Campus AI Agents
02

How agents arrive on campus

Most campuses already have agents; few planned all of them. Agents arrive through ten pathways, and each needs a different first move. An inventory that tracks only what IT builds will miss most of them.

Ten pathways

  1. 01

    Switched on inside existing platforms

    Vendors add agent features to the SIS, LMS, ERP, CRM, or service desk through routine updates.

    Examples
    Workday agents, Salesforce Agentforce (Education Cloud), ServiceNow AI Agents, Instructure Canvas AI features, Ellucian AI features
    Visibility
    Often low — can arrive with no procurement decision.
    First move
    Review release notes; set a default-off or pilot-first rule for agent features.
  2. 02

    Purchased as a standalone product

    A department buys an agent for admissions, advising, tutoring, or support.

    Examples
    Mainstay, Ocelot, Element451, EAB Navigate AI features
    Visibility
    Medium — visible if purchasing routes through review.
    First move
    Add agent questions to procurement and security review.
  3. 03

    Built on an enterprise AI suite

    Staff and faculty create no-code agents or custom assistants in institution-licensed AI tools.

    Examples
    Microsoft 365 Copilot and Copilot Studio agents, Google Gemini Gems and Gemini Enterprise, ChatGPT Edu custom GPTs, Claude for Education Projects
    Visibility
    Low to medium — many small agents, few owners on record.
    First move
    Require registration above T1; set sharing and data defaults centrally.
  4. 04

    Built by central IT or a development team

    Custom agents built on model APIs and frameworks, integrated with systems of record.

    Examples
    Azure AI Foundry Agent Service, Amazon Bedrock Agents, Google Vertex AI Agent Builder, OpenAI Agents SDK, LangGraph, Model Context Protocol (MCP) integrations
    Visibility
    High — but only if the team logs them.
    First move
    Apply the full design-to-retire playbook and the registry.
  5. 05

    Built by departments, faculty, or researchers

    Course assistants, lab workflow agents, and departmental tools built locally.

    Examples
    A course GPT or Gem for a single class, Copilot Studio departmental helpers, n8n or Zapier AI workflows, lab pipelines on model APIs
    Visibility
    Low to medium.
    First move
    Offer a supported platform with guardrails so local builders don’t start from scratch.
  6. 06

    Built by students

    Class projects, hackathons, clubs, and startups — sometimes touching campus data or services.

    Examples
    Hackathon apps on OpenAI, Anthropic, or Google APIs; coding agents such as GitHub Copilot, Cursor, and Claude Code
    Visibility
    Low.
    First move
    Provide sandboxes and clear rules on campus data and branding.
  7. 07

    Brought by individuals

    Personal agents — meeting notetakers, email and browser agents — used with campus accounts.

    Examples
    Otter.ai, Fireflies.ai, and Read AI meeting notetakers; ChatGPT agent; Perplexity Comet and other AI browsers
    Visibility
    Very low — shadow AI.
    First move
    Publish acceptable-use guidance; control app consent in identity systems.
  8. 08

    Delivered through integrations and marketplaces

    LMS apps, browser extensions, video-meeting apps, and plug-ins that add agent behavior.

    Examples
    Canvas and LMS LTI apps, Zoom AI Companion, Microsoft Teams and Slack apps, AI browser extensions
    Visibility
    Low — approved once, updated silently.
    First move
    Re-review integrations when vendors add agent capabilities.
  9. 09

    Shared through a consortium, system, or pilot

    System-wide services, grant-funded projects, or free vendor pilots.

    Examples
    Internet2 NET+ service agreements, system-wide licenses such as the California State University ChatGPT Edu rollout, free vendor pilots
    Visibility
    Medium — ownership can be unclear.
    First move
    Name a local owner and exit plan before the pilot starts.
  10. 10

    Arriving from outside

    Agents acting for applicants, students, vendors, or others interact with campus portals, forms, and staff.

    Examples
    Applicants’ AI browsers completing forms, vendor bots contacting staff, third-party agents calling campus APIs or MCP servers
    Visibility
    Very low — the institution doesn’t own them.
    First move
    Plan for inbound agents: identity checks, rate limits, and terms of use.

Named products are illustrative, not endorsements. Vendor capabilities and names change often — confirm current features before relying on them.

Record every pathway in one place with the agent registry fields. For tracking what was built across campus, see Campus AI Registry.

The ten pathways are this guide’s own synthesis of campus practice. Definitions and sources: What is an AI agent?

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