ASU+GSV 2026 Summit | Monday, April 13, 2026, 9:30 am-10:30 am | Sponsored Partner Programming
Speakers
- David Marchick, American University, Kogod School of Business
Key Takeaways
- David Marchick, Dean of the Kogod School of Business at American University, presented a detailed case study of how Kogod became what Bloomberg recognized as the first "AI-first" business school in the world.
- Over a three-and-a-half-year journey, Kogod moved from initial experimentation to having 90% of faculty teaching with AI, launching an AI major, minor, and graduate degree.
- Marchick outlined a four-phase approach: activation (dean obsession and faculty volunteers), incubation (incentives like $5,000 mini-grants and enterprise Perplexity access), systematization (infusing AI across all core courses), and the current challenge of assessment and measurement.
- A key insight was that the transformation was driven bottom-up by junior faculty -- a non-threatening 28-year-old AI expert trained senior professors -- creating a psychological tipping point when 50% adoption triggered the remaining faculty to join.
- Marchick argued that the future of higher education requires fundamentally changing the instructor's role from authority figure and content disseminator to mentor, coach, and facilitator of learning.
Notable Quotes
"Here at Kogod, you're going to use AI every day for everything you do, or almost everything. But we're going to teach you what's wrong with AI first."
— David Marchick
"One of them said, well, I figured it out. We're using paper and pen. And I basically said, well, that's failure in my view."
— David Marchick
"There was a psychological moment where they said, I better get in front of the parade before it leaves town. And by the fall, we were at 90%."
— David Marchick
"The biggest thing that's next is really changing the role of the instructor... the faculty should become more of a mentor, a coach, a facilitator, a guider of learning. And that's the future of education."
— David Marchick
Full Transcript
I'm going to take you on a 16 minute journey to talk about whether you're AI ready. And as we've approached being AI ready, we assumed that AI was going to change everything. We assumed that it would change everything we do every day in almost every way. And we've been down a three and a half year journey to change the way we deliver education and prepare our students.
So we know AI is going to change everything. It's going to change healthcare. Studies show that if you use AI plus a physician in diagnosing people that come into the emergency room, they can do better job at triage than a doctor alone or AI alone. AI is changing Hollywood and the movie industry.
AI is changing the energy stack in the United States and water usage. It's changing the way that jobs are created and the way that we all perform our jobs. It's changing search. Most young people today use no click search.
They go to their favorite AI agent, put in a question and accept the answer. People maybe my age and some of the people in the room, we're used to iterating. But most people now use no click search if you're young. It's changing the way we write and evaluate the way we write.
This is a New York Times study or survey that I actually did. And I picked the AI writing over human writing 55% of the time. I don't know if you saw this article. Check it out.
It will take you seven minutes. It's fascinating. Anybody dating in the room? AI is going to change the way you date.
So the swipe right, which I never did, now you can have an AI assistant actually scout potential dates for you on Bumble. So it's changing everything. Any pig farmers in the room, AI can improve outcomes. So this study shows that an AI agent can actually identify swine flu in pigs three days before they show other symptoms.
So you can isolate those pigs and protect the rest of your herd. So if you're a pig farmer, AI can help you. And we're early in evolution. So we've gone from AI being an assistant, a collaborator, and now we're moving slowly or maybe rapidly into the agentic AI phase.
And then we'll get to this phase at some point of when AI is as smart as a human in every field. And higher ed, as the introducer said, is next. AI is going to change everything in higher ed. And our approach is to try to change everything as fast as we can.
So here's how we started. It actually started about three and a half years ago. I don't know if that music came on for this. But when we had a CEO, Brett Wilson, come into a class, and a student raised his hand and said, is AI going to replace me?
This was before or right after ChatGPT came on the National Consciousness. And Brett said what we now know, which is it probably won't replace you, but if someone with AI skills might. And so when we heard that, plus hearing the head of Google saying AI is going to be as profound as fire electricity, we said let's change. We went to our advisory committee who said run, don't walk.
We brought young graduates in to train our faculty, including this young woman who basically was on Wall Street as a 26-year-old. She came in and trained our faculty on how to use AI to underwrite investments, to pick stocks, to do fundamental research. She became the ultimate karate kid where the student became the teacher. And so we began this journey three and a half years ago.
And let me cue up a video to show you where we are now. This is from very popular. Hello, and welcome to AI Curious. My name is Jeff Wilser.
I'm a journalist, I'm a human, and I am curious about AI. And two years ago, David Marshak came on this show and made a bold claim. He was going to turn the Kogod School of Business into the first AI-first business school in the country. Not an AI lab, not a computer science department, a business school, the kind of place where people study marketing and finance and entrepreneurship.
He was going to rebuild that all around AI. At the time, I remember thinking, okay, that's interesting, but ambitious. Let's see. So nearly two years later, we invited him back.
And here's what I can tell you. Something happens. Bloomberg picked up the AI-first label. Poets and Quants, which is basically the Bible of business school coverage, recognized Kogod for the most comprehensive AI transformation of any school in the world. 90% of their faculty are now teaching with AI.
They've launched an AI major, a minor, a graduate degree. But the numbers aren't the interesting part. The interesting part to me is what's actually happening in the classrooms. There's a professor, for example, who was initially AI skeptical.
He's been teaching for decades. He's seen deans come and go. He was not really into it at first, but he eventually got so curious, he threw out every textbook and rebuilt his entire course on entrepreneurship using only prompts. There's a negotiations class where students practice against AI counterparts with different including one that's just a complete jerk.
They're using AI everywhere for a more interactive, engaging back and forth with students. So I didn't pay that fellow. It was a nice endorsement. But he's a podcast host on AI.
And so how did we do it? We basically broke down our structure and focused on every course, every program, and the entire school to infuse AI. And then we drove change both from the top down. I became obsessed with it, I would say.
But most importantly, the bottom up. We got the most junior faculty who's an AI expert, 28 years old, to be in charge of training the rest of the faculty. And so she was very non-threatening. So a senior, maybe grumpy, grizzled, 40-year veteran could say, I don't really understand this.
Can you come help me? So it was both top down, but more importantly, bottom up to drive the culture. And here's just a few more examples of what we did. There's a little lag on this.
So first with activation. Basically, as I said, one of our marketing people put the slides together. She said Dean's fixation. I think that was nice.
Maybe neuroses, obsession, annoying. Lots of experimentation. We first started by basically getting five or ten faculty volunteers to either raise their hand or maybe we twisted their arm a little. Then phase two was really incubation where we created incentives.
It might have been a $5,000 mini grant for someone to reinvent and rewrite their course. It might have been psychic income by highlighting someone in a meeting. We gave perplexity enterprise the highest level of perplexity to every student, staff, and faculty. And then we basically gave the faculty kind of freedom and room to fail.
So we basically said try something. If it doesn't work, try something else. Phase three was really to make it systematic across the entire curriculum. So we took all of our core courses and we infused AI into them.
And what you do then is you have a core coordinator and you might have the same course taught ten times. That way you can get scale in that class. And then we went major by major, minor by minor, department by department, subject by subject to infuse AI throughout. Ultimately, there was a point where there was kind of a tipping point in our culture where we got to about 50% of our faculty that were infusing AI.
And that was over the summer at about the two-year mark. And that summer, some senior leaders and I, including Professor Lee who's here who heads our AI Institute, would send emails to faculty saying, well, about 50% of our faculty just wanted to see what you're thinking about for the fall. And when they saw the 50% number, I think there was a psychological moment where they said, I better get in front of the parade before it leaves town. And by the fall, we were at 90%.
Again, it was very, very top down, but most importantly, bottom up. Now, where are we going next? I would say this phase four is really hard. We actually don't know the answers.
We really have not figured out well how to measure the level of AI infusion. We've had three kind of categories. Coach, which is a little AI. Artisan, which is a medium amount of AI.
And then SAGE classes, which is 50% more in the class is AI. But we're trying to refine that and figure it out. If there's any suggestions of what you're doing in the audience, I'd love to know. And then this final one of assessment of learning outcomes.
I think universities, including us, are struggling everywhere to really figure out how you can test skills. If you give students a take-home test, they're going to use AI. If you give them a test in the classroom where they have their computer, they're probably going to use AI. So yesterday, there was a bunch of deans together, and one of them said, well, I figured it out.
We're using paper and pen. And I basically said, well, that's failure in my view. So we're trying to figure this out. We have not yet.
If anybody in the audience has great ideas, I'd love to hear them. So where we are, as the podcaster said, 100% in every department, major, minor. 100% of our AI classes have AI learning objectives. So typically, in every class, you have to have learning outcomes for the class. What do you need to know in physics or marketing, et cetera?
So for every class where we have AI infused, we require the faculty to have AI learning outcomes. And about 90% of our faculty are using it in the classroom. We've mentioned Bloomberg said we're the first AI first business school, major, minor. And then we're also having a lot of badges and certificates to credentialize students.
So here's what an AI first curriculum looks like. In year one, when a 17-year-old freshman comes to us, and they've been told, you're not allowed to use AI in your high school, we tell them, here at Kogod, you're going to use AI every day for everything you do, or almost everything. But we're going to teach you what's wrong with AI first, the biases, the imperfections, the way it can substitute for learning. And then we're going to teach you what's right with AI and how to use it properly.
In year two, they're starting to use AI across the verticals, so in marketing, finance, et cetera. And then they're going deeper in year three with their deep dive in their major. And then by year four, they have a capstone where they're in the same way that an architect has a portfolio of drawings or a musician has a portfolio of compositions they've created. We want our students to have apps and tools that they've created that they can show on their resume that they've created something.
They've written code. They have produced an app, produced software. So that's our capstone. And the same thing at each graduate level.
So five ideas for your consideration. The coach, this is one that was mentioned on the podcast where Tommy White, a professor, basically said, no books, no articles. We're going to develop personalized learning with prompts to take students down a path to discovery. So instead of having a book, which a professor is assigned for the same class for 30 years, now if the student is interested in X, they can find their own articles, videos, their own research on that subject.
And the outcomes and excitement is much better. We're using the same approach in our entrepreneurship class where the first day a student shows up and they're given a prompt, what problem are you trying to solve with a new company? And then that prompt leads them down a path to refine their idea, to understand the market, to develop a pitch, to develop a financial plan. It basically leads them down the discovery of learning.
Strategist, in our marketing classes, we're teaching the fundamentals of marketing that have been taught forever, but students are also learning how to create their own marketing apps, their own tools to create and monitor social media, to be an influencer. Data analyst, this is when we get to higher level classes. This is a grad level class. Automated API workflows to underwrite investments or to analyze corporate earnings.
In this case, they're creating agents to correlate events with stock markets going up or down. I know that would never happen in this day and age as we watch the market go up and down every day. And then system architects, we're teaching our students how to create advanced agentic AI workflows. We require for every assignment, students disclose how they used AI.
So if they just turn in a paper that's been done by AI, they're going to fail. But if they disclose what they're doing and each assignment has instructions on how they should and should not use AI, we require them to disclose it. Now, as the previous panel said, as we infused AI into our curriculum, we also doubled down on all the skills that AI can't teach and help. And those are the soft skills, the power skills, these five Cs, curiosity, compassion.
We worked on these with LinkedIn, who has more data on skills development. So what's next? The big things we're working on, assessment. Again, I don't think anybody really has figured out how to assess learning outcomes, learning about AI.
How do you measure someone's AI fluency and literacy? And also how you assess what they're learning with AI. We're struggling with that. We're developing best practices that hopefully we can share with other schools.
We're trying to create, to drive AI across the rest of the university. My own view is that if you're going to be a doctor, you should have AI on your resume. You should have bio. You should have your labs.
But if you graduate undergrad in 2027, by the time you are actually practicing medicine, it's going to be 2037 or so, AI is going to be infused in everything. So if you have AI skills plus all the other skills that you want for someone to be a doctor, I think you're going to be better off. Niche AI applications. So now we want to infuse the same tools that private equity firms use in our finance courses.
The same tools that accounting firms use in our accounting courses. And then this idea of students having their own portfolio. The biggest thing that's next is really changing the role of the instructor. Changing the paradigm of the instructor being the authority, the person that disseminates knowledge for students to absorb and then spit out or share their knowledge based on the traditional methods.
And with AI, because every young person will have every piece of information at their fingertips, we believe that over time, the faculty should become more of a mentor, a coach, a facilitator, a guider of learning. And that's the future of education. So that is our journey. I appreciate you taking the time and I'd love to hear any ideas from you for things that we should be doing differently or better.
Thank you very much.
This transcript was put together by our friend Philippos Savvides from Arizona State University. The original transcript and additional summit resources are available on GitHub. Licensed under CC BY 4.0.