Training university IT to lead on AI
A prominent Midwest university invested in AI training and enablement to make its IT organization the campus leader on AI
The university had made AI an institutional priority, with the president leading it. Its IT organization wanted to be a partner to faculty, staff, and students in bringing AI to campus. To do that, the CIO first wanted to bring the whole IT team to the same level of expertise.
Staff had access but uneven experience.
The IT department had already made access easy: one platform gave staff a single way in to several leading AI models.
Some staff had little experience with AI, and others were deeply technical. They wanted training that showed AI doing real work, with use cases they could try the next day. The program also had to leave room for skepticism and make people feel safe voicing it. Parts of higher education oppose AI, among faculty and students alike, and an IT team that wants to partner with the campus has to be ready to answer that opposition.
The IT team needed an outside partner who could teach each person at their own level, build in responsible use from the start, and keep a mixed group of technical and less technical staff hands-on.
Assessment, training, then AI agents
We worked with the university’s IT leadership over several months, from program design through hands-on training to a deeper follow-up on AI agents.
- 01
A baseline first
AssessmentWe started with a short AI maturity self-assessment. It gave leadership a de-identified baseline of each person’s AI maturity and helped each person choose the right depth of training. Google Public Sector supported the work with AI credits.
- 02
An in-person program
AI Fluency 101 and 201The in-person program opened with the president and CIO speaking on AI and leadership. Live demos then showed what AI could do with real IT work, and staff split into AI Fluency 101 and 201 tracks. IT staff presented AI projects they had already built. In a hackathon, teams took an idea from zero to pitch, with every person owning a role. Last, a faculty panel answered hard questions, including worries that AI use leads to cognitive atrophy, its environmental impact, and student resistance.
- 03
A follow-up on AI agents
AI Fluency 201Staff asked for more hands-on time, so we came back. We worked with university IT to set up the cloud environment, then led a follow-up 201 session on directing AI agents. Staff followed along as an agent in a demo sandbox reviewed support tickets and security concerns, drafted runbooks, and built a working ticket viewer. The teams took those prototypes back to build on.
A solid starting point
The assessment showed a solid foundation. As at most organizations, the biggest opportunity was connecting AI to larger goals and the future of work. The agent work added a deeper view of more advanced AI implementations.
A more confident IT team
In post-program feedback, the IT team rated the experience very valuable, and most felt more confident using AI at work. The department now has shared baselines, working prototypes, and a visible group of internal champions to support the rest of campus.
When a technology team is expected to lead on AI and its members start from different places, we measure where each person stands before any training.
Then we design the training and enablement with the leaders who own the outcome, keep it hands-on, and roll it out.
Start with a clear baseline
In a 30-minute briefing, we’ll talk through where your team stands and what a hands-on day built around your own tools could look like.
You’ll talk with a partner, and there’s no commitment.