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In the digital wave of globalization, artificial intelligence (AI) technology, with its powerful data processing, analysis and prediction capabilities, is gradually becoming a key force in promoting the transformation and upgrading of various industries. As a field closely linked to consumers' daily lives, the retail industry has also ushered in unprecedented changes driven by AI. Alibaba uses AI technology to optimize the product recommendation system of its e-commerce platform and improve inventory management efficiency through big data analysis; Walmart deploys generative AI and launches voice shopping functions to improve user experience; Starbucks uses AI algorithms to accurately predict customers' purchasing habits and preferences, thereby optimizing product recommendations and inventory management. These retail giants have invested heavily in AI applications in order to gain an advantage in the fierce market competition.

Based on this, this article will deeply explore the practical application of AI technology in retail scenarios, analyze its specific impact and potential opportunities on retail business, and provide valuable reference information for related companies and investors.

1. Overview of the development of “AI+Retail”

“AI+Retail”It refers to the application of artificial intelligence (AI) technology to all aspects of the retail industry to enhance the intelligence level of retail business, improve operational efficiency, optimize customer experience, and promote innovation and transformation in the retail industry. This concept covers many aspects from product recommendation, customer service, inventory management, logistics distribution to marketing, and aims to achieve automation, personalization and intelligence of retail business processes through the application of AI technology.

Development drivers: Technological progress, changes in consumer demand, and the need for digital transformation in the retail industry are jointly driving the rapid development of “AI+retail”

Advances in AI technology, especially the development of generative AI, have brought new development opportunities to the retail industry.At the algorithmic level, generative AI uses more advanced deep learning techniques, such as RNN, LSTM, and Transformer, to enable the model to more deeply understand the intrinsic structure and relationship of the data, improve the accuracy of the model, and enhance its generalization ability, making it more handy when handling complex tasks. In terms of computing power, advances in hardware technology, especially the popularity of GPUs and TPUs, have greatly improved the training and reasoning speed of generative AI, shortened the development cycle, and improved the efficiency of AI applications. In addition, through large-scale data training, generative AI can more accurately capture data features, generate more realistic and natural content, and provide the retail industry with recommendations that are closer to consumer needs. Therefore, the advancement of AI technology has not only optimized the functions and performance of generative AI, but also created a new marketing and service model for the retail industry, and promoted the innovative development of the industry.

Generational changes in consumers, increased demand for personalized services and instant gratification, the retail industry must adapt to these changes to remain competitive. With the changing times, consumer groups are also experiencing generational changes. Young consumers, especially Generation Z and Millennials, are gradually becoming the main consumers. They grew up in the digital age, their adaptability and acceptance of technology are much higher than their predecessors, and they have higher expectations for personalized services and instant gratification. They crave customized product recommendations, personalized marketing information, and flexible and convenient payment and delivery methods. McKinsey data shows that more than half of "Generation Z" consumers prefer personalized brands that can tell unique stories. QuestMobile data shows that the average monthly usage time of "Generation Z" users for mobile Internet is nearly 160 hours, and the average daily usage time is 7.2 hours. They are deeply dependent on this and have high expectations for convenient payment and instant delivery. To meet the needs of the new generation of consumers, the retail industry must innovate and improve the service experience, and constantly adapt and adjust in the competition to win the lasting trust of consumers.

The retail industry has entered an era of stock competition, and AI retail has become a new code for corporate growth.The retail industry has entered an era of stock competition, the market environment is becoming increasingly complex, and traditional growth methods can no longer adapt to the new competitive situation. Against this background, AI retail has opened a new door to growth for enterprises and has become a new password for enterprise growth. The in-depth application of AI technology enables retail companies to capture consumer needs with unprecedented accuracy, accurately portray user portraits through big data analysis, and provide consumers with tailored personalized services. This consumer-centric service model not only improves consumers' shopping experience, but also invisibly enhances the brand's appeal and consumer loyalty. At the same time, AI technology also plays a role in precision marketing, optimizing inventory, and improving supply chain efficiency, helping companies reduce operating costs and enhance market competitiveness. AI retail not only brings new growth points to retail companies, but also injects new vitality into the entire retail industry.

Development status: user-centric, omni-channel integration, data-driven, creating a new smart retail ecosystem

Currently, AI is reshaping the retail industry. The traditional linear value chain centered on "goods" is transforming into a closed-loop value chain centered on "users". With the help of AI technology, retail companies can gain in-depth insights into consumer needs through real-time, scenario-based user journey interactions, and then achieve omni-channel integration online and offline based on accurate data, and infiltrate and apply AI to all links of the retail industry chain to create an intelligent ecosystem. In this process, large retail companies and platforms are becoming the core of the industry ecosystem with their high-quality data resources and assets, and are driving the overall upgrade and digital growth of corresponding categories and industries.

Figure: AI reshapes the major paradigm shifts in the retail industry

Figure: Current status of China’s “AI+retail” development

2. Analysis of the “AI+Retail” Industry Ecosystem“AI+Retail” Industry Ecosystem Map

The "AI+retail" industry ecosystem mainly includes three levels: the foundation and technology level, the application development and service level, and the user level. These three levels are closely connected through data flow, technology integration, and service interaction, forming a complete ecosystem and promoting the continuous development and innovation of the "AI+retail" industry.

Illustration: "AI+Retail" Industry Map

Basic and technical layer: the foundation of the "AI+retail" ecosystem

The basic and technical layer is the foundation of the entire "AI+retail" ecosystem, providing the core driving force and technical support for the digital transformation of the retail industry. This layer covers multiple key links such as hardware suppliers, AI chip manufacturers, cloud computing service providers, and AI algorithm and technology developers, which together constitute the infrastructure for the application of AI technology in the retail field.Hardware VendorsProvide the retail industry with necessary hardware equipment such as sensors, cameras, smart shelves, etc. These hardware are the basis for data collection and AI applications.AI chip makersIt provides powerful computing power for image recognition, voice processing, and other retail applications, enabling complex data processing and machine learning algorithms to run efficiently.Cloud computing service providersIt mainly provides data storage, processing and analysis services, and is the key to the scale and efficient operation of AI applications. It enables retail companies to process and analyze large amounts of data and support complex AI model training and deployment.AI algorithm and technology developersIt is the key force driving the continuous innovation of AI technology. The algorithms it develops, such as machine learning, deep learning, and natural language processing, are the key to promoting retail intelligence. With the development of AI big models, AI algorithm and technology developers are also constantly exploring new applications of big models in the retail field, such as personalized product recommendations through generative AI and optimization of supply chain management through reinforcement learning. With the continuous advancement of technology, AI big models are expected to play a greater role in the retail industry and promote the "AI+retail" industry ecosystem to develop in a smarter and more efficient direction.

Application development and service layer: the key bridge connecting basic technology and end users

In the "AI+Retail" industry ecosystem, the application development and service layer plays a vital role. It is the key bridge between basic technology and end users. This layer mainly involves core areas such as supply chain management, marketing and user operations. By deeply integrating AI technology with retail business processes, it promotes the intelligent transformation of the retail industry.In terms of supply chain management,AI technology is applied to warehousing and commodity logistics management. Through accurate demand forecasting, inventory optimization and intelligent scheduling, it can significantly improve the efficiency and responsiveness of the supply chain. At the same time, logistics planning and applications can also use AI algorithms to optimize delivery routes, reduce transportation costs, increase delivery speed, and ensure that consumers can receive goods quickly.In terms of marketing,AI-assisted marketing helps retail companies achieve precision marketing and improve the conversion rate of advertising by analyzing consumer data; unmanned retail uses computer vision and machine learning technologies to create a shopping experience that does not require human intervention, reducing operating costs and improving customer convenience; AI commercial photography uses automated image recognition and editing technology to quickly generate product display images, thereby improving the production efficiency of marketing content.In terms of user operations,The intelligent customer service system provides 24/7 instant customer service through natural language processing and machine learning technologies to solve customer problems and improve the service experience; user operations rely on AI's analysis of user behavior to achieve personalized recommendations and refined operations, and enhance customer loyalty; digital human technology has brought new ways of interaction to the retail industry, communicating naturally with customers through virtual assistants and providing consultation and purchasing advice.

User layer: Demanders and ultimate beneficiaries of AI retail applications

The user layer mainly includes two categories: enterprises and consumers. Their needs and feedback have an important impact on the development and application of AI retail. Enterprises are the main demanders of AI retail technology and services. Enterprises in different segments such as e-commerce, department stores, and supermarkets have unique market demands and operating models, which prompts AI retail solution providers to continuously customize and optimize services to meet the diverse needs of enterprises. Consumer needs and preferences are one of the core driving forces for the development of the retail market. By analyzing and predicting consumer behavior, AI technology can help companies meet customer needs more accurately and improve consumers' shopping experience and satisfaction. At the same time, the continuous improvement of consumers' acceptance of AI retail will further feed back the popularization and development of AI retail.

3. Analysis of the main application segments of “AI+retail”

"AI+retail" has many subdivided application fields. Based on multiple factors such as market size, maturity of AI technology application, and changes in consumer demand, we have selected five key subdivided fields, including e-commerce (including fresh food e-commerce), department stores, supermarkets, beauty, and food and beverages, for in-depth analysis. During the analysis, we will discuss multiple dimensions, including the specific application of AI technology, the impact on consumer experience, the improvement of industry operating efficiency, and future development trends, in order to fully demonstrate the actual application results and development prospects of "AI+retail" in various subdivided fields.

E-commerce (including fresh food e-commerce): AI helps with accurate recommendations and intelligent customer service to optimize the shopping experience

In the field of e-commerce, the application of AI has fully penetrated into multiple core links such as product recommendation, customer service, and supply chain management, significantly improving the shopping experience and operational efficiency. Through the intelligent recommendation system, e-commerce platforms can accurately analyze consumers' purchasing behavior and preferences and provide them with personalized product recommendations, thereby effectively improving conversion rates and user satisfaction. The introduction of intelligent customer service uses advanced natural language processing technology to answer consumer questions online 24 hours a day and provide personalized suggestions, greatly optimizing the user's shopping experience. In terms of supply chain management, AI can accurately predict demand changes, optimize inventory levels and replenishment strategies through comprehensive analysis of multi-source data such as historical sales data, market trends, and logistics conditions, effectively reduce inventory backlogs and out-of-stock risks, and improve the overall efficiency of the supply chain. At present, major mainstream e-commerce platforms (including fresh food e-commerce) have widely used AI technology. For example, Jing Xiaozhi, an intelligent shopping guide robot launched by JD.com, is based on natural language processing technology and can answer user questions online 24 hours a day, provide personalized product recommendations, and significantly improve customer service efficiency and user satisfaction. Taobao uses AI algorithms to deeply analyze user shopping behaviors and preferences, provide personalized product recommendations, help users quickly find their favorite products, and improve purchase conversion rates. Douyin e-commerce has innovatively launched a smart live broadcast function, which generates personalized product trays and speech solutions for influencers, effectively lowering the threshold for new anchors and one-person teams to sell goods through live broadcasts. In the field of fresh food e-commerce, Hema Fresh provides convenient services such as smart recommendations and self-service checkout through online and offline integration and AI technology, bringing consumers a new shopping experience. In the future, AI retail in the e-commerce field will deeply integrate consumer data to generate more accurate and personalized recommendations and services. At the same time, automated warehouse operations and virtual reality experiences will also be widely used, bringing higher sales, lower operating costs and stronger market competitiveness to the e-commerce industry.

Department stores: AI enables precision marketing and virtual experience to improve consumer satisfaction

The department store industry is actively exploring the application of AI retail, and continuously improving consumer experience and operational efficiency through precision marketing, smart shopping guides and other means. With the help of AI technology, department stores can deeply analyze consumer behavior and preferences, realize accurate product recommendations and promotions, and effectively improve marketing effectiveness. At the same time, the introduction of smart shopping guides, using AR/VR technology to provide consumers with innovative experiences such as virtual fitting and makeup, can also assist consumers in making more informed purchasing decisions. Take Intime Department Store as an example. The company is at the forefront of the industry in the application of AI retail. Intime Commercial released its self-developed natural language counter assistant "Chat@Taolue GPT". This innovative tool not only helps brand counters to select products, replenish stocks, place orders, divert traffic, and manage communities in daily operations, but also added a "shopping guide employment" scenario this year, further improving the service efficiency and professional level of shopping guides. In the future, AI applications in the department store industry will pay more attention to the integration of online and offline channels to achieve omni-channel marketing and services. At the same time, personalized shopping experience and intelligent store management will also become important development directions. These innovative measures will jointly drive business growth and transformation and upgrading in the department store industry, and bring consumers a more convenient, efficient and personalized shopping experience.

Supermarkets: AI leads self-service checkout and smart product selection, reshaping the new retail ecosystem of supermarkets

In the supermarket sector, the application of AI retail has become an important driving force for the transformation and upgrading of the industry. With the help of intelligent settlement systems, combined with technologies such as facial recognition and RFID, customers can enjoy the convenience of fast self-service settlement, which greatly improves the shopping experience. At the same time, supermarkets also use AI technology for intelligent product selection and display. Through in-depth analysis of sales data, they intelligently recommend hot-selling products and optimize the display layout of products, thereby improving sales efficiency. For example, Wumart and Duodian DMALL jointly launched the "AI Smart Shopping Guide" service. Based on AI technology, this service can provide personalized product recommendations and shopping suggestions based on consumer shopping habits and needs. Walmart has demonstrated a diversified strategy in the application of AI retail. On the one hand, through the pilot application of AI and computer vision technology, it can eliminate the queue phenomenon in the store exit area; on the other hand, it is also actively exploring drone delivery services to ensure that goods can be delivered to customers in a shorter time. In addition, Walmart has also created a new search experience supported by GenAI, which can generate relevant cross-category results and provide customers with more accurate and personalized shopping suggestions. In the future, the supermarket sector will pay more attention to the development of in-depth data analysis and unmanned retail. By using AI to deeply mine massive amounts of data, supermarkets will be able to more accurately grasp market demand and consumer behavior. At the same time, the promotion of unmanned retail models will also bring new growth points to supermarkets.

Beauty and cosmetics: AI empowers virtual makeup trials and smart services to drive innovation and development in the beauty and cosmetics industry

In the beauty industry, the integration of AI retail is driving the industry towards a new stage of development. With the help of the virtual makeup trial system, consumers can experience different makeup effects before purchasing and easily find the most suitable products for themselves. At the same time, the application of AI technology also covers areas such as personalized recommendations and intelligent customer service, bringing consumers more intimate and efficient services. Take L'Oréal as an example. This global beauty giant actively embraces AI technology, acquires Modi Face, an augmented reality and artificial intelligence technology company, and launches Modi Face App. This App is connected to multiple brands under the L'Oréal Group, allowing consumers to enjoy a number of AI intelligent services such as makeup trial and skin diagnosis online. These innovative applications not only enhance consumers' willingness to buy and satisfaction, but also promote the innovation and development of beauty products. In the future, AI applications in the beauty industry will pay more attention to the development of customized products and intelligent skin care solutions. By combining AI and 3D printing technology, beauty brands can launch customized beauty products to meet the personalized needs of consumers. At the same time, intelligent skin care solutions will also provide dynamic skin care suggestions and solutions based on changes in consumers' skin quality.

Food and Beverage: AI drives personalized services and new product development, leading the transformation and upgrading of the industry

In the food and beverage industry, the application of AI retail also has broad prospects. Through intelligent supply chain management, food and beverage companies can predict market demand, optimize production plans and logistics distribution, thereby ensuring the freshness and quality of products. At the same time, AI is also used in personalized customization and intelligent marketing to provide consumers with more diversified products and services. For example, Haidilao has developed an intelligent service system using AI technology, which can predict satisfaction by identifying customers' facial expressions and adjust service strategies based on this prediction to further meet consumer needs. This innovative application not only enhances customers' dining experience, but also strengthens the interaction and connection between Haidilao and customers. Nestlé has achieved intelligent management of production processes by introducing AI technology, thereby improving production efficiency and quality. At the same time, Nestlé also uses AI technology to analyze consumer behavior to provide more accurate product recommendations and personalized services. PepsiCo is also actively using AI technology to track consumer demand and accelerate the development of new products. Through AI analysis, PepsiCo can grasp market trends more accurately and develop products that better meet consumer tastes and health needs. In the future, AI applications in the food and beverage industry will pay more attention to the research and development of healthy foods and the development of environmentally friendly packaging. By combining AI technology, food and beverage companies can accelerate the research and development and innovation of healthy foods to meet consumers' demand for healthy diets. At the same time, the application of environmentally friendly packaging will also reduce material waste and environmental pollution, and promote the sustainable development of the industry.

4. Outlook on development trendsTrend 1: Driven by AI, the seamless integration and personalized experience of the retail industry will be further deepened

AI technology is driving the retail industry towards a more seamless integration and personalized experience. The future retail industry will no longer be limited to traditional online or offline channels, but will achieve seamless integration of online and offline channels through the in-depth application of AI technology. Consumers will be able to enjoy one-stop, all-round shopping services at any time, any place, and through any device. In addition, AI technology will gain a deeper understanding of consumers' shopping habits, preferences, and needs through deep learning and data analysis, thereby providing them with more accurate and personalized product recommendations and service experiences. This deeply personalized service will not only improve consumer satisfaction and loyalty, but will also bring more sales opportunities and profits to retailers.

Trend 2: AI will further optimize resource allocation, reduce waste, and drive sustainable development of the retail industry

The application of AI technology in the retail industry will not only optimize resource allocation, but also promote the sustainable development of the retail industry. Through intelligent supply chain management, inventory management and logistics distribution, AI systems can accurately predict changes in demand, optimize inventory levels and replenishment strategies, and reduce inventory backlogs and out-of-stock risks. At the same time, automated warehouse operations and logistics distribution will improve operational efficiency and accuracy, and further reduce operating costs. In addition, AI technology will also help the retail industry reduce waste and promote sustainable development. Through intelligent product selection and display, AI systems can accurately predict commodity demand, avoid overproduction and inventory backlogs, and reduce resource waste and environmental pollution. At the same time, sustainable development measures such as green packaging and environmentally friendly logistics will also be further promoted and implemented, providing strong support for the sustainable development of the retail industry.

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