Should AI be allowed to ‘see everything’ at work?

For years, AI at work felt like a quiet helper in the background. It summarized meetings, suggested text, and answered questions when we asked. That era is ending.

The latest AI agents are beginning to move through systems more like teammates. They join projects, update plans, and act across teams. For the first time, organizations are effectively bringing on colleagues that can see more of the workplace than any single person ever could.

I’ve spent years building tools to give teams clarity and save them time, so I see the upside. But that shift forces a harder question: what does it really mean for an AI to “see everything” in a workplace?

The ethical issue isn’t whether agents can technically access information. It is whether their access mirrors what a reasonable employee would encounter in the course of doing their job.

When Visibility Turns Into Influence

Most workplaces rely on role-based access and permissions to maintain order. People see only the information relevant to their role, and those boundaries shape how teams collaborate and how they resolve disagreements.

AI agents complicate that system. If an agent has more access than it should, even by accident, it can surface information that changes how work is interpreted and shifts decisions away from the people meant to make them.

These scenarios usually appear in small ways first. An employee might ask an agent a question and receive an answer based on sensitive information they did not realize was in the agent’s scope. 

People also produce their best ideas through drafts, notes, and early sketches that are not meant for broad consumption. Even the chance that AI might leverage those early drafts changes how people ideate. They’ll start revising earlier, sharing less freely, and spending more time avoiding misinterpretation.

Each incident can seem isolated, but together they alter how authority, context, and trust flow through an organization.

What Responsible Use Should Look Like

The central question for leaders is not what AI agents are capable of doing; it is what they should be allowed to see. Boundaries must be clear before these systems become part of daily work.

An agent working on behalf of an employee should have the same access that employee has, no more and no less. Anything else creates uncertainty. Who can see what? Who can change what? That uncertainty erodes internal trust.

Limiting agents to any other standard also creates problems. An agent that lacks access to shared context, public decisions, or common company knowledge will give incomplete or misleading answers. Ethical design is not about minimizing access. It is about giving agents enough accurate, live context to be genuinely useful.

Responsibility also has to remain with people. Access defines what an agent can do; accountability defines who owns the outcome. When an agent takes an action, the individual who invoked it should be accountable for the result. Just like a manager owning the work done by their team, delegating tasks to AI can help with efficiency, but decision-making still belongs to the humans who direct the work.

Private creative spaces deserve protection as well. Drafts, personal notes, and early explorations help employees test ideas before presenting them. These spaces do not need to be sealed off, but they should be clearly defined and respected. Preserving them supports healthier experimentation and a more open exchange of ideas.

Transparency matters throughout this process. Protected spaces only work if the system around them is visible and understandable. When an agent recommends an action or executes one, employees should be able to understand, at a basic level, how it reached that conclusion.

As companies adopt AI agents more widely, technical and organizational decisions will converge. The systems will influence how teams collaborate, how information moves, and how people feel about their work. This shapes whether AI becomes a supportive part of the workplace or a source of friction.

The issue is no longer whether AI can see everything. It is how leaders define the limits, and how clearly they communicate those choices to the people who rely on them.