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AI Changes
AI Risk & Governance
AI Changes
What Can Go Wrong
As organizations give AI more access, autonomy and authority,
the risk question changes from what the technology can do to what
happens when it is wrong, manipulated or given too much power.
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The risk of AI is not only what the model knows. It is what the system is allowed to do.
Capability changes consequence.
An AI system that summarizes information carries one level of risk. An AI agent able to communicate, approve, modify data, trigger workflows or interact with financial systems carries another.
The question is therefore not simply whether the technology performs well. Leaders also need to understand authority, permissions, evidence, escalation and failure containment.
Build
Design useful AI capability around real operational needs,
workflows and decision support.
Govern
Define authority, human oversight, escalation, logging,
accountability and control boundaries.
Defend
Assume systems will be challenged through fraud,
manipulation, adversarial behavior and control failure.
“Build boldly. Govern intelligently. Know what can go wrong.”
The questions executives should be asking.
Who can instruct the system?
What systems can it access?
What actions can it execute?
When must a human intervene?
What happens when confidence is low?
What evidence remains after a decision?
Can activity be reconstructed after failure?
What happens if an adversary manipulates it?
“Safe AI is not AI that never fails. Safe AI is AI whose failures can be anticipated, detected, contained and investigated.”
Move the AI conversation from capability to consequence.
Designed for boards, CIOs, CISOs, risk leaders, AI governance teams, technology executives and organizations deploying AI into consequential environments.
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