Allianz Investment stated in a document that in the competitive home decoration industry, large American companies are using artificial intelligence to gain a competitive advantage. Participants in the home decoration industry are actively integrating artificial intelligence into their business operations. Allianz Investment's research shows that major DIY retailers are investing heavily in artificial intelligence projects to improve customer experience and back-end operations. The investment cycle for artificial intelligence in the retail industry is just beginning. According to McKinsey's research, generative artificial intelligence could create an additional $400 billion in value for the retail and consumer goods industry, and "major" home improvement retailers are already starting to use this new technology in innovative ways. Do-it-yourself (DIY) is a vast and growing global industry. In the United States alone, the total value of the home decoration industry is as high as $545 billion, growing at a compound annual growth rate of 6% over the past decade. In the current environment, large brands are striving to improve customer experience and manage costs through new technologies, especially artificial intelligence, in order to expand market share. Allianz Investment believes that there are compelling reasons for businesses to invest heavily in artificial intelligence. McKinsey estimates that generative artificial intelligence could bring an additional $400 billion in value to the retail and consumer goods industry, with marketing being the most easily achievable. Considering this, Allianz Investment's research team studied the artificial intelligence projects being undertaken by two major home improvement retailers in the United States, whose combined market share approaches 40%: Retailer A has approximately 1,700 stores in the United States. Retailer B has approximately 2,400 stores in North America. AI-driven websites and specialized applications Retailer A's website and applications use AI-driven recommendation engines to suggest products based on browsing history and past purchase records, helping customers quickly find what they need. The company believes that AI can help change how customers view their brand from a store selling products to a partner helping solve problems for customers. This approach also helps retailer A follow up with customers, reminding them of maintenance and replacement times, with the aim of transforming the retailer-customer relationship from a single transaction to a long-term one. Digital twins Retailer A uses a 3D simulation software platform from a large chip manufacturer to replicate a virtual store, a concept known in the tech world as "digital twins". AI simulates the customer journey in the store to optimize product layout and train salespeople to create a smoother shopping experience. Inventory management AI can also help improve inventory management in these large stores. Many of these stores have large and heavy inventory, making transportation and storage complex and costly, which is where AI can come in to optimize supply chains and inventory. Retailer B has developed a proprietary technology solution for its employees, combining mobile devices and specialized applications. Employees take photos in the store, and the application uses machine vision and AI to identify shelves that need restocking and quickly locate specific products, reducing friction with customers during shopping and improving inventory management in the store. Retailer A takes it a step further, testing a robot that patrols the store using AI and 3D maps to identify inventory differences and ensure accurate inventory data without any manual input. This robot is currently being tested in 11 stores in the San Francisco Bay Area. Retailer A also uses AI algorithms to analyze sales data and market trends to predict demand for specific items in the future, helping optimize inventory levels and avoid shortages. TD Cowen estimates that this technology (along with saved labor costs) could help increase gross margins by 20-60 basis points and reduce the proportion of sales, general, and administrative expenses as a percentage of revenue by 30-90 basis points.