Before You Give AI the Keys
By Ryan Clement · Published
A report finished in five minutes can still send a team in the wrong direction. As AI takes on more work, the question is whether the result deserves our trust.
The promise comes with a responsibility
Microsoft’s September 23 announcement about Dynamics 365 points toward AI doing more of the work that fills an ordinary business day. Alongside those capabilities, Microsoft described planned controls to limit what AI can do on an employee’s behalf.
That deserves as much attention as the promise of saving time. Being able to reach information or take an action does not mean either one belongs in the assignment.
Anthropic offers a similar caution in its guidance for Claude Cowork: be selective about the files it can access. These companies are describing different products, but both raise a practical question for anyone using AI at work: how much access does this task actually need?
When a helpful shortcut becomes a bad decision
Imagine a team asking AI to prepare a briefing on which customers need attention. This is a hypothetical example, but the problem is easy to recognize.
The briefing arrives quickly. It is clear, organized, and confident. One customer is labeled as losing interest because there is no recent contact in the records.
But the account manager spoke with that customer yesterday. The conversation went well. The notes simply have not been entered yet.
If someone checks the recommendation, the gap is easy to catch. If the team accepts it without review, they may change their priorities or send an unnecessary message. If AI also has permission to update records or contact customers, that mistaken conclusion could travel further before anyone notices.
What looked like a time savings now creates work: correct the record, explain the message, and reassure the customer.
The failure began when missing information became a confident conclusion. More access would not necessarily have fixed it. A person who understood the relationship could.
Judge the result by what happens next
There is real value in a briefing that helps someone prepare, identifies an overlooked follow-up, or makes a decision easier to understand. Those are useful outcomes to aim for.
Getting there means deciding what information AI needs, what it may do, and where a person checks the work. Asking for a draft should not quietly become permission to send it. A recommendation should be reviewed before it changes a customer record or someone’s priorities.
Accuracy needs its own check, too. Anthropic’s guidance on reducing incorrect answers makes clear that precautions do not eliminate mistakes. A polished answer still needs evidence.
Before calling an AI-assisted process a success, look beyond the speed of the first draft. Did it help someone make a better decision? Did it reduce the total work, including corrections? Did it protect the trust of the people affected?
I would rather have a useful draft that flags what it does not know than a finished-looking report that gives someone the wrong reason to act.
Give AI a clear job, enough information to do it, and a point where a person takes responsibility. The result should be work you can use with confidence.