University Adopting AI at Scale

A university or college moving from ad hoc AI experimentation to a structured curriculum, faculty training and a functioning AI lab — without an internal team that has done this before.

Higher Education Government / Public Sector 1,001-5,000 employees Domestic Board

What You Can Expect

A leadership team or faculty cohort that has actually used the relevant AI tools hands-on, not just heard about them; a shared vocabulary for the AI adoption conversation that follows; and a clear, honest recommendation on whether a fuller engagement is actually warranted.

When This Applies

Leadership needs to make an AI adoption decision without any hands-on AI experience

A leadership team is being asked to approve or reject an AI initiative without ever having used the relevant tools themselves in a structured setting.

A department wants a low-commitment way to test appetite before a bigger program

A department wants to gauge real interest and readiness for AI curriculum before committing budget to a full Faculty Development engagement.

In Their Own Words

"As a Department Chair, I need my faculty to actually try the AI tools hands-on before we debate curriculum policy, so that the conversation is grounded in experience, not speculation."

— Department Chair, liberal arts college

"As a VP of People, I need our leadership team aligned on AI basics before we roll out any company-wide policy, so that the policy reflects an informed decision, not a guess."

— VP of People, mid-market company

How We Work

Deliverables

Facilitated workshop session(s); a written summary of key takeaways and recommended next steps; where applicable, a recommendation on whether a fuller Faculty Development or Managed Labs engagement is warranted.

Technology & Tools

Workshop Delivery
Hands-on exercise sandbox

A scoped, safe environment for participants to try AI tools directly during the session

Governance
AI adoption decision framework

A structured framework participants leave with to guide their next AI-related decision

Frameworks Applied

ISO42001

Artificial intelligence management systems — organizational accountability, AI policies, lifecycle governance, risk management and continuous improvement.

See the Full Registry →

How Success Is Measured

Participant-reported confidence increase in using the relevant AI tools (pre/post session)Percentage of sessions resulting in a clear next-step recommendation acted onConversion rate from workshop into a fuller Faculty Development or Managed Labs engagementSession satisfaction score

Representative Scenarios

Liberal Arts College — From One Workshop to a Full Faculty Program Illustrative Scenario

Situation: A department chair wanted faculty buy-in before proposing a full AI curriculum initiative to the wider college.

Approach: A Department Series workshop ran over one term, building hands-on familiarity and surfacing real curriculum questions.

Outcome: The department used the workshop's written recommendations to secure budget for a Full Faculty Development engagement the following year.