AI Glossary
What it means, why it matters to your business, and where it shows up in a real build decision.
In plain terms
Agentic AI describes systems that operate with a degree of autonomy, deciding the next step themselves instead of following a fixed script. It is the current frontier and the current hype magnet. The practical version is narrow and well-supervised, not a fully autonomous employee.
Traditional AI answers the question you asked. Agentic AI decides which question to ask next, takes the steps to answer it, and adjusts its plan when it hits an obstacle.
A research team uses an agentic system to perform competitive analysis. It searches the web, retrieves documents, synthesizes findings, and produces a report, each step informed by what the previous step found.
For complex, multi-step tasks where the exact sequence of steps cannot be fully predicted in advance. Research, analysis, and multi-system processes are good starting points.
Where predictability matters more than flexibility. Agentic systems are harder to audit, more likely to go off-rails, and more expensive than deterministic pipelines for well-defined tasks.
Related reading
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