The Decision Most Institutions Are Making Backwards
Higher education leaders are under significant pressure to demonstrate that their institutions are engaging with artificial intelligence meaningfully. Trustees ask about it. Accreditors are beginning to. Prospective students and faculty are paying attention to it in ways they were not two years ago.
The response at most institutions has been to move toward adoption before answering the more important prior question. That question is not "which AI tools should we buy?" It is "are we actually ready to implement AI in ways that help our students rather than complicate their experience?"
Readiness is not about technical infrastructure alone. It is about whether your institutional culture can absorb change, whether your faculty have been brought into the conversation as partners rather than informed as afterthoughts, whether your existing policies create a coherent framework for responsible use, and whether you have thought carefully about what student impact actually looks like before the deployment decision is made.
This assessment was built to answer those questions honestly. It will not tell you which vendor to choose. It will tell you whether you are ready to choose responsibly.
The institutions that implement AI well are not the ones with the largest technology budgets. They are the ones that slowed down long enough to understand their own readiness before making commitments they had to walk back.
Full Table of Contents
| 01 | How to Use This Assessment Scoring instructions, how to interpret your results, and how to use this tool with your leadership team rather than completing it in isolation. |
| 02 | Dimension One — Institutional Culture Does your institution have the change management capacity to absorb AI implementation? Eight items assessing leadership alignment, communication practices, and tolerance for iteration. |
| 03 | Dimension Two — Technical Infrastructure What your institution actually needs in place before meaningful AI deployment is possible. Seven items covering data systems, integration capacity, and privacy infrastructure. |
| 04 | Dimension Three — Policy and Governance Where your policy framework stands relative to where it needs to be. Six items covering acceptable use, student data rights, vendor accountability, and faculty academic freedom. |
| 05 | Dimension Four — Faculty and Staff Adoption The human side of implementation — and why it usually breaks first. Seven items assessing training readiness, shared governance involvement, and professional development infrastructure. |
| 06 | Dimension Five — Student Impact Preparedness Whether your institution has thought carefully enough about the student experience before pulling the trigger on adoption. Six items covering equity, transparency, student agency, and outcome measurement. |
| 07 | Scoring, Interpretation, and Priority Setting How to read your results across all five dimensions, identify your highest-leverage improvement areas, and build a sequenced readiness plan. |
| 08 | Vendor Evaluation Checklist and Policy Starter Framework A 15-item vendor due diligence checklist and a starter framework for drafting your institution's AI use policy — built to be adapted, not copied verbatim. |
Dimension One — Institutional Culture
AI implementation is a change management challenge before it is a technology challenge. Institutions that treat it primarily as a procurement decision discover this after the contract is signed — when faculty resistance, administrative confusion, and student concern surface simultaneously without a clear response plan in place.
The items below assess your institution's change management capacity as it applies specifically to AI adoption. Score each from 1 to 5. A score of 1 means this condition does not currently exist. A score of 5 means this is functioning well and would not be a barrier to implementation.
Dimension Four — Faculty and Staff Adoption
Faculty resistance is the most common reason AI implementations stall — and it is almost always preventable. Not through mandates or incentives, but through early, genuine involvement. The institutions that implement AI well typically brought faculty into the conversation at the design stage, not the rollout stage. There is a significant difference.
Dimension Four continues with five additional items covering staff support infrastructure, differentiated training pathways for different roles, and the assessment of baseline AI literacy across your institution. Dimensions Two, Three, and Five follow with their own scoring items and interpretation guidance...
Get the Full Assessment
All five dimensions, the complete scoring guide, the gap analysis worksheet, the vendor evaluation checklist, and the policy drafting starter framework.
Built for These Roles
This assessment was written for provosts, chief academic officers, and deans in higher education — and equally for nonprofit executive directors, program directors, board chairs, and organizational leaders in the for-profit sector who are navigating AI adoption decisions without a clear framework for making them responsibly. The five dimensions are universal. Whether you lead a community college, a regional nonprofit, or a mid-size company, the questions about culture, infrastructure, policy, adoption, and student or constituent impact apply directly to your context.
It is also valuable for institutional research staff, chief information officers who want a framework that goes beyond technical infrastructure, and faculty governance leaders who want to arrive at AI conversations with a concrete diagnostic rather than a general set of concerns.
It is not a technical document. You do not need a background in AI or data science to use it. Every item is written in plain language and connected to the organizational decisions you are already making or being asked to make — whether your organization serves students, clients, communities, or customers.