For each of the following 10 questions, select the option that best reflects your institution today.

Scale:
1 = Not in place
2 = Early discussion
3 = Partially established
4 = Well established
5 = Fully embedded across the institution

Leadership & Decision Ownership

01 

Our institution has clearly defined ownership among leaders for AI strategy and decision-making.

This includes having a responsible party for coordinating AI initiatives across academic, administrative and technology functions.

BACK

NEXT 

Leadership & Decision Ownership

02 

Our institution has a clear process for evaluating and approving new AI tools or use cases.

This includes oversight that considers institutional risk, academic priorities and operational impact.

BACK

NEXT 

Governance & Institutional Guardrails

03 

Our institution has established policies or guidance regarding responsible AI use.

This includes considerations such as academic integrity, data privacy, transparency and ethical use.

BACK

NEXT 

Governance & Institutional Guardrails

04 

Governance bodies (IT leadership, academic leadership, legal/compliance, shared governance) are aligned on how AI decisions should be made.

BACK

NEXT 

Data Readiness

05 

Leadership has confidence in the quality, consistency and governance of institutional data.

BACK

NEXT 

Data Readiness

06 

Our data environment allows responsible access and integration across key systems (SIS, CRM, LMS, finance, etc.).

BACK

NEXT 

People & Institutional Culture

07 

Faculty are receiving guidance or development opportunities related to AI use in teaching and learning

BACK

NEXT 

People & Institutional Culture

08 

Staff across administrative units understand how AI may impact workflows, operations and decision-making.

BACK

NEXT 

Measurement & Institutional Impact

09 

Our institution has identified priority areas where AI could meaningfully support institutional goals (student success, enrollment, operations, etc.).

BACK

NEXT 

Measurement & Institutional Impact

10 

Leadership has defined how AI initiatives will be evaluated and when they should scale, pause or sunset.

BACK

SHOW MY RESULTS 

Your Score

10–24: Early Stage

Focus on establishing ownership, guardrails, and a shared institutional roadmap.

25–39: Emerging AI Readiness

Focus on leadership alignment, governance design, and data foundations.

40–50: Strategic AI Readiness

Focus on scaling, prioritization, and measurable outcomes.

What Your Results Mean

Most institutions are still building the foundations required to support AI at scale. Gaps in governance, data readiness, and leadership alignment are common and addressing them early is what separates experimentation from long-term impact.

Dynamic Campus partners with higher education leaders to turn early AI activity into a coordinated, institution-wide approach. This includes establishing governance frameworks, strengthening data foundations and aligning AI initiatives to institutional priorities.

Advance Your Institution’s AI Readiness

Whether your institution is in the early stages, building momentum or preparing to scale, the next step is moving from assessment to action with a clear, structured path forward.

If you're ready to turn AI potential into institutional progress, let's discuss your results and build a roadmap that aligns AI strategy, governance and adoption with your campus priorities.

AI Adoption