Campus AI AgentsA field guide Start
Strategy + practice · Version 1.2

A practical framework for governing AI agents in higher education.

Assess the risk, assign an owner, set the controls, and check the results, before and after an agent goes live.

Assess an agentStart with the basics

Start here

  1. 01

    Inventory

    List the agents you already have, including ones built into licensed software. Record each owner, its data access, permissions, and who it affects.

    Registry fields →
  2. 02

    Classify and control

    Score each agent on the six lenses, set baseline controls and approvals, and write down the risks still open.

    Score an agent →
  3. 03

    Pilot and monitor

    Run a limited pilot, measure performance and equity, set escalation paths, and record a go, revise, or stop decision.

    Evaluating →

The order matters more than the timeline. How long each stage takes depends on readiness, procurement, and risk.

Why it matters

Agents can send messages, change records, and start workflows for students and staff. Many are already on campus, turned on in licensed platforms, bought by departments, or built by faculty and students. Few campuses track them all.

They take action

An agent that changes a record needs an owner and limits. A use policy alone won't cover it.

Students carry the risk

Errors in advising or financial aid hit first-generation, disabled, and working students hardest.

Ad hoc gets expensive

Unmanaged agents duplicate cost, protect people unevenly, and leave no one accountable.

How to use it

  1. 01

    Understand

    What an agent is and how it reaches campus.

    What is an AI agent →
  2. 02

    Decide

    Six questions that set the oversight level.

    The six lenses →
  3. 03

    Govern

    Five control tiers matched to risk.

    Control tiers →
  4. 04

    Apply

    Scenarios, checklists, and templates.

    Tools & templates →

Written for campus leaders, governance and IT teams, and the faculty and staff who build agents. Adapt it to your institution.

Start by role

Executive · CAIO · CIO

Set direction, portfolio, and accountability.

DimensionsGoverningEvaluating

AI governance & risk

Classify agents and right-size controls.

DecidingGoverningEvaluating

Technical & platform teams

Build and run agents safely at scale.

DoingScenariosTools

Academic & student-success leaders

Protect learning and close equity gaps.

ScenariosEvaluatingEquity

Faculty & staff builders

Build useful agents within guardrails.

ScenariosDoingTools

The guide

  1. 01What is an AI agentDefinition and how agents arrive on campus
  2. 02Why it mattersThe institutional case for agents
  3. 03ImpactReported outcomes and incidents
  4. 04DimensionsThe 12 institutional dimensions
  5. 05DecidingSix lenses and risk classification
  6. 06ScenariosRole- and domain-based agents
  7. 07DoingDesign, pilot, deploy, monitor, retire
  8. 08GoverningControl tiers and oversight
  9. 09Standards crosswalkNIST AI RMF, privacy, security, accessibility
  10. 10EvaluatingMetrics, equity, sunset criteria
  11. 11Tools & TemplatesChecklists, rubrics, policy starters
  12. 12On campusAnnotated examples and patterns
  13. 13ReferencesEvery source cited
  14. 14About & how to usePaths by role; author and contact
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