What is Agentic AI?

About Agentic AI:

• Agentic AI is an advanced form of artificial intelligence focused on autonomous decision-making and action.
• It consists of AI agents—machine learning models that mimic human decision-making to solve problems in real time.
• Unlike traditional AI, which primarily responds to commands or analyzes data, agentic AI can set goals, plan, and execute tasks with minimal human intervention.
• "Agentic" indicates agency — the ability of these systems to act independently, but in a goal-driven manner.
• At its core, this technology is built on several key components:
  • Perception: Agentic AI starts by gathering information from its surroundings and different sources, such as sensors, databases, and user interfaces.
  • Reasoning: Using a large language model (LLM), agentic AI analyzes the gathered data to understand the context, identify relevant information, and formulate potential solutions.
  • Planning: The AI then uses the information it gathered to develop a plan. This involves setting goals, breaking them down into smaller steps, and figuring out the best way to achieve them.
  • Action: Based on its plan, the AI takes action. This could involve performing tasks, making decisions, or interacting with other systems.
  • Reflection: After taking action, the AI learns from the results. It evaluates whether its actions were successful and uses this feedback to adjust its plans and actions in the future.
• Agentic AI builds on generative AI (GenAI) techniques by using large language models (LLMs) to function in dynamic environments.
• While generative models focus on creating content based on learned patterns, agentic AI extends this capability by applying generative outputs toward specific goals.
• For example, a generative AI model like OpenAI’s ChatGPT might produce text, images, or code, but an agentic AI system can use that generated content to complete complex tasks autonomously by calling external tools.