From the College Athletics edition of September 28, 2026
Maryland Athletics publishes GenAI Data Governance with four levels and Golden Rules
University of Maryland Athletics IT · Higher education athletics / IT governance · United States (College Park, Maryland)
- Publisher
- Maryland Athletics IT
- Original publication
- undated page retrieved 2026-09-28
- Source retrieved
- 2026-09-29
What happened
Maryland Athletics IT publishes a GenAI Data Governance guide organizing athletics data into four levels (Level 1 public through Level 4 restricted—no GenAI) so staff can decide what is safe to share, what stays internal, and what needs approval. The sheet includes do's/don'ts and UMD Data & AI Golden Rules: classify first, minimize what you share, use the right approved tool, verify the output, and avoid bulk exports, plus escalation to Athletics IT for a fast data check. No adoption metrics or audit results are reported. Why now: practical staff controls as peer departments adopt GenAI content/ops tools.
Why it matters
Operational GenAI control framework inside a Power conference athletic department—directly addresses student-athlete and institutional data risk in everyday AI use.
Evidence and measured results
Athletics IT page describing four-level classification, Golden Rules list, and Athletics IT escalation path; companion AI Initiative site confirms DIT partnership context.
Limitations and uncertainty
Undated page; detailed sheet is image-hosted; enforcement and audit outcomes not published.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-09-29; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Athletics staff lack a quick classification guide for what UMD data is safe to put into GenAI tools as AI use spreads.
- Stakeholders
- Athletics IT
- Sports medicine / compliance
- Coaches and communications staff
- Campus Division of IT
- Discovery questions
- Which athletics data stores contain Level 3/4 restricted information?
- What enterprise GenAI tools are already approved?
- How do staff escalate uncertain classification today?
- Value hypothesis
- A four-level GenAI data guide with Golden Rules can reduce unsafe prompts if paired with approved tools and an Athletics IT check path.
- Potential engagement
- Governance enablement workshop plus 90-day prompt-audit pilot in communications and compliance units.
- Unsupported claims
- Complete elimination of data leakage
- Legal certification of FERPA/HIPAA from the one-pager alone
- Measured productivity gains from governance alone
Pre-sales engineering
Role takeaway
- Fit
- Policy/control overlay classifying athletics data Levels 1–4 for GenAI use, with approved-tool routing and escalation.
- Architecture and integration
- Map athletics systems to classification levels; route work to approved GenAI; ticket path to Athletics IT for uncertain cases.
- Prerequisites
- Campus data classification scheme
- Approved GenAI tool list
- Staff-accessible governance sheet
- Constraints
- Enforcement is largely procedural/staff-driven
- Detailed do/don't content is image-hosted
- No published audit metrics on the page
- Security
- Level 4 restricted = no GenAI; minimize sharing; avoid bulk exports; verify outputs before use.
- Proof of value
- Staff classification quiz pass rate
- Athletics IT escalation volume and time-to-answer
- Sampled prompt audits in high-risk units
Delivery
Role takeaway
- Work
- Publish/update governance sheet, train staff on Golden Rules, operate escalation inbox, refresh with DIT changes.
- Dependencies
- Campus DIT policy updates
- Approved tool catalog
- Unit manager reinforcement
- Ownership
- Athletics IT owns the guide and escalation; unit leaders own day-to-day compliance.
- Skills and adoption
- Train classify-first, minimize-share, verify-output habits before any GenAI paste of athletics data.
- Governance checkpoints
- Quarterly sheet accuracy review
- Spot audits in sports medicine and compliance
- Annual alignment with campus AI policy
- Acceptance criteria
- Staff can identify Level 4 ban examples
- Escalation path documented and monitored
- Governance linked from AI training materials
- Risks
- Staff using personal ChatGPT on restricted data
- Stale image sheet after policy changes
- Over-blocking that drives shadow AI
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Policy overlay on approved GenAI tools rather than a new model stack; requires mapping athletics systems to classification levels and routing restricted data away from public LLMs.
Governance
Who approves, reviews and stays accountable for outcomes?
Makes classify-first and human verification explicit departmental norms; pairs with campus DIT authority and unit-level accountability.
Security and privacy
What data, permissions and controls need testing?
Level 4 ban on GenAI for restricted data is the key control; minimize-share and no-bulk-export rules target prompt leakage of student-athlete and institutional data.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Gives non-technical athletics staff a short classification habit, but requires literacy training so rules are usable under deadline pressure.
Procurement
What should contracts, pricing and exit terms secure?
Prefer enterprise-approved GenAI tools that support data-classification commitments; contract for no-training and retention controls aligned to Level rules.
Operating model
Which teams own the service once it runs?
Embeds Athletics IT as GenAI traffic cop via escalation path while expecting unit staff to classify before paste.
Publication history
- 2026-09-28College Athletics · Issue 225 resources
Stable resource ID: umd-athletics-genai-data-governance