AI Strategy for Higher Education
Build AI capacity without losing the human experience.
Practical, human-centered strategy for colleges and universities ready to move beyond experimentation and make thoughtful decisions about AI, work, and student experience.
The Real Opportunity
AI won’t fix a broken system.
AI can increase speed, capacity, personalization, and access. It can also automate confusion, scale inequity, and make a fragmented experience move faster.
The most important question is not simply which tools an institution should adopt. It is whether the people, workflows, policies, data, and decisions surrounding those tools are ready.
My approach starts with the work and the people experiencing it—then determines where AI can create meaningful value.
What Institutions Are Facing
The pressure to act is real. So is the risk of acting without a plan.
Uncoordinated experimentation
Teams are testing tools independently without shared priorities, standards, language, or institutional learning.
Uneven staff readiness
Confidence and capability vary widely, leaving some employees overwhelmed and others working far ahead of policy.
Disconnected systems
AI is introduced into workflows already shaped by fragmented platforms, unclear ownership, and difficult handoffs.
Competing expectations
Students, staff, faculty, leaders, and regulators may have very different expectations about where and how AI should be used.
How I Can Help
Move from scattered activity to institutional capacity.
Engagements are tailored to your institution’s goals, maturity, existing systems, and available internal capacity.
AI Readiness & Strategy
Establish a shared institutional understanding of current activity, priorities, risks, capabilities, and next steps.
- AI-readiness assessment
- Use-case and opportunity identification
- Strategic priorities and implementation roadmap
Workflow & Process Redesign
Examine the work before automating it, identifying where AI can reduce friction and where human judgment must remain.
- Workflow and handoff mapping
- Automation-opportunity analysis
- Human-in-the-loop process design
AI & Student Experience
Design AI-enabled experiences that improve access, clarity, responsiveness, and personalization for students.
- Student-facing use-case design
- Advising and support applications
- Experience, trust, and equity review
Workshops & Capacity Building
Give leaders and teams practical frameworks for evaluating, using, and discussing AI with greater confidence.
- Executive and cabinet workshops
- Team training and facilitated planning
- Custom use-case labs
Guiding Principles
Human-centered by design.
Start with purpose
Define the problem and desired outcome before selecting a tool.
Improve before automating
Avoid making a confusing or inequitable process move faster.
Preserve judgment
Keep people accountable for consequential decisions.
Design for trust
Make AI use visible, understandable, and aligned with expectations.
Build capacity
Help teams learn, adapt, and make better decisions over time.
Engagement Options
Support matched to your stage of adoption.
Executive Workshop
A facilitated session that creates shared understanding and clarifies immediate institutional decisions.
- Leadership briefing
- Opportunity and risk discussion
- Priority-setting exercises
- Recommended next steps
AI Readiness & Roadmap
A structured assessment and planning engagement that turns scattered AI activity into a coherent institutional direction.
- Stakeholder discovery
- Current-state assessment
- Use-case prioritization
- Institutional roadmap
Fractional AI Strategy
Ongoing strategic guidance for institutions implementing AI across multiple teams, functions, and priorities.
- Implementation guidance
- Cross-functional facilitation
- Workflow and use-case review
- Leadership advising
Possible Outcomes
Leave with direction—not just inspiration.
Let’s build an AI strategy grounded in your institution.
Start with where you are, what your people need, and the work you are trying to improve. The technology comes after that.
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