Safe AI for Boards and Leaders
Make AI decisions you can stand behind.
A 90-minute live course for boards, executives and department leaders. Learn to assess, reduce and oversee the risk of any AI decision.
Why this course
AI is moving from answering questions to acting on your behalf
That raises the stakes, because behind every AI decision is a member who trusts you to get it right. It's also a risk leaders can govern. This course gives you a disciplined way to weigh each AI decision, insist on safeguards that actually hold, and approve AI with your eyes open.
Who it's for
Built for the people accountable for AI
The curriculum
What we'll cover
Five modules, built around real decisions your institution is making now.
AI strategy and Safe AI go together
Safe AI isn’t a brake on your AI strategy. It’s what lets that strategy scale.
- Why every AI ambition depends on the controls behind it
- How your safeguards decide which AI uses you can approve, and how quickly
- The cost of treating safety as an afterthought: stalled projects, exam findings and lost member trust
- Building Safe AI into your strategy from the very first use case
From answering to acting
AI is starting to take action, not just give answers. That changes how closely it needs to be governed.
- Where AI simply informs, and where it makes or carries out decisions
- Why risk rises each time AI moves closer to acting on its own
- Where AI is already taking action at credit unions and community banks
- How to decide what level of autonomy is acceptable for each use
The risk equation
A simple, repeatable way to weigh any AI task: the harm it could do against how clearly you can see what it did.
- Gauging the potential harm of an AI task: what it touches, how many people, how reversible
- Judging your visibility: records, decision trails and the sources behind each answer
- The two ways to lower risk: limit what the AI can do, or improve how well you can see it
- Why the goal is AI that is easy to check, not AI you have to trust
Guardrails that hold
Some safeguards warn. Others stop. Leaders need to know which is which.
- The difference between guidance an AI can ignore and limits it cannot cross
- Why instructions alone are not enough when money or member data is involved
- Hard limits that matter most: transaction caps, approvals and restricted access
- Finding the last line of defense if every other safeguard fails
Proving it works, and keeping it working
AI isn’t approved once. It has to keep earning that approval.
- How AI should be tested before every change, on its own and with other systems
- Where people must stay in the decision, and where automation can help them keep up
- What leadership should see from management every month
- What examiners are likely to ask, and how to be ready with answers
Your presenters
Taught by the engineers who build Safe AI
Enroll
Save your seat for November 12
One live session, 90 minutes, taught by Eltropy's CTO and Head of AI Engineering.
