TECHNOLOGY
There’s a meaningful difference between an AI that answers questions and an AI that takes actions.
We’ve spent the last few years getting comfortable with the former. Chatbots, copilots, writing assistants — tools that respond to prompts and wait politely for the next one. We’ve built workflows around them. We’ve worked out roughly where to trust them and where to check their work.
Agentic AI breaks all of that. And I don’t think most organisations are remotely prepared for it.
What “Agentic” Actually Means
An AI agent doesn’t just generate text. It executes multi-step tasks across tools, systems, and APIs — often without a human in the loop at each step. It books the meeting, sends the email, queries the database, updates the record. It acts.
That shift from “generate” to “act” is not incremental. It is categorical. The error modes are completely different, the trust requirements are completely different, and the governance frameworks needed are completely different.
“The shift from ‘generate’ to ‘act’ is not incremental. It is categorical.”
The Problem Nobody’s Talking About
When a chatbot hallucinates, you get a wrong answer. When an agent hallucinates, it might send an email to the wrong person, delete a file, or execute a financial transaction based on faulty reasoning. The blast radius of an agentic mistake is orders of magnitude larger.
Most enterprise security models weren’t designed for this. Most IT governance frameworks weren’t designed for this. Most audit trails weren’t designed for this.
What Good Looks Like
The organisations getting this right are treating agentic AI like they’d treat a new employee with significant system access: limited permissions to start, clear escalation paths, detailed logging of every action taken, and a human review step for anything irreversible.
That’s not technophobia. That’s just sensible risk management. The exciting capabilities are real — but so are the failure modes.
Tags: Artificial Intelligence • Opinion • Technology & Society • 192.168.1.22/