Straight answers for presidents, provosts, deans and AI task forces on AI strategy, governance, faculty buy-in, academic integrity and accreditation. Written by Eric Goodman, Ph.D., a former chief academic officer.
Last updated October 2026
Start by finding out where your people actually are. Listen to faculty, staff and students before writing policy or buying tools, then set governance, then train by role. The free AI Readiness Benchmark takes about 3 minutes and shows leaders where their institution stands.
AI readiness is how prepared an institution is to adopt AI responsibly across teaching, operations and student services. It covers leadership alignment, governance and policy, faculty and staff skills, data and privacy, academic integrity, and how change actually gets made on that campus.
The president sets direction, but AI strategy works best when the provost and CIO lead it together. AI touches teaching, research and operations at once, so it stalls when one office owns it alone. A cross-functional group with a clear executive sponsor and decision rights works best.
Most task forces have opinions but not evidence. Higher Ed OS gives yours the data it is missing: what every stakeholder group actually thinks and needs, routed into prioritized actions the task force can act on and report.
Yes. Without one, each department and instructor makes up its own rules, which creates uneven student experiences and data risk. A good policy sets campus-wide principles and leaves room for course-level decisions.
At minimum: approved and prohibited uses, data privacy and which tools may handle student data, academic integrity expectations, disclosure rules for AI-assisted work, procurement review for AI tools, training expectations by role, and a schedule for reviewing the policy as the technology changes.
It is the structure that decides who approves AI uses, who reviews AI tools, how risks are assessed, and how decisions are reported to the cabinet and board. It turns a policy into decisions people actually make, with owners and timelines.
Review it at least once each academic year, and sooner when a major tool your campus relies on changes how it handles data. Name an owner and a review date in the policy itself.
By listening first. Faculty shape the plan through structured interviews before any training or policy reaches them, which is how change survives shared governance. Faculty resist change imposed on them, not AI itself.
Training should match the role. Faculty need course design, assessment and integrity guidance. Advisors need student-support uses. Administrative staff need workflow and data-handling skills. Leaders need governance and risk judgment. One generic session for everyone rarely changes practice.
Vendor training teaches a tool. Higher Ed Change leads the change: governance, faculty buy-in, measurable readiness, and training matched to each role and institution.
No. AI changes parts of the work, such as drafting, feedback and administrative tasks, but teaching depends on judgment, mentoring and relationships. Institutions that train faculty to use AI well will get more from it than those that avoid it.
Set campus-wide principles, then let each course state clearly what AI use is allowed. Redesign assessments so they value process and reflection, not just a final product. AI detection tools alone are not reliable enough to base misconduct cases on.
In most programs, yes, with clear rules. Employers expect graduates to use AI well. The real question is which uses support learning in each course, and that answer should be written down for students.
Increasingly, yes. Accreditors look for evidence that an institution governs new technology, protects academic integrity and assesses learning outcomes. Your AI policy, training records and outcomes data become evidence in a review.
AI touches several standards at once: academic integrity, faculty qualifications and development, assessment of student learning, and data governance. Documenting AI decisions now makes the next self-study easier. Eric Goodman, Ph.D., is a former HLC Peer Reviewer and led a 10-year SACSCOC reaffirmation with no academic findings.
Higher Ed OS is the operating system for AI change on campus. It hears every stakeholder group, trains every role, and routes what it learns into prioritized actions leaders can act on and report.
Presidents, provosts, deans and AI task forces at colleges and universities that want evidence, not opinions, behind their AI decisions.
Participation requires no account, responses are de-identified before analysis, and every action is logged in a full audit trail. Higher Ed Change reviews your data and privacy requirements before any deployment.
By taking a baseline, then measuring again at set points: stakeholder sentiment, training completion by role, policy adoption and the actions completed. Higher Ed OS reports measured outcomes, not promises.
A free, 10-question assessment for college and university leaders. It takes about 3 minutes and gives instant results showing how ready your institution is to lead AI, plus a report sent by email.
Any senior leader: president, provost, dean, CIO or task force chair. Results are most useful when several leaders from the same institution take it and compare answers.
You see your results right away and receive a report by email. If you want to go further, you can book a 60-minute Executive Briefing to review the results with Dr. Goodman.
Higher Ed Change helps colleges and universities lead AI adoption the way change actually happens on campus: listening to every stakeholder, setting governance, and training every role, with measured outcomes.
Eric Goodman, Ph.D., is the founder of Higher Ed Change. He has spent more than 25 years leading change inside colleges and universities as a chief academic officer, vice president of academic affairs and dean, and he led Western Governors University's College of Business, growing it to more than 22,000 students.
Online-first and adult-serving institutions, private nonprofits, multi-campus systems, community colleges, and regional and state universities.
A 60-minute session with your leadership team. You leave with a clear picture of where your institution stands on AI and a written summary to share with your cabinet.
You don't have to. Start with the free benchmark or a 60-minute briefing. The AI Operating Model Sprint is fixed in scope and timeline, so you know the cost and the deliverables up front.
A fixed-scope engagement of 30 to 45 days. It delivers leadership alignment, a governance model, priority workflows and a 90-day roadmap for AI at your institution.
Email [email protected], call 303-335-5800, or book an Executive Briefing at higheredchange.com.
Bring it to a 60-minute Executive Briefing. You'll leave with a clear picture of where your institution stands and a written summary for your cabinet.