AI Governance in US Higher Ed

What colleges and universities are saying about AI, aggregated from their policy pages.

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Institutions Monitored
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Verified AI Policy
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States Covered
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Policies Classified
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Dominant Stance

AI Policy Coverage by State

Rule-based

Verified AI policy coverage rate across {{ data.kpi.states_covered }} states. Darker states have a higher share of institutions with confirmed AI governance.

0-14% 15-29% 30-44% 45-59% 60-69% 70%+ No data

Coverage Gap by State

Rule-based

Percentage of institutions in each state with a verified AI policy. Hover for raw counts. Sorted by total institutions.

Stance Distribution

LLM-classified

How classified policies position themselves on AI use, from outright encouragement to prohibition.

StanceCount%
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Stance by Audience

LLM-classified

Prohibitive policies are overwhelmingly student-facing. Encouraged policies tend to address a balanced audience.

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≤30% 31-60% >60%

Who Owns the AI Policy

LLM-classified

Which department frames the policy. Public universities lead with teaching and learning; private nonprofits frame AI primarily as an academic integrity issue.

Which AI Tools Do Policies Name?

Rule-based

Ranked by the number of institutions that mention each tool at least once. ChatGPT dominates both breadth and depth of coverage.

How Are Tools Referenced?

Rule-based

Context is determined by a 300-character window around each mention. Most tools are merely named without active governance.

Tool {{ c }}
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Low Medium High

Policy Adoption by Type

Rule-based

Public universities lead at 62.4% coverage. For-profits trail at 4.0%, representing the largest ungoverned segment.

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Who Do Policies Cover?

LLM-classified

Enterprise-wide policies govern all campus members including staff. Most institutions still limit scope to faculty and students.

How Deep Do AI Policies Go?

Rule-based

Percentage of policies that mention each operational domain. Nearly all cover academics and staff, but research governance, IT procurement, and formal training remain blind spots across every institution type.

Policy Quality Signals

Rule-based

Three operational prerequisites that indicate whether a policy is ready for real-world use.

Data Risk Awareness

Mentions data classification, PII, FERPA, HIPAA, or sensitive data handling.

Human Oversight Required

Requires human review or verification of AI output before use in decisions.

Formal AI Training

Mentions professional development, AI literacy programs, or certification courses.

Community College Spotlight

Rule-based

Community colleges serve the largest share of US undergraduates but lag in formal AI governance. Most AI mentions are guidance documents or resource pages, not binding policy.

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CCs Monitored
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Mention AI
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Formal Policy
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With Guidance
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With Resource

{{ data.cc_deep_dive.data.total }} CCs currently monitored. {{ data.cc_deep_dive.data.with_hub }} mention AI somewhere on their sites, but only {{ data.cc_deep_dive.data.with_policy }} ({{ data.cc_deep_dive.data.policy_rate }}%) have a formal binding policy.

CC Coverage by State

CC Stance Distribution

Policy Maturity Index

Rule-based

Institutions scored into four tiers based on the depth and breadth of their AI governance. Only 3.6% reach comprehensive status; the majority have no verified policy at all.

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Comprehensive
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Developing
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Minimal
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None

Scoring: dedicated AI page (+3), formal policy (+2), >1,000 words (+1), names tools (+1), balanced audience (+1).

Are Policies Keeping Up?

Rule-based

Staleness signals flag policies that may reference outdated tools or framing.

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Show Staleness Signals
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Institutions Flagged
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Total Classified