For deans, chairs, and faculty leaders
Prepare your campus for AI without giving up on judgment.
Campus AI Ready helps public universities move from scattered pilots and policy memos to a coordinated plan for faculty readiness, course design, assessment, and academic leadership. Built by a professor who still grades on Monday.
The tension on campus
Faculty are being asked to redesign courses while the tools change every semester.
Students already use AI. Employers already expect it. Accreditors are starting to ask about it. Meanwhile most faculty have had one workshop, one memo, and no time. The answer is not a detection tool or a campus-wide ban. It is a learning strategy that tells students what they should now be able to do, and tells faculty how to teach and assess it.
Move beyond
- "Allow it or ban it?"
- "Which detector should we buy?"
- "Another policy revision."
Move toward
- "What should a graduate be able to judge, decide, and defend?"
- "Which assignments show learning now?"
- "Who on our faculty is ready to lead this?"
A readiness framework
Four moves, built on the DART model.
Start where the campus actually is. Build the next layer deliberately.
Diagnose
Find the real starting point. A short survey of faculty use and confidence, a review of current policy, and a look at ten syllabi tell you more than a task force report. You leave with a one-page readiness map by college.
Align
Decide what graduates should be able to do with AI in your disciplines, then map it to program learning outcomes you already report. No new bureaucracy, just a column added to the matrix you have.
Redesign
Make learning visible again. Rebuild the assignments most exposed to AI around process, local context, and explanation. Faculty leave with their own course changed, not a template.
Enable
Give faculty room to practice. Working labs, peer cohorts, and a few trusted colleagues who can answer questions. No one-way demos and no mandates without support.
Case in practice · CSUDH
The Innovation Incubator began with listening.
At California State University, Dominguez Hills, the work started not with a tool but with interviews: owners, employers, and students describing what they needed people to be able to do. What followed became the template this site is built on.
Listen
Customer-discovery interviews with small-business owners and marketing leaders through the NSF I-Corps program, Fall 2025.
Translate
The DART model and two textbooks, Management and Compensation, that build judgment into every chapter.
Convene
Incubator cohorts with the City of Carson, campus partners, and the Toro Auxiliary Partners board.
Build
A faculty-led Incubator with a standing program, and now a readiness practice for other campuses.
AI-resilient assessment
Do not try to out-detect the technology. Redesign the evidence.
Three principles I use in my own courses at CSUDH.
Make the process inspectable
Drafts, decisions, source checks, and a short reflection count. The final file is one piece of evidence, not the only one.
Require contextual judgment
Local cases, incomplete information, and a trade-off the student must defend out loud or in writing.
Assess transfer
Can the student explain the idea, adapt it to a new case, and challenge the AI's version of it?
Courses
Three four-week courses. One tier each.
Every week: one 20 to 30 minute video lecture, one Google Sheets template you fill in as the assignment, and a live office hour on Zoom. Each course ends with a certificate and one piece of your own work changed.
Intro
AI in the Classroom Without Losing the Point
For faculty with no AI habit yet. Weekly templates: a syllabus AI policy builder, an assignment exposure audit, a prompt log with judgment notes, and a personal AI code of conduct.
Intermediate
Redesigning Assessment for the AI Era
For faculty who use AI and want assessments to hold. Weekly templates: a process-evidence rubric, a local-case assignment template, a transfer-and-explanation question bank, and a grading time budget.
Advanced
Leading AI Readiness in a Department or College
For chairs, deans, and program directors. Weekly templates: a readiness map by program, a learning-outcome alignment matrix, a faculty enablement plan, and a procurement and privacy checklist.
All three courses: $1,250. Department license, up to 20 seats: $4,500. First cohorts open in early 2027; email to reserve a seat.
Free · About two minutes
How ready is your campus for AI?
Rate each statement from 1 (not at all) to 5 (fully true). You'll get a readiness score and the areas to look at first. Nothing is saved or sent anywhere.
Ways to work together
Start with the decision in front of you.
Three formats, sized by time. CSU and community college campuses, and any campus referred by a system office or consortium, receive a 20 percent reduction.
Start here
Leadership briefing
For deans, chairs, and provosts' staff. A shared point of view on where the campus stands and the four moves, ending with a one-page readiness map.
Hands-on
Faculty working lab
For a department or college. Hands-on practice in the morning, then each participant redesigns one real assignment with a partner.
One semester
Readiness partnership
For a college or the whole campus. Diagnose, Align, Redesign, Enable over 10 to 16 weeks, with a faculty cohort and a report to the provost.
Events
Come as a guest first.
Every session runs on Zoom and is recorded for members. Guests are welcome at the monthly Campus AI Hour; email for the link.
Monthly · Open to all
Campus AI Hour
One idea, one template, and open questions. First Tuesday of the month, 3:30 to 4:30 p.m. Pacific, starting January 2027.
Monthly · Deans and chairs
Dean's briefing
Forty-five minutes on one decision academic leaders are facing this month: policy, procurement, assessment, or faculty development.
Monthly · Members
Assessment lab
Bring one assignment. Leave with it redesigned. Recordings and templates go to the members' replay page.
About
I have sat on both sides of the table you are at.
I'm Thomas J. Norman, Ph.D., a tenured full professor of management at California State University, Dominguez Hills, past department chair and acting associate dean, faculty founder of the university's Innovation Incubator, and a member of the Academic Senate of the CSU and its GenAI subcommittee on privacy, security, and procurement.
I wrote two textbooks this year, Management and Compensation, that build the DART model into every chapter, and my book Judgment Call is in press. I teach three courses this fall and grade on Mondays, so every template on this site has been used with real students first.
- Full Professor of Management, CSU Dominguez Hills; tenured since 2013
- Past Department Chair and Acting Associate Dean
- Faculty founder, CSUDH Innovation Incubator
- Academic Senate of the CSU; GenAI Subcommittee on Privacy, Security, and Procurement
- Gallup Certified CliftonStrengths Coach
- Ph.D. and M.A., University of Minnesota; A.B., Harvard University
- Author, Management and Compensation (2026); Judgment Call, in press
A practical next step
Give your faculty something more useful than another memo.
Bring one course, one assessment, or one leadership decision. We start there.