AI Governance Is Not Just a Policy Exercise
One of the biggest mistakes institutions can make with AI governance is treating it as a document-production exercise.
Write the policy.
Publish the policy.
Put it on the website.
Done.
But responsible AI adoption does not happen because a policy exists.
It happens because people understand what the policy means in practice.
Faculty need to know what responsible AI use looks like in teaching and assessment.
Students need clarity about what AI use is permitted, restricted, or prohibited.
Administrators need guidance on using AI with institutional information.
IT and data teams need clear expectations around security, privacy, and approved tools.
Leaders need to understand where human accountability cannot be delegated to an AI system.
This is why AI governance has to be connected to AI literacy.
People cannot follow rules they do not understand.
And they cannot make responsible decisions if they do not understand the risks and limitations of the technology.
For post-secondary and tertiary institutions, governance should therefore answer practical questions:
What can I do?
What should I avoid?
When do I need approval?
Who do I ask?
What happens if something goes wrong?
The goal is not to make everyone an AI expert.
The goal is to make responsible AI use understandable and achievable.
Governance provides the guardrails. People make the decisions.
And both have to work together.
Comments