Why Everyone's Talking About Agentic AI (and What It Actually Is)

“Agentic AI” is quickly becoming the next big buzzword—but like most hot tech terms, it risks being misunderstood before it’s even fully defined. So what is agentic AI, really? And why is everyone in the AI world suddenly obsessed with it?

From chatbot to co-pilot

The easiest way to understand agentic AI is to think of the difference between a helpful assistant and a proactive co-worker. Traditional LLMs like ChatGPT answer your questions when you ask them. Agentic AI systems go a step further: they take initiative. They can break down goals into tasks, make decisions, and act autonomously across tools and platforms—sometimes without much (or any) oversight.

What’s the hype about?

Agentic AI is exciting because it opens the door to full-on automation. Need a report generated weekly, based on a spreadsheet and some emails? An agentic AI could schedule that, write it, and send it—without waiting for a prompt. These systems can also collaborate across tools, run code, search the web, or even integrate into internal workflows.

The challenges we can’t ignore

But there are trade-offs. Agentic AI can go off-script, especially if it’s given too much freedom or unclear goals. It can hallucinate steps, misunderstand data, or trigger unintended actions. And unlike human agents, it can’t explain why it made a particular decision unless you’ve built in transparency from the start.

How I use (and help others use) agentic AI

In my consulting work, I help people build agentic systems that augment their workflows without losing human oversight. Whether it's a lead-generation pipeline or a document-sorting system, the key is always the same: design carefully, test thoroughly, and stay in the loop.

Final thought

Agentic AI isn’t magic—it’s just software with a little more autonomy. But that autonomy is powerful, and with the right approach, it can help people move faster without giving up control.