AI is reshaping every academic workflow.
The question is who governs it.
Falkovia designs the academic authority structures, decision rights, and faculty alignment frameworks that institutional leaders need before the next accreditation review cycle forces the question.
Accreditation bodies are issuing AI-specific oversight policies. State legislatures are moving on higher education AI requirements. And boards of trustees are increasing scrutiny of AI adoption without always having the expertise to evaluate what they are being told. Some presidents, provosts, and board chairs want a trusted partner who keeps them current on what is happening, translates what new accreditation and regulatory requirements mean for their college or university, and makes sure they walk into every conversation prepared. That is the work this practice was built around. The moment a leader walks into that room knowing exactly what to say.
Explore The Intelligence LayerThe higher education AI governance gap
AI is embedded in admissions processing, grading and assessment, academic advising, research workflows, and administrative operations across higher education. Much of it was adopted by individual faculty, departments, or administrative units without institutional governance approval. Some of it affects student outcomes in ways no one has formally evaluated.
The governance gap is not theoretical. Accreditation bodies are issuing AI-specific oversight requirements. State legislatures are passing AI legislation that applies to public and private institutions. FERPA implications of AI-assisted student data processing remain largely unaddressed. And faculty senates are increasingly asserting governance authority over AI in academic domains.
The question for institutional leadership is not whether AI is being used. It is whether the governance architecture exists to make every AI-assisted decision in your institution defensible: to your accreditors, your faculty senate, your board, and your students.
Dr. Masson understands the governance failures that create exposure; she designs solutions that fix them at the source.
— University President
of higher education institutions report faculty and staff actively integrating AI into academic and administrative workflows
of institutions have formal AI governance policies that address decision authority, oversight, and accountability
states have introduced or passed AI-specific legislation affecting higher education institutions since 2023
Five questions every university president should be able to answer
Decision rights
Who in your institution has the documented authority to approve, restrict, or prohibit AI use in admissions, grading, advising, research, and administrative operations?
Human authority mapping
Where in your institution must human academic judgment remain non-delegable, and is that line documented, or assumed?
Shadow AI exposure
How many AI tools are being used by faculty, staff, and departments right now that were never formally approved, evaluated for student impact, or documented in your governance architecture?
Accreditation readiness
If your accreditor asked to see your AI governance documentation at your next review, what would you hand them, and would it demonstrate the institutional oversight they are now requiring?
Incident response readiness
If an AI-assisted admissions decision, grading outcome, or advising recommendation was publicly challenged tomorrow, does your institution have a documented response protocol, or would leadership be designing one in the middle of a crisis?
What the engagement produces
Discovery & Assessment
Understanding where you stand
Shadow AI Audit
Complete inventory of AI tools in use across academic, administrative, and research domains, including tools adopted by individual faculty or departments without formal governance approval.
G.U.A.R.D. Framework Assessment
Governance, Use authority, Accountability, Risk management, and Documentation framework customized to your institution's accreditation and regulatory environment.
Decision Authority Map
Role-by-role documentation of who holds authority to approve, restrict, override, or prohibit AI in each academic and administrative domain.
Architecture & Protocols
Building the governance infrastructure
Human Authority Line
Documented mapping of where human academic judgment must remain non-delegable, by school, department, workflow, and decision type.
Faculty Alignment Framework
Governance architecture that respects shared governance traditions while establishing clear institutional authority over AI adoption, use, and oversight.
Board Governance Charter
Board-ready AI governance charter defining oversight responsibilities, reporting requirements, and fiduciary accountability structures.
Accreditation Alignment Documentation
Mapping of governance architecture to your accreditor's AI-specific requirements, standards, and oversight expectations.
FERPA and Privacy Architecture
AI-specific student data governance protocols aligned with FERPA requirements, state privacy laws, and institutional data policies.
Operationalization
Making it work from day one
Incident Response Protocol
Documented protocol for AI-related academic integrity events, student complaints, regulatory inquiries, and public accountability situations.
Implementation Roadmap
Phased implementation plan with accountability assignments, milestones, and governance maturity benchmarks designed for the academic calendar and shared governance process.
Who this engagement serves
Presidents
Accountable for institutional AI governance and responsible for ensuring the institution's AI adoption does not create accreditation, regulatory, or reputational exposure that reaches the board.
Provosts
Responsible for academic quality and integrity across AI-assisted teaching, grading, advising, and research workflows, and accountable when AI-related academic decisions are questioned by faculty, students, or accreditors.
General Counsel
Managing legal exposure from AI-assisted academic decisions, FERPA compliance obligations, and the growing landscape of state AI legislation and litigation affecting higher education.
Chief Information Officers
Managing the technology infrastructure that enables AI adoption while navigating the gap between what technology teams deploy and what institutional governance has formally approved and documented.
Compliance and Risk Officers
Responsible for regulatory compliance, accreditation readiness, and risk management across an AI landscape that is evolving faster than most institutional compliance frameworks can track.
Board Members
Exercising fiduciary oversight of AI adoption without operational visibility into how AI is being used across academic and administrative operations, who approved it, or whether governance structures exist to manage it.
Frequently Asked Questions
The architecture is designed for shared governance environments, not against them. Falkovia maps where AI-related academic decisions intersect with faculty authority, academic affairs, and institutional research, and produces governance documentation that the faculty senate can engage with substantively. The engagement is structured to strengthen shared governance, not bypass it.
Yes. FERPA exposure is a core dimension of the higher education engagement. The architecture includes documentation of which AI systems process student records, what data sharing agreements exist with vendors, and where governance gaps create FERPA exposure that has not yet been surfaced internally.
Yes. The engagement maps governance architecture against the AI policies accreditors have begun issuing, including Middle States' AI accreditation policy and the comparable standards in development across other accreditors. The output is documentation an accreditor can review, not a policy document that requires translation before they can evaluate it.
The question is whether the committee has documented decision authority and structural capacity to provide meaningful oversight, or whether it functions as a discussion forum. The diagnostic surfaces that distinction. Many institutions find their committee needs architectural authority it does not currently have, and the engagement is designed to provide that.
Yes, with sector-specific calibration. Research universities carry additional considerations around AI in research integrity and human subjects review. Teaching institutions often face heavier exposure across advising tools, early alert systems, and faculty-deployed AI in coursework. The engagement is scoped to the institution's actual academic operations.
G.U.A.R.D. stands for Governance, Use Authority, Accountability, Risk Management, and Documentation. It is one of several structured instruments Falkovia applies in higher education engagements. The full assessment includes the AI Governance Maturity Index, the AI Adoption Risk Index, a Shadow AI Audit, and the AI Governance Framework for Higher Education Boards, alongside a 50+ question diagnostic mapped to NIST AI RMF, ISO/IEC 42001, and the EU AI Act. The work is calibrated across academic, research, advising, and student conduct domains, with explicit attention to the shared governance environment that distinguishes higher education from other sectors.
Next Step
Your faculty and staff are already using AI. The governance question is whether your college or university is ready for your next accreditation review.
Every engagement begins with a confidential conversation about what your college or university actually needs.
Start a Confidential Conversation