Agents & automation
It is the current frontier and the current hype magnet. The practical version is narrow and well-supervised, not a fully autonomous employee.
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.
Agentic AI is the ability to chase a goal across steps. You give an outcome, such as reconcile these three reports. The system decides which step comes next, instead of following a script you wrote line by line.
That flexibility is the point and the problem. A fixed checklist is easier to predict. An agentic system can handle a messy task and can also wander, retry, or spend money on steps you did not expect. Use it when the path varies. Use a fixed sequence when the path is known and a missed step is expensive.
Think of it this way: 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.
A finance analyst asks an agentic system to explain why last month's shipping cost jumped. It pulls the invoice file, the volume report, and the rate card, then writes the comparison. A person checks the conclusion before it goes to the leadership meeting. The gathering of the files was the slow part, and that is what the system did.
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. A system that chooses its own next step is harder to check, more likely to wander, and more expensive than a fixed sequence for a job you already understand.
RaftLabs builds agents that do one defined job, with a person still on the steps that cannot be undone. You see the workflow on your own data before it runs on its own. The related work on our side is AI agent development.
This sits with the other agents & automation terms on the glossary. When software stops only answering and starts carrying out the work. Worth reading next: AI Agent, Multi-agent System, and Orchestration. For the full walkthrough, read What is agentic AI? The full guide.
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