Core Insights - The article discusses the challenges enterprises face in integrating AI technologies due to outdated systems, emphasizing the need for a comprehensive digital transformation to leverage AI effectively [1][2] - It highlights the concept of "native integration," which is essential for AI to be embedded into core business processes, enabling seamless data flow and intelligent decision-making [4][5] Group 1: AI Integration Challenges - Enterprises are eager to adopt AI but struggle due to legacy systems that cannot support new technologies, leading to data fragmentation and inefficient processes [1][2] - A significant portion of participants in a recent course on AI integration were company leaders, indicating a top-down recognition of the need for change [1] Group 2: Native Integration Concept - "Native integration" involves a holistic approach where AI is not just an add-on but is embedded within the core business processes, ensuring data and intelligence are interconnected from the outset [4][5] - The article outlines three levels of native integration: cloud-native, data-native, and AI-native, which collectively enhance operational efficiency [4] Group 3: Use Cases and Benefits - Successful implementations of native integration have been observed in various industries, such as a short-shelf-life food company that improved supply chain coordination and a manufacturing group that enhanced operational efficiency through a smart factory setup [6][10] - The article emphasizes that native integration allows for real-time data sharing and collaboration across the entire value chain, leading to improved decision-making and operational agility [9][10] Group 4: Future Outlook - The article concludes that the native integration framework provided by companies like Yonyou will be crucial for enterprises aiming to achieve intelligent upgrades and maintain competitive advantages in the evolving digital landscape [11]