Agentic AI
A category of AI systems that autonomously decompose goals, use tools, and run multi-step tasks
What is Agentic AI?
Agentic AI is a category of AI systems that decompose a goal on their own, use tools, observe the results, and decide the next action — without a human directing every step. If a single "AI agent" is one unit, agentic AI is the broader term for the whole paradigm built around that autonomous behavior.
Unlike a standard chatbot that only answers questions, agentic AI takes a high-level objective like "research competitors and write a summary report," breaks it into subtasks, and actually executes them.
How Does It Work?
Agentic AI typically uses an LLM as its reasoning engine and runs a repeating loop: decompose the goal, call tools (search, code execution, APIs), observe the result, and decide the next action. Unlike plain generative AI, it does not stop after one response — if an intermediate result is wrong, it retries.
Why Does It Matter?
Agentic AI is the dominant theme in the AI industry for 2025–2026, with OpenAI, Anthropic, and Google all concentrating on it. Gartner forecasts that by 2028, 33% of enterprise software will include agentic AI. Adoption is moving faster than proof of value, however — only a minority of companies can yet show a bottom-line return — so designing measurement before adoption is increasingly emphasized.
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