AI Oversight for Boards and Directors
Ask the questions a board should ask about AI strategy, risk and value, and know what good answers sound like
A taste of a lesson
Management reported 30 AI pilots launched this year. Is that good news?
It is activity, not yet results. Thirty pilots could mean healthy experimentation or scattered effort with no follow through. Useful follow up questions: which pilots had success criteria set in advance, how many reached a decision, what outcomes were measured against a baseline, and what was stopped and why? Also ask who owns each one and whether any touch customer data. A strong answer names a few pilots that scaled and several that were deliberately ended. Which of those questions would you ask first at your next meeting, and why?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Distinguish board oversight of AI from management decisions
- Read a management AI update critically and spot what is missing
- Use a question bank covering strategy, risk, data and people
- Place AI oversight within existing committees and risk processes
- Specify the regular reporting a board should expect
Lesson plan
- 1 Oversight versus management Clarify the board's role on AI and the decisions it should not make. Start
- 2 Strategy: threat and opportunity Assess how AI may change the organisation's market, costs and model. Start
- 3 The risk landscape Map AI risks onto the existing enterprise risk framework. Start
- 4 Reading a management update Evaluate a sample AI report and identify gaps and warning signs. Start
- 5 Structures and reporting Decide where AI oversight sits and what regular reporting should contain. Start
- 6 Board capability Plan how the board keeps its own understanding current. Start
Try asking
About this tutor
For board members, trustees, non executive directors and executives who report to boards. Boards are increasingly expected to oversee AI without micromanaging it or being dazzled by it. This tutor covers what AI changes for strategy and risk, how to read a management AI update critically, the questions that reveal whether a programme is well run, how AI fits existing risk, audit and data governance structures, and what reporting a board should expect over time. It stays at the level of judgement and governance, never legal advice, and always points to your own counsel and regulators' guidance for specific obligations. You leave with a question bank and a simple reporting template.
Reviews
4.5
2 ratingsSample
- Margaret H.Sample
Exactly the right altitude for a non executive. The exercise on reading a sample management report was worth the price on its own.
- Femi O.Sample
Clear on the line between oversight and management. Appropriately careful about regulation, which was a little frustrating but correct.
About the teacher
Helps leaders choose AI work that pays for itself and drop the projects that do not
9 tutors 353 lessons taught Sample
I teach managers and executives how to make sound decisions about AI without needing to become engineers. My background is in strategy and operations work inside companies, where I spent a lot of time turning vague ambitions into projects with a budget, an owner and a way to tell if they worked. I teach with real decisions: a use case...
See Sofia's profile and tutorsMore like this
Other tutors on the same or nearby topics.