I bought Claude for my team. Are they using it safely?

First, the good news: you found real value yourself. Some leaders never get there. Now you are confronting three different challenges: a tool a founder loves, a habit a team must adopt, and the risk of Shadow AI. The last two are mostly about people, not software.

Put yourself in your team’s shoes. You bought a powerful tool and told them to use it. To you, that is a gift. To them, it may feel like a test, a threat, or another task on an already full plate. In financial services, the hesitation is sharper: nobody wants to be the person who pasted client information into a system they did not understand. Silence is not always resistance. Growth-focused leaders play offense; employees often learn that defense is safer.

Sharing use cases in meetings is a good start, but it will mostly surface your confident adopters. It will not reveal the analyst who tried Claude once, received a mediocre answer, and quietly returned to Excel.

Work two problems at once. First, make adoption visible without turning it into surveillance. Use basic enterprise activity data to identify unused seats, not rank employees. Pair hesitant users with curious colleagues and protect time for experimentation. Nobody learns a new tool in the cracks between deadlines.

Second, publish a one-page stoplight guide: green for approved use cases, yellow for situations requiring review, and red for information that must never enter an AI system. Bring compliance, cybersecurity, and HR into that process early. Ask employees to share one thing the tool improved and one place it failed; both answers are valuable.

Do not over-measure adoption. If people feel watched, they will perform usage rather than build judgment. The goal is not to prove that Claude gets opened. It is to help the team reach for it safely when it can genuinely improve the work.

Finally, address Shadow AI directly. Explain which accounts and tools are approved, prohibit company or client information from entering personal systems, provide basic cybersecurity training, and document employees’ acknowledgement. Be equally clear that approved activity data is being used to support adoption, not secretly read their work.

You cannot reasonably prohibit employees from using AI privately as a personal “therapist.” You can—and should—prohibit them from using personal AI accounts for company work, technical support involving internal systems, or conversations containing confidential information.

Cover the downside clearly, give people somewhere safe to ask questions, and make responsible experimentation easier than hiding it.