Core Viewpoint - The emergence of Agentic AI is seen as a revolutionary shift in how AI interacts with humans, moving from simple question-answering to executing tasks autonomously, which is expected to significantly enhance productivity and innovation across various industries [1][4]. Factors Behind the Emergence of Agentic AI - The rapid advancement of large model capabilities over the past two years has led to AI systems that can think similarly to the human brain [3]. - The introduction of Model Context Protocol (MCP) allows AI agents to interact with their environment in a standardized manner, facilitating easier data access and tool usage [3]. - The cost of reasoning has decreased by approximately 280 times in the last two years, making the large-scale deployment of Agentic AI feasible [3]. - The availability of powerful SDKs, such as Strands Agents, simplifies the development of sophisticated Agentic AI systems, enabling companies to create multi-agent applications with minimal coding [3]. - Previous investments in digitalization have prepared many companies with ready-to-use data and APIs, making the emergence of Agentic AI almost inevitable [3]. Innovation in Products and Business Models - The Agentic AI era is expected to drive significant innovation in products and services, allowing companies to enhance customer experiences and transform business models for substantial value returns [4]. - Examples of innovative business models include the sharing economy created by Uber and Airbnb, and the subscription model pioneered by Netflix [5]. - Startups like Cursor and Perplexity are integrating AI into their offerings, revolutionizing programming and information retrieval respectively [5]. Key Technical Preparations for Companies - Companies need to establish a unified AI-ready infrastructure to maximize the value of Agentic AI [7]. - Aggregated and governed AI-ready data is crucial, as it represents a strategic asset that can differentiate companies in the AI landscape [8]. - Companies must ensure data quality and accessibility to enable effective use of Agentic AI "digital employees" [8][9]. - A clear strategy and efficient execution are essential for realizing the value of Agentic AI, with a focus on long-term impacts rather than short-term expectations [10]. Conclusion - The transition to Agentic AI requires companies to adapt their infrastructure, data governance, and strategic planning to fully leverage the potential of AI in enhancing operational efficiency and driving innovation [7][10].