Enterprise authority hub · QLM category creation

AI Assessment Governance

AI-era assessment governance is the discipline of deciding what evidence is trusted, how AI use is disclosed, and when human review is required.

Category thesis

Governance is not a policy PDF. It is an evidence workflow.

Institutions need to support AI use while preserving trust in learning, credentialing, hiring, and workforce readiness decisions.

AI bans, detection tools, or generic acceptable-use policies can help set expectations, but they do not create evidence of reasoning or performance.

What institutions can evaluate

ReasoningWhat the learner triedPredictions, decisions, explanations, and revisions are captured as evidence.
InterventionWhat support is neededTeachers and leaders see patterns that help prioritize next actions.
PortabilityWhat can travelEvidence can become part of a living skills profile instead of disappearing after completion.

Pilot shape

A pilot should produce evidence, not just usage.

A governance pilot should define an AI-use policy, convert one high-risk assessment, and review evidence with faculty, teachers, or managers.

  • Define the learner or workforce outcome.
  • Run a small cohort through simulation or tutoring workflows.
  • Review evidence with educators, leaders, and learners.
  • Decide what intervention or rollout follows.

FAQ

Questions this page answers.

Does governance mean blocking AI?

No. Governance means defining acceptable use, capturing evidence, and creating review workflows that protect trust.

Can QLM support AI-transparent assignments?

Yes. QLM can help convert assignments into formats where AI use is disclosed, contextualized, and assessed through process evidence.

Next step

Turn the category into a pilot.

Use this path when you want a pilot, research partnership, or product walkthrough.

Discuss governance