Most companies would never give a new employee unrestricted access to every system on their first day.
A new hire might get access to a few tools, a defined set of responsibilities, and additional permissions as trust is earned. Some actions require manager approval. Some systems are restricted entirely. That's not because the employee is untrustworthy. It's because access and responsibility usually grow together.
I've always found it interesting that AI agents are sometimes introduced with the opposite assumption. An agent gets connected to calendars, databases, internal documents, customer systems, and external tools all at once because technically it can use them.
The challenge is that capability and authorization aren't the same thing.
I've noticed that most founders spend a lot of time asking whether an AI agent works and much less time asking what happens after people start relying on it.
Before launching, I'd want clear answers to five questions:
1. What can the agent access?
Data access tends to expand over time. It's worth knowing exactly which systems, documents, and information sources are within reach.
Imagine an AI agent responsible for routing inbound leads. Nothing crashes. No alerts fire. The workflow keeps running exactly as expected.
The problem is that the agent has slowly started sending high-value leads to the wrong queue. Maybe a few customer issues are being summarized inaccurately. Maybe records are being updated with small mistakes that seem harmless on their own. Each individual error is easy to miss. Over time, though, the impact starts to compound.
Those are the AI failures that interest me most because they rarely look like failures at first. There is no outage, no red warning message, and no obvious signal that something is wrong. The workflow continues operating, but the quality of the outcomes quietly drifts away from what the team intended.
That makes detection a different challenge altogether. It's less about system uptime and more about observation. Are there feedback loops? Quality checks? Escalation paths? Can someone spot a pattern before customers, revenue, or operations start feeling the effects?
