Agentic Technology: Exploring Use Cases in Diverse Sectors 
Agentic AI or Agentic technology refers to systems or tools that can make decisions and act independently to achieve specific goals. These technologies act like "Agents" that operate autonomously, using the given data to evaluate situations, plan actions, and adjust their behavior. For example, self-driving cars navigate roads, or virtual assistants schedule meetings without needing constant human input. The key feature of agentic AI is its ability to make intentional decisions and act in pursuit of objectives, often adapting to changing circumstances.
Unlike traditional automation, which relies on static programming, agentic systems are designed to:
Agents, whether in the form of software (e.g., chatbots, trading algorithms) or hardware (e.g., robots, drones), operate independently to achieve specific goals, often collaborating with other agents or humans to produce optimal results.
Generative AI, on the other hand, focuses on creating new content, such as text, images, music, or code. It uses large datasets and patterns to generate outputs based on prompts. For example, tools like ChatGPT generate conversations, while image generators like DALL·E create visual artwork. While generative AI is highly creative, it does not act independently or pursue goals—it simply produces results based on the input it receives.
The main difference is that agentic AI is action-oriented and goal-driven, while generative AI is creation-focused and responds to specific instructions. Agentic AI takes the initiative and interacts with its environment, while generative AI requires prompts and does not act autonomously beyond generating outputs. Both are powerful but serve different purposes in technology and AI applications.Download Macrosoft's whitepaper to learn the key takeaways on what the Agentic AI technology is with visionary leader G. N. Shah.
