From the College Athletics edition of October 25, 2026
FanWord marketing head's 'AI Playbook' for college sports staff: check every number, name, date and rule, and keep FERPA, medical and recruit data out of unapproved chatbots
The Future of College Sports newsletter (Jayson Schmidt, head of marketing at FanWord) · Athletic department communications, recruiting and administrative staff use of general-purpose AI chatbots · United States (general college athletics audience)
- Publisher
- The Future of College Sports (Substack)
- Original publication
- October 25, 2026 (datePublished 2026-10-25T14:48:27Z, 9:48 a.m. CT)
- Source retrieved
- 2026-10-26
What happened
Part 1 of a four-post series for coaches and staff who run program brand and communications. It names ChatGPT, Claude, Gemini and Microsoft Copilot and advises checking what the school already licenses. It lists failure modes: generic-sounding writing, images that get jersey numbers, logos and faces wrong, and confident fabrication of stats, rules or quotes. Its rule is that anything with a number, name, date or rule gets checked before it goes out. Unless the school has approved a tool, staff should keep out FERPA-covered records, injury and medical information, recruits' personal information, athlete or recruit photos for AI editing, non-public news, and compliance, Title IX or personnel matters. Recruiting publicity and contact rules still apply to AI-assisted messages.
Why it matters
Why now: published Oct 25. It is fresh practitioner guidance aimed at the staff level of the same departments buying AI storytelling tools; FanWord has 24 archived records. It turns the stream brief's emphasis on protecting student-athlete data into a concrete do-not-input list. Relevance is limited: this is advice, not evidence of adoption or outcomes.
Evidence and measured results
Opinion and guidance from a former NCAA Division II head coach who now runs marketing at FanWord, with bias disclosed in the post. No data, sample or evaluation. The data categories listed match common FERPA and institutional policy concerns, but the post cites no specific policy.
Limitations and uncertainty
The author works for a vendor that sells AI to athletic departments. Guidance only, with no measurement. Tool feature descriptions are as of Oct 2026 and depend on license. Not legal advice. Parts 2-4 (recruiting, communications, back office) are not yet published.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-10-25; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Coaches and communications staff use personal AI chatbots without clear rules, which puts FERPA, medical and recruit data and program accuracy at risk.
- Stakeholders
- Associate AD for communications
- Compliance director
- Head coaches and directors of operations
- Campus IT and privacy office
- Recruiting coordinators
- Discovery questions
- Which AI tools does the school already license for staff?
- Do staff know which data categories must never go into a chatbot?
- Who reviews AI-assisted recruiting messages for compliance?
- How are AI-generated stats or images checked before posting?
- Value hypothesis
- An approved-tools list and staff data rules could reduce privacy and accuracy incidents from ad hoc chatbot use. The value is limited to risk reduction, not productivity.
- Potential engagement
- A short staff AI-use standard and training session built on the department's existing Microsoft 365 or Google Workspace licenses.
- Unsupported claims
- Time savings or brand gains from chatbot use
- That any listed tool is FERPA-compliant by default
- That hallucination rates are low enough to skip review
- That FanWord's products follow these practices
Pre-sales engineering
Role takeaway
- Fit
- Departments whose staff use general-purpose chatbots for communications and administration.
- Architecture and integration
- Point staff to institution-licensed AI within existing productivity suites, with saved shared contexts for program voice and hard rules.
- Prerequisites
- Inventory of licensed AI features
- Tenant data-protection and retention settings confirmed
- Approved-tools list from IT and privacy
- Constraints
- Features and data terms vary by license
- FERPA and state privacy law
- NCAA recruiting publicity and contact rules
- Security
- Disable training on institutional data where configurable, prefer enterprise tenants over personal accounts, and consider data-loss rules for student and medical identifiers.
- Proof of value
- Confirm in vendor terms that licensed tenants exclude institutional data from training
- Spot-check a sample of AI-assisted posts for factual errors before and after the fact-check rule
Delivery
Role takeaway
- Work
- Publish a staff AI standard covering approved tools, never-input data, fact-checking and compliance review, and run a one-hour training.
- Dependencies
- IT confirmation of tool settings
- Compliance sign-off on recruiting guidance
- Communications office ownership
- Ownership
- Associate AD for communications with the compliance director, supported by campus IT.
- Skills and adoption
- Staff learn to set up saved project contexts, fact-check AI output and recognize restricted data.
- Governance checkpoints
- Compliance review of the standard
- Privacy office review of data categories
- Annual refresh as tools change
- Acceptance criteria
- Proposed: all communications and recruiting staff complete training
- Proposed: approved-tools list published and reviewed each semester
- Proposed: zero restricted-data entries found in periodic spot checks
- Risks
- Staff keep using personal accounts
- Guidance read as vendor marketing
- Tool terms change without notice
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?
Steers staff toward school-licensed tools (Copilot on Microsoft 365 campuses, Gemini in Google Workspace) and saved project or Gem contexts, rather than personal accounts. Retention and training settings vary by tool and license.
Governance
Who approves, reviews and stays accountable for outcomes?
Departments should publish an approved-tools list and a data-category rule for staff AI use, aligned with compliance and recruiting rules. Without that, the post leaves the judgment to individual staff.
Security and privacy
What data, permissions and controls need testing?
Warns that personal chatbot conversations may be stored and used for training, and names FERPA records, medical data, recruit PII and athlete images as categories to withhold unless a tool is approved.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Aimed at small staffs where one person runs accounts. Training on review habits matters more than tool choice.
Procurement
What should contracts, pricing and exit terms secure?
Favors using AI already included in campus productivity licenses before buying separate tools.
Operating model
Which teams own the service once it runs?
Staff AI use becomes a communications-and-compliance standard rather than individual choice.
Publication history
- 2026-10-25College Athletics · Issue 452 resources
Stable resource ID: fanword-schmidt-ai-playbook-staff-chatbot-data-rules-2026-10-25