What an AI-First University Has to Redesign
Kogod's dean on turning a business school into an 'AI-first' institution — what worked, the cheating problem, and the existential stakes for higher ed.
Original episode title: Creating an AI-First University, w/ Kogod Dean David Marchick
Guest
David Marchick
Dean, Kogod School of Business at American University
David Marchick is dean of the Kogod School of Business at American University. His background spans business education, public policy, international affairs, and government service. As dean, he led Kogod’s effort to integrate AI into teaching, assessment, faculty practice, and the broader business-school curriculum.
Turns an “AI-first university” slogan into an institutional case: curriculum, faculty support, employer demand, and the judgment students still need to build.
Watch on YouTube ▶What this conversation is really about
David Marchick describes what Kogod had to change when AI became part of ordinary teaching rather than a special topic. Faculty rebuilt courses, students used AI alongside disciplinary fundamentals, and experiments moved beyond a few enthusiasts. The examples are practical: entrepreneurship exercises, AI negotiation partners, software built by nontechnical students, and an agent intended to simplify university bureaucracy. The harder work is redesigning assessment and preserving human connection. Students disclose AI use, evaluation takes more than one form, and educators remain coaches. These institutional claims are Kogod’s account, not independent findings.
From the conversation
The argument in focus
David Marchick
Dean, Kogod School of Business at American University
David Marchick is dean of the Kogod School of Business at American University. His background spans business education, public policy, international affairs, and government service. As dean, he led Kogod’s effort to integrate AI into teaching, assessment, faculty practice, and the broader business-school curriculum.
Turns an “AI-first university” slogan into an institutional case: curriculum, faculty support, employer demand, and the judgment students still need to build.
“What we’ve been the first to do is really infuse, in a comprehensive way, AI into every program that we offer.”
Evidence status
Client/operator-reported case
An institutional leader describes curriculum and culture changes. Program details and outcome claims remain attributed and not independently corroborated.
Boundary map
Where the system stops
- What the system handles
- Practice, feedback, simulation, software building, and selected administrative workflows.
- What remains human
- Assessment, disciplinary fundamentals, coaching, disclosure rules, collaboration, and the definition of competent work.
- What remains open
- Which changes improve learning and judgment rather than merely making student output faster or more polished?
Ideas worth carrying forward
- AI fluency works best as a layer on top of domain knowledge, critical thinking, and collaboration.
- A culture that makes experiments and failures visible can move adoption past the early enthusiasts.
- When old outputs become cheap, assess process, judgment, disclosure, and live performance.
- Teach workflows and problem framing, not just whichever AI product happens to be current.
What this changes Monday
Pick one course, team, or internal program and redesign the work rather than merely adding an AI tool. Define what the learner or employee must still know without assistance, what AI may help with, and what evidence will show genuine understanding. Require a short disclosure of how AI was used. Add at least one live, oral, collaborative, or process-based checkpoint. Give the instructor or manager time to coach experiments publicly, including failures. Finally, measure the outcome you actually care about—learning, judgment, service, or workflow quality—not just polished output. The point is not to become a campus of prompt technicians. It is to become an institution that can keep learning.
Original episode notes
What happens when a business school decides AI isn’t a bolt-on elective, but the operating system for how students learn marketing, finance, entrepreneurship, and leadership?
In this episode of AI-Curious, we’re back with David Marchick , Dean of the Kogod School of Business , to see what changed after his earlier promise to become the country’s first AI-first business school .
We dig into what “AI-first” actually means in practice, what worked (and what failed), and how a culture of experimentation turned AI adoption from a handful of pilots into a school-wide shift.
We also tackle the most unavoidable issue in education right now: cheating . David shares Kogod’s approach to disclosure, ethics, group work, oral exams, and why “blue books” may be making a comeback.
From there, we zoom out to the bigger stakes: the existential threat AI poses to universities , how the higher ed business model may change, and what skills still matter when AI can generate content on demand.