By now we all know that the AI Hype Engine is running at full tilt 24/7 and is probably about to overheat (or maybe it’s already overheated and blown up…). The last couple weeks have been no exception, and the focus of the hype has been AI agents, largely due to the release of Manus, a Chinese AI model that “makes its own decisions without requiring specific instructions from a human operator.”
What is an AI agent, you ask? Good luck finding a consistent answer. Even ChatGPT, which has invested heavily in creating AI agents, can’t agree with itself on what an AI agent is and does.
Even though experts can't entirely agree on a single definition, there are some core ideas most people agree on, and understanding these can help you cut through the hype.
At its most basic, an AI agent is an automated system designed to independently (that’s the key word here) complete tasks on a person’s behalf. Unlike traditional AI tools like chatbots (how are we already using the word “traditional” to describe AI, by the way?), AI agents don't just respond to questions or follow predefined instructions step-by-step. Instead, they can autonomously plan and execute tasks, adjust strategies dynamically, and operate without constant human supervision.
Think of an AI agent as an intern who can manage tasks independently – given a single prompt, it researches, analyzes data, makes decisions, and acts to achieve a goal, even if the goal is complex or requires multiple steps.
As noted above, the distinguishing characteristic of an AI agent is its ability to act on its own. This doesn’t mean that it can (or should) act without human involvement. In fact, it should definitely NOT do that (at least not yet). But an agent is different from a workflow that has been created by a human and then runs by itself.
I encountered this earlier this week when I created an “agent” that, using Zapier, triggers a sequence of events when someone answers the brief “what is an AI agent” survey I created. When I shared it on LinkedIn, I was asked if what I created was a “workflow” and not an “agent.” And it was!
So, what’s the difference? Let's clarify with examples:
True AI agents often use multiple AI models and specialized tools simultaneously, collaborating to deliver more complex outcomes than standalone tools.
It's equally important to know what AI agents aren't:
AI agents represent an exciting leap forward in AI capabilities, but they are largely incapable (for now) of doing many of the things they AI Hype Machine will have you believe they can do.
So for now, my advice is to learn more about what’s possible, try to create some simple workflows or agents of your own, and start to envision what it might look like to have a digital clone of yourself that can do certain things on your behalf.
One week later, on Thursday, May 8, I'm presenting Deploying AI Agents: Boosting Your Team's Output at Mirren Live, an annual gathering of agency business development and client services leaders in NYC.