“Agentic AI” has become the label vendors slap on anything they want to sound sophisticated. The term has been diluted to the point where it often means nothing more than “our chatbot got an upgrade.”
Genuinely agentic systems can make decisions and take actions toward goals without being explicitly prompted for each step. A traditional AI tool waits for your input and responds. An agentic system can perceive a situation, decide what to do, and act with some degree of autonomy.
Most products marketed as “agentic” don’t meet that bar.
The Red Flags
It never initiates without prompting. If the system only does things when you explicitly ask, it’s reactive, not agentic. A truly agentic system might notice you haven’t completed a task, gather the information you need, and propose next steps without being told to.
It has no memory across interactions. If every conversation starts fresh, with no context from previous sessions, the system can’t learn or adapt. It’s responding to the current prompt, not working toward longer-term goals.
It can’t interact with external systems. An agent needs to take actions in the world: calling APIs, updating records, triggering workflows. If all it does is generate text in a chat window, it’s a conversational interface, not an agent.
Its behavior only changes through new code. Agentic systems adapt based on feedback and changing conditions. If the only way to change how the system behaves is to have developers update the code, you’re looking at traditional automation with better marketing.
The Simple Test
Ask the vendor: “What will this system do when I’m not using it?”
If the answer is “nothing,” it’s not agentic in any meaningful sense. It may be a useful AI tool, but calling it “agentic” is a stretch.
Genuinely agentic systems can be given an objective and will work toward it: breaking down tasks, using tools, adapting to obstacles, and making decisions along the way. They operate more like an assistant you’ve delegated to than a tool you’re wielding.
Why This Matters
Agentic systems require different governance, different security models, and different integration approaches than traditional AI tools. If you’re planning for one and buying the other, your implementation will fail in ways that aren’t immediately obvious.
When a vendor tells you their product is “agentic,” push for a demonstration of autonomous behavior. What decisions can the system make without human approval? How does it handle situations it wasn’t explicitly programmed for?
The answers will tell you quickly whether you’re looking at genuine agency or a chatbot with a new label.