In this guide
Boards are being asked to back AI adoption faster than most have been briefed on its risks. This is a short, plain-language summary of what a board actually needs to understand and ask about, without the hype or the jargon.
What changes when you adopt AI
- Data exposure. Staff paste sensitive data into tools you do not control, and that data may train someone else's model or leak.
- A new attack surface. Prompt injection, model manipulation and insecure integrations are real and largely unfamiliar to most teams.
- Vendor and model risk. You inherit the security posture of every AI provider and the models behind them, often with little visibility.
- Decisions you cannot explain. Models that drive decisions create accountability and regulatory questions when no one can say why.
The questions a board should be asking
- Where is company and customer data going when we use these tools?
- Who owns AI risk, and how is it reported to us?
- What is our acceptable-use policy, and is anyone enforcing it?
- How do we evaluate the security of an AI vendor before we commit?
The governance to put around it
Adopt AI deliberately: an acceptable-use policy, an approved-tools list, data-handling rules, and the same vendor due diligence you apply elsewhere. None of this needs to slow the business down; it keeps a fast-moving capability from becoming an unmanaged liability.
Get the full brief
The download is a two-page version you can put in a board pack, with the risks, the questions and a simple maturity check to gauge where you stand today.