Faculty Senate AI Approval Process Guide

Faculty Senate AI Approval Process for Shared Governance

A Faculty Senate AI approval process extends existing shared governance authority to cover AI-specific risk factors, such as data access, system permissions, and post-deployment auditability, by combining academic policy review with a parallel technical and security review before a request reaches a Senate vote.

What Shared Governance Means for AI Adoption

Shared governance is the long-standing structure through which faculty, administrators, and governing boards distribute decision-making authority over academic policy, curriculum, and institutional standards. AI systems introduce a category of decisions that combine academic judgment with technical risk, such as a classroom tool that also processes student data, a research assistant that accesses proprietary datasets, or an administrative agent that acts on institutional systems. Applying shared governance to AI does not require building a parallel structure. It requires extending the Faculty Senate's existing review authority to cover criteria that traditional curriculum review does not typically address, including data access, system permissions, and auditability after deployment. Treating AI governance as an extension of academic oversight, rather than a separate IT-only function, keeps faculty accountable for decisions that affect instruction and research while ensuring technical risk is evaluated by people qualified to assess it.

Mapping AI Use Cases to Faculty Senate Authority

Not every AI tool proposed for campus use carries the same governance weight, and treating all requests identically slows the process without improving oversight. AI use cases generally fall into three categories: classroom or instructional use, research use, and administrative or data-processing use, each with a different risk profile. A generative writing tool used for a single assignment does not require the same scrutiny as an agent-based system with access to student information systems or research data repositories. Faculty Senates implementing an approval process typically benefit from defining tiers in advance: low-risk instructional tools that can be cleared at the department or committee level, and higher-risk tools, particularly those with system access or autonomous execution capability, that require full Senate review. Defining these tiers before requests arrive gives faculty a consistent basis for evaluation and gives requesters clear expectations about what documentation their proposal will need.

Technical Review Criteria for AI Approval

Faculty Senate review can remain grounded in academic governance while also requiring a parallel technical and security assessment. The following criteria help reviewers distinguish policy questions from operational risk questions.

Data access and permissions

What student, research, or institutional data the tool can read or write, and whether access follows least-privilege scoping.

Runtime behavior

What the tool is able to execute or access during an active session, as distinct from what it was designed to do.

System integrations

Whether the tool connects to the learning management system, student information system, or other institutional platforms.

Logging and audit capability

Whether the tool's actions and outputs can be recorded and reviewed after use, not just evaluated at approval time.

Hosting and update cadence

Whether the tool runs on institutional infrastructure or third-party hosting, and how often the underlying model or vendor terms change.

A Structured Faculty Senate Approval Workflow

The approval process is easiest to sustain when academic review, technical review, Senate deliberation, and post-approval oversight are treated as connected stages rather than isolated decisions.

Academic Review

Faculty evaluate instructional, research, or curricular impact.

Technical Review

IT or security staff assess data access and system permissions.

Senate Deliberation

Full Senate or delegated committee approves or rejects the request.

Post-Approval Oversight

A designated owner monitors the tool after deployment.

Sustaining Oversight After Approval

Senate approval should define both the decision to approve a tool and the conditions under which that decision remains valid.

Set a defined review interval rather than treating Senate approval as permanent.

Establish clear triggers for re-review, such as vendor model updates, expanded scope of use, or incident reports.

Assign a standing committee or named role responsible for monitoring tools already approved.

Document revocation authority separately from approval authority so it is not left ambiguous.

Maintain a record of what was approved, under what data conditions, and by whom, for future audit reference.

Where continuous permission enforcement or usage logging is needed, runtime governance tooling can supplement Senate policy decisions without replacing the governance decision itself.

Common Governance Questions

Do vendor-provided AI tools require different Senate review than internally built tools?

Vendor tools generally offer less visibility into underlying model behavior, which limits an institution's ability to independently verify data handling or version changes. Review criteria should account for this reduced visibility by requiring more explicit documentation from the vendor on data access, retention, and update practices before approval.

Who has final authority over AI tools used for administrative rather than instructional purposes?

This varies by institution and should be explicitly defined rather than assumed. Administrative AI systems often fall under combined authority, with IT or executive administration owning operational risk decisions and the Faculty Senate retaining authority where the tool affects academic records, evaluation, or faculty workload.

What typically triggers re-review of an already approved AI tool?

Common triggers include a vendor-side model or feature update, expansion of the tool's use beyond its originally approved scope, a security incident, or the passage of a defined review interval. Institutions that treat approval as a one-time event without renewal criteria create gaps in oversight.

Faculty Senate AI Approval Process for Shared Governance

What Shared Governance Means for AI Adoption

Mapping AI Use Cases to Faculty Senate Authority

Technical Review Criteria for AI Approval

Data access and permissions

Runtime behavior

System integrations

Logging and audit capability

Hosting and update cadence

A Structured Faculty Senate Approval Workflow

Sustaining Oversight After Approval

Common Governance Questions

Bring Structured Oversight to AI Tools After Approval