Purpose Over Hype: How St. Thomas Is Building AI the Right Way
Most universities are racing to plug AI into everything. The University of St. Thomas in Minnesota is doing the opposite: slowing down, asking better questions, and building on purpose, not pressure.
Led by chief data and AI officer Jena Zangs - recently recognized by CDO Magazine - St. Thomas is showing what a values-first AI strategy looks like in practice. The centerpiece is a simple filter: What is the purpose?
Why This Matters for Education Leaders
St. Thomas is a mid-sized private Catholic university in St. Paul with roughly 10,000 students. It doesn't have the sprawl of a massive research system, and that's an advantage.
With tighter coordination, the university can align AI decisions across academics, student success, and operations. The result: fewer random pilots and more coherent, mission-linked outcomes.
The Architecture of a Purpose-Driven AI Strategy
Every AI initiative starts with mission. For St. Thomas, that means the Catholic intellectual tradition: the common good, human dignity, and ethical reasoning.
Projects are judged by impact, not novelty. Will this help students learn? Will it support faculty? Does it uphold the university's ethical commitments? If the answer isn't clear, the project waits.
The CDAO Role: Strategy Over Systems
The chief data and AI officer is not a CIO with a different title. The CDAO sits at the intersection of technology, policy, and institutional planning.
Zangs's mandate includes building data literacy and AI fluency across campus, partnering with skeptical faculty, enabling staff with practical tools, and preparing students for a job market where AI skills are baseline. This is leadership work as much as it is technical work.
Innovation Without Losing Academic Integrity
Since late 2022, generative AI has raised real concerns about academic integrity. Some schools banned tools; others opened the gates.
St. Thomas is taking a middle path. Use is welcomed where it serves learning and research, with clear ethical boundaries and course-level context. Blanket policies don't fit the varied ways AI shows up in classrooms and research labs.
Data Governance First, Not After
AI built on messy data creates messy outcomes - and erodes trust. St. Thomas flips the script: strengthen data quality, access, privacy, and stewardship before deploying AI.
That means clear policies on who can access what, how data is collected and stored, and how algorithmic decisions are audited and explained. In higher ed, where student records, aid data, and research carry high stakes, this isn't optional. It's the foundation. For more on data governance fundamentals, see EDUCAUSE resources.
What Your Institution Can Put in Place Now
- Write down your AI purpose. One page, plain language. Tie every project to student outcomes, faculty support, or mission-critical operations.
- Create a lightweight AI review board. Include faculty, IT, student affairs, legal, and ethics. Approve pilots with clear goals and exit criteria.
- Fix the data layer first. Inventory critical data, define owners, set access rules, and implement audit trails.
- Start small, prove value. Run short pilots in advising, enrollment communications, or administrative workflows with measurable outcomes.
- Set course-level guidance for generative AI. Provide examples of acceptable use, citation norms, and consequences for misuse.
- Publish an AI use policy for staff. Focus on acceptable tools, data handling, and review steps before deploying automations.
- Invest in people. Offer practical workshops on prompt quality, verification, bias awareness, and tool selection.
- Build procurement guardrails. Require vendors to document data flows, model behavior, security practices, and explainability.
A Model Others Can Learn From
The St. Thomas approach offers three takeaways. First, lead with mission - not with tools. Second, empower a CDAO to bridge strategy and data science. Third, treat culture change and skills as core deliverables, not afterthoughts.
Speed for its own sake creates waste and risk. Purpose creates staying power.
The Road Ahead
Universities will make decisions this year that shape their AI posture for years. The temptation to say yes to everything is real - especially as peers announce big initiatives.
The bet at St. Thomas is different: steady, values-aligned, and built on trustworthy data. If you adopt that stance, you don't just keep up - you build systems your community will actually trust and use.
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