Boulder, United States

University of Colorado Boulder

Record status

Policy statusReviewed evidence-backed recordReview: Agent reviewedClaim coverage3 reviewedEvidence-backed claims3Reviewed3Candidate0Official sources3Source languageenPublic JSON/api/public/v1/universities/university-of-colorado-boulder.json

Policy profile

Coverage score85/100Coverage labelbroad public coverageReview: Machine candidateAnalysis confidence78%

AI disclosure

No source-backed public claim about AI disclosure or acknowledgement is present in this profile.

The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Approved tools

University of Colorado Boulder has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.

AllowedMachine candidateConfidence81%Evidence1Sources1

Named AI services

No source-backed public claim naming a specific AI service is present in this profile.

The current public tracker record does not contain claim evidence naming a specific AI service.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Research guidance

No source-backed public claim about research AI use is present in this profile.

The current public tracker record does not contain claim evidence about research use, publication ethics, research data, grants, or human-subjects compliance.

Not MentionedMachine candidateConfidence0%Evidence0Sources0

Security and procurement

University of Colorado Boulder has 1 source-backed public claim for security and procurement; deterministic analysis status: required.

RequiredMachine candidateConfidence81%Evidence1Sources1

AI tools

Derived tool records0

No tool-level evidence is published for this record yet. Broad AI tool mentions are not expanded into named tool conclusions.

Evidence-backed claims

3 reviewed evidence-backed public claim

Security Review

CU Boulder OIT states that AI tools and integrations are evaluated through the Information Technology Accessibility and Security Review Process and that tools or services not completing campus review breach campus guidelines.

Review: Agent reviewedConfidence95%

Normalized value: ai_tools_require_ict_review

Original evidence

Evidence 1
CU Boulder requires that accessibility and security compliance provisions be included in all contracts or user agreements. AI tools and integrations are evaluated by CU Boulder’s Information Technology Accessibility and Security Review Process, also known as the ICT Review Process. The ICT Review Process applies to purchases and adoptions of all information technology regardless of the cost or funding source. The use of tools and services that have not completed the campus review is considered a breach of campus guidelines.

Teaching

CU Boulder Center for Teaching & Learning identifies generative AI as raising teaching questions about assessment design, classroom AI-use expectations, AI literacy, and ethical awareness.

Review: Agent reviewedConfidence90%

Normalized value: teaching_guidance_available

Original evidence

Evidence 1
Generative AI has introduced new considerations and challenges for educators. It raises important questions about how to design valid assessments of student learning, how to communicate expectations around appropriate AI use in the classroom, and how to support students in developing AI literacy and ethical awareness.

Academic Integrity

CU Boulder Center for Teaching & Learning provides instructor-facing guidance on how generative AI complicates academic integrity and how instructors can address misconduct while supporting learning, fairness, and trust.

Review: Agent reviewedConfidence89%

Normalized value: ai_academic_integrity_guidance_available

Original evidence

Evidence 1
The proliferation of generative AI technologies has blurred the boundaries between original, assisted and unauthorized work, complicating how academic integrity is maintained in higher education. This guide synthesizes research and institutional practices to help instructors understand how AI may be reshaping student approaches to academic work and integrity, why students engage in misconduct, and how instructors can address misconduct in a way that supports learning, fairness and trust.

Candidate claims

0 machine or needs-review claim

Official sources

3 source attribution

Change log

Last checkedMay 16, 2026Last changedMay 16, 2026Open change log

Corrections

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