Core Concept - The combination of AI (Artificial Intelligence) and BI (Business Intelligence) is transforming business analysis from "describing the past" to "predicting the future" [1] Group 1: AI and BI Integration - The emergence of AI assistants like Microsoft's Power BI Copilot, Tableau GPT, and Qlik's AutoML Copilot signifies the shift to "conversational analytics" in the BI sector [3] - The integration of generative AI into BI tools is an irreversible trend driven by the need to address traditional BI pain points and market demands [3][5] Group 2: Technological Breakthroughs - Generative AI enables BI to transition from being an "expert tool" to a "universal assistant," allowing users to interact using natural language instead of complex technical skills [5] - This shift democratizes data access, enabling business personnel to conduct analyses without relying on IT or data teams [6] Group 3: Business Needs and Market Dynamics - Businesses require more agile, intelligent, and widespread data-driven insights, which generative AI facilitates by providing immediate answers to queries [6] - Generative AI not only generates reports but also offers actionable insights and recommendations based on data analysis, enhancing the practical value of BI [7] Group 4: Competitive Landscape - As core BI functionalities become standardized, the differentiation among BI tools increasingly relies on their ease of use and intelligence, making AI capabilities a critical competitive factor [8] - Major BI players like Microsoft, Tableau, and Qlik are heavily investing in intelligent assistants to attract and retain users, particularly non-technical users and small to medium enterprises [8] Group 5: Microsoft Power BI Copilot - Microsoft’s Power BI Copilot is continuously evolving, enabling users to perform various tasks such as content planning, report creation, and DAX query writing efficiently [9] - Real-world applications of Power BI Copilot include generating dashboards and optimizing inventory management through natural language queries [10][12] Group 6: Future of AI and BI - The essence of AI+BI is a "human-machine collaboration revolution," where AI takes over routine data tasks, allowing analysts to focus on strategic decision-making [20] - This trend is reshaping corporate data culture, emphasizing the importance of using natural language to interact with AI assistants as a core competency for professionals [21]

Core Viewpoint - The article discusses the launch of the "Agentic AI" era at the Microsoft Build 2025 conference, highlighting significant advancements in AI applications and tools, particularly GitHub Copilot and Microsoft 365 Copilot, which are evolving into autonomous agents capable of executing complex tasks independently [1][3]. Group 1: GitHub Copilot Evolution - GitHub Copilot has transitioned from a code completion tool to an independent "intelligent programming partner" that can autonomously plan, execute, and submit pull requests for complete tasks [3]. - Developers can now assign full tasks to Copilot, which can handle everything from adding new features to fixing bugs through simple dialogue [3]. Group 2: Microsoft 365 Copilot Upgrade - Microsoft 365 Copilot received its largest upgrade, integrating five core modules: Chat, Search, Notebooks, Create, and Agents, enhancing enterprise workflows [4]. - Users can build personalized multi-agent systems via Copilot Studio and publish them to the Agent Store, reaching millions of users on Microsoft Teams and 365 platforms [4]. Group 3: AI Foundry and Infrastructure - Microsoft upgraded the Azure AI Foundry to a comprehensive AI application and agent-building factory, supporting over 1900 models and enabling low-code agent construction [10]. - The Foundry platform is utilized by institutions like Stanford University Medical Center to create multi-agent systems for automating complex medical data integration [10]. Group 4: Windows and Development Tools - Windows introduced significant updates, including Windows AI Foundry and WSL (Windows Subsystem for Linux) becoming open-source, enhancing local model operations and deployment capabilities [12][13]. - VS Code now features an Agent mode, allowing developers to configure environments and deploy applications with simple commands [13]. Group 5: Agentic Web Concept - Microsoft CTO Kevin Scott introduced the "Agentic Web" architecture, emphasizing the development of collaborative web systems that integrate intelligent agents [15]. - The new NL Web language aims to make websites and applications agent-ready, facilitating seamless integration with the MCP protocol [15]. Group 6: AI in Research and Social Impact - The Microsoft Discovery platform aims to accelerate scientific research by providing intelligent agents capable of generating hypotheses and analyzing data [19][20]. - Copilot has shown significant social impact in various sectors, including education and healthcare, with successful implementations in countries like Nigeria and Japan [21][22].