AI Agents Are Being Oversold. Here's What They Actually Do Well.

The hype around AI agents has outpaced the reality. Significantly.

Most of what's being marketed as an 'AI agent' is a chatbot with a better prompt. It doesn't reason. It doesn't plan. It doesn't adapt to unexpected inputs. It follows a script with slightly more flexibility than the chatbots of five years ago.

That said, I'm building AI agent systems for clients every day. The gap between the marketing and the reality doesn't mean agents are useless. It means you need to understand what they're actually good at.

Where agents work today

AI agents excel at structured tasks with clear inputs, defined outputs, and access to the right knowledge. Think: drafting a first pass of a client report using data from three specific sources. Routing incoming requests to the right team based on a set of classification rules. Transforming raw data into formatted deliverables.

The pattern is consistent: agents work when the task is well-defined, the knowledge base is organized, and the human reviews the output before it ships. That last part is non-negotiable for anything client-facing.

Where agents fail

Agents fail at ambiguity, politics, and novel situations. They can't read a room. They can't tell when a client is frustrated versus confused. They can't navigate the organizational dynamics that determine whether a recommendation gets adopted.

The companies that get in trouble are the ones that deploy agents for these situations and then blame the technology when it doesn't work. The technology is fine. The task selection was wrong.

The 80/20 of agent deployment

In my experience, the sweet spot is using agents to handle the 80% of any workflow that's predictable and structured, freeing the human to focus on the 20% that requires judgment, creativity, and context. The agent does the first draft. The human does the final pass. The agent does the data pull. The human does the interpretation.

That's less exciting than 'fully autonomous AI agents,' but it's what actually works. And in practice, it's transformative. Reclaiming 80% of repetitive work changes what a team is capable of.