Stop handing AI agents broad permissions, or you may lose control

AI agents can be productive in minutes, but that speed is exactly why permissions matter. ZDNet’s core warning is simple: think twice about the permissions you provide AI agents, and about what they can do on your behalf. The risk is not hypothetical. If an agent can access sensitive systems, execute transactions, or make operational changes without the right guardrails, you are effectively delegating real-world power to software that may misunderstand your intent.

The “intern” analogy lands for a reason. Treat your AI agents like eager but misguided interns, and you will build the kind of supervision that keeps mistakes from turning into incidents. Interns are good at following tasks quickly and badly interpreting context. AI agents can do the same, especially when the task requires nuance that the agent does not truly have, or when your internal goals are broader than the instructions it receives. When the permissions are broad, “misguided” becomes operationally expensive.

This is where modern organizations get into trouble. Many teams are racing to deploy automation, because automation is the easy headline and the obvious ROI lever. But automation without boundaries is not just a technical problem, it is an organizational design problem. If an agent can take actions in the same way a human employee could, then the organization has to manage that agent like a new kind of worker, with onboarding, training, approval flows, and escalation paths. The alternative is to pretend the agent is harmless because it is not a human, while quietly giving it the human version of access.

Board dynamics also matter. Executives and boards do not typically get blamed for “potential” risks. They get blamed for actual outcomes caused by preventable control failures. That is why limiting permissions is not merely a safety best practice; it is governance hygiene. If your AI agent can alter data, create records, send messages, pull customer information, or run changes across systems, then the organization should treat those permissions as a board-level control issue. Otherwise, you can end up with a gap between what leadership thinks is happening and what the agent is actually capable of doing.

There is also a regulatory angle, even if the ZDNet framing stays practical rather than legalistic. Across the industry, regulators increasingly focus on accountability: who is responsible when automated systems produce harmful results, and what controls were in place to prevent foreseeable misuse. When you grant broad permissions, you make it harder to show that you implemented reasonable safeguards. When you constrain permissions, you reduce the blast radius of errors and make your intent clearer to auditors and regulators. You are building a paper trail of control, not just a tech demo.

Second-order implications can be nasty. If an agent is given too much autonomy, you may start to depend on it operationally. Over time, people stop double-checking, because the agent is “usually right.” Then a single misunderstood instruction can propagate through workflows that are now largely automated. The result is a failure mode that looks less like a one-off bug and more like an operational drift, where the organization’s processes quietly recalibrate around the agent's behavior.

There is another layer for decision-makers: incident response becomes harder when the system is empowered. If an agent can take many actions, you have to determine what it did, what it accessed, and what it changed. That increases time-to-containment and complicates forensics. Limiting permissions is how you keep the investigation smaller, faster, and more likely to stay within normal incident-handling capacity.

The strategic takeaway for any executive team is that AI agent control is not a “later” problem. ZDNet’s warning boils down to a governance principle: delegation requires constraints. If you want to use AI agents to move faster, you have to prevent them from moving beyond your intent. Treat them like interns, supervise accordingly, and restrict what they can do. That is how you avoid losing control while still getting the productivity gains you are chasing.