Technology, Leadership, and the Future of Work
AI Governance Checklist for Corporate Boards
Most boards ask whether the AI is working. These are the questions they should be asking instead. A practical companion to the five-part AI Governance for Boards series.
The Workforce Question Boards Aren't Asking
Most boards have had the AI workforce conversation. Jobs displaced, jobs created, retraining commitments. Those are the right questions. They are not the hardest one. When your AI gets something wrong, do the people responsible for catching it still know how to catch it?
What Your Board Should Be Seeing and Probably Isn't
If your regulator called tomorrow and asked you to describe your AI risk profile, what would you say? Not what management presented last quarter. What you actually know. For most boards, the honest answer is very little. That is a governance gap, not a reporting gap.
Can You Defend That Decision in a Courtroom?
Most organizations have an AI explainability policy. Very few can answer the question a regulator or jury actually asks: why did this person, in this situation, receive this outcome? That's a different standard. Most organizations haven't built it.
When Everyone Is Accountable for AI, No One Is
Most organizations feel like they've handled AI accountability. They have a committee, a policy, oversight across every function. When something goes wrong, the structure collapses. Because the test of accountability isn't who signed the policy. It's who answers.
The Three Questions Every Board Should Be Asking About AI
Boards aren't failing on AI because they don't understand the technology. They're failing because they haven't established the governance structures that make accountability real. Three questions change that.