Why I rebuilt my business program around AI — and what deans should know

When generative AI arrived on campus, the instinctive administrative response across higher education was policy: update the syllabus statement, buy detection software, and wait for guidance from accrediting bodies.

Within one term, that strategy proved ineffective. Students were already using AI across finance, marketing, and management assignments. Meanwhile, regional employers were asking why recent business graduates couldn't critique model outputs or analyze financial data with AI assistance.

As Dean of Business at ECPI University, I chose a different path: instead of fighting AI, we set out to build practical tools and equip our faculty to lead the integration.

Here are three key lessons from that work:

1. Faculty need usable assignment tools, not abstract policy statements

Telling faculty to "embrace AI thoughtfully" creates anxiety. Giving them an assignment-design tool with built-in visible thinking and rubric checkpoints creates confidence. When faculty see that AI can elevate student reasoning rather than replace it, resistance turns into collaboration.

2. Document everything for institutional review from day one

Accreditation and institutional review committees do not penalize innovation; they penalize unmeasured changes. By mapping every AI learning activity to recognized competencies and Bloom's Taxonomy, our program built clear evidence of learning outcome alignment.

3. Outside vendors can't own your curriculum — your team must

Software subscriptions come and go. The only sustainable path is capability transfer: developing practical tools with your departmental leads and teaching them how to use AI to adapt, extend, and create new materials independently.

That is why I founded Diffusion Higher Ed. Through focused, remote advisory engagements, I work directly with business deans and academic chairs to develop practical tools, anticipate hurdles, and build institutional capability that lasts.