasting, dynamic pricing, and customer analytics, allowing retailers to adopt AI without a large upfront investment in infrastructure.

• Visual Search and AR-Powered Experiences: Businesses can focus on creating AI-powered visual search tools that allow consumers to find products by uploading images. Additionally, there is a growing opportunity to develop augmented reality (AR) applications that let customers "try on" clothes, makeup, or place furniture in their homes virtually.

Investment Analysis

• Primary Drivers: The market is fundamentally driven by the need for retailers to stay competitive in an omnichannel world, the escalating demand for personalized customer experiences, and the imperative to increase operational efficiency and reduce costs. The rise of e-commerce and a shift in consumer expectations are also major factors.

• Geographical Trends: North America holds a dominant market share due to its early adoption of AI technologies and the presence of major retail giants. However, the Asia-Pacific region, fueled by a booming e-commerce sector and a large, digitally savvy population in countries like Japan, is expected to see the fastest growth.

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Summary

The AI in Retail market is transforming how businesses operate and engage with customers through technology. Key trends include the use of generative AI for hyper-personalization and the adoption of computer vision for frictionless in-store shopping. Opportunities are strong in providing AI-as-a-service platforms, developing specialized software for supply chain optimization, and creating solutions for loss prevention. Recent news from the U.S. and Japan shows a continued commitment to adopting these innovative technologies.

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