A Q&A With Mike Capone '88, on the Heels of His $1,000,000 Gift to Dickinson
Mike Capone '88 a former Dickinson computer science major, is more engaged with Dickinson than ever, striving to give students every professional advantage.
Capone has spent decades at the center of the industry that his $1 million gift will help students break into
Mike Capone '88 has been a presence at Dickinson since his time as a computer science major, returning most recently as part of the Burgess Institute's Profiles in Leadership series.
The former CEO of Qlik, a global leader in data analytics and AI, has spent decades at the center of the industry that his $1 million gift will help students break into—funding the college's new Data Intelligence Initiative.
Below, he talks about what drew him back to campus, why he believes liberal-arts graduates have an edge in data-driven fields and what he hopes this investment makes possible for the next generation of Dickinsonians.
You’ve now made multiple significant investments in Dickinson’s data analytics and data intelligence efforts. What do you see in Dickinson’s students, faculty and leadership that gives you confidence that the college can succeed in this rapidly evolving space?
Honestly, it comes down to the people—and I’ve seen that at every level of the institution.
When I look at Dickinson’s students, I see exactly the kind of thinkers the data world needs right now. They aren’t just technically capable—they know how to ask hard questions, challenge assumptions and communicate complex ideas to a broad audience. That’s what a liberal-arts education does, and it turns out that those are precisely the skills that separate good data analysts from great ones. The students I’ve met through this program have that combination in abundance.
The faculty have impressed me equally. Building a data analytics program at a liberal-arts college requires real courage and creativity, and the faculty here have embraced that challenge with genuine intellectual excitement. That enthusiasm is contagious, and it shows up in how students engage with the work. I visit the campus regularly to listen to students present their projects, and I always walk away invigorated.
"I want a student who grows up without obvious advantages to walk out of Dickinson with the skills, the experience, the relationships and the confidence to compete with anyone—anywhere. That felt worth investing in."
Dickinson’s leadership understood something important before many others did: Data literacy isn’t just a technical skill set; it’s a foundational competency for the modern world. My career, and what I’ve watched happen in the marketplace over the past two decades, made that crystal clear to me. When I had early conversations with the college about where things were heading, I found that leadership shared that conviction—and was ready to act on it. That alignment gave me the confidence to invest, and what I’ve seen since has only deepened it.
I have also been blessed with a number of like-minded alumni who have invested alongside me and have helped guide the program along the way. Without them, none of this would have been possible.
You’ve talked about the value of a liberal arts education in developing “broad thinking and adaptability.” How do you see those qualities becoming even more important in a world increasingly shaped by AI and data intelligence?
I think about this a lot, and honestly, the more I watch AI evolve, the more convinced I become that a liberal arts education isn’t just holding its own—it’s becoming more valuable.
I spent years as CEO of Qlik, one of the leading data, analytics and AI companies in the world. I watched firsthand as organizations poured enormous resources into data infrastructure, hiring armies of technically brilliant people—and still struggled to translate all of that capability into better decisions. The bottleneck was almost never the technology. It was the human layer. It was people who could look at what the data was telling them, understand the broader context, ask the uncomfortable questions and then communicate a clear path forward to a room full of skeptics. That is a liberal arts skill set.
"When I think about what Dickinson is building, I see an institution that is genuinely preparing students for that future. Not just to find jobs in the data economy but to lead it. That’s why I keep investing. And frankly, that’s why I’m proud to be a part of it."
Here’s the paradox I kept coming back to at Qlik, and that I still think about today: As AI gets better at processing data, running models and automating technical tasks, the premium shifts to the things AI still can’t reliably do—exercise judgment, understand context, ask the right question in the first place and translate findings into decisions that actually account for human complexity. Data without wisdom is just noise.
What I find most exciting—and also quite urgent—is that AI is going to put enormous power in the hands of people who know how to use it. The question is whether those people will have the ethical grounding and critical perspective to use it responsibly. That’s not a technical curriculum question. That’s a liberal arts question. And it’s why I believe institutions like Dickinson aren’t just keeping pace with this moment—they’re built for it.
When I graduated in 1988, we couldn’t have imagined the world we’re operating in today. But the habits of mind I developed at Dickinson—curiosity, rigor, the ability to see across disciplines—those have served me at every turn, including in the boardroom at Qlik, as well as the other companies I work with. I want today’s students to have that same foundation, supercharged with the data skills to thrive in the world that’s actually in front of them.
This new initiative goes beyond classroom learning by funding mentorships, internships, research and real-world projects. Why was it important to you to create opportunities that connect students directly with industry experience?
Because I’ve sat on both sides of that equation—as a student trying to figure out how classroom theory connected to the real world, and as a CEO trying to figure out why so many talented young hires still needed years of on-the-job experience before they could truly contribute. That gap frustrated me for a long time, and funding this initiative was in part my way of trying to close it.
At Qlik, we were always looking for people who didn’t just understand data concepts intellectually but who had actually wrestled with complex, real-world problems. Who had experienced the moment when a dataset doesn’t behave the way the textbook said it would. Who had sat across from a business leader and had to defend their analysis under pressure. You can’t simulate that in a classroom—you have to live it.
"The students who will thrive are the ones who are genuinely comfortable saying 'I don’t know yet, but I know how to figure it out.' That orientation toward continuous learning isn’t just useful, it’s essential."
I also think there’s something that happens to students’ confidence when they work on a real project with real stakes. Suddenly the skills they’ve been building have weight and consequence. They stop thinking of themselves as students learning about data analytics and start thinking of themselves as data professionals who happen to still be in school. That shift in identity is enormously powerful, and it tends to be self-reinforcing—students who get that early exposure aim higher, push harder and enter the workforce ready to contribute on day one.
The mentorship component was equally important to me. I’ve been fortunate throughout my career to have people who opened doors, offered candid guidance and helped me see around corners I couldn’t see on my own. Not everyone has access to that kind of network, and I wanted to make sure Dickinson students—regardless of their background or connections—had a real shot at it. My LinkedIn network is full of Dickinson students. Not just data analytics majors, but students from every discipline.
Ultimately, what I and my fellow alumni donors are trying to fund isn’t just a major. It’s a launchpad. I want a student who grows up without obvious advantages to walk out of Dickinson with the skills, the experience, the relationships and the confidence to compete with anyone—anywhere. That felt worth investing in.
You’ve led technology companies at the highest levels while watching the field transform dramatically over the past few decades. What kinds of skills or mindsets do you think today’s students will need most to thrive in the future data and AI economy?
That’s the question I find myself returning to constantly—and I’ll be honest: The answer keeps evolving as the technology does. But after decades of leading in this space, a few things feel increasingly clear to me.
The first is intellectual humility. Tools that were cutting-edge three years ago are being automated or replaced today. Students who arrive in the workforce convinced that mastering a particular platform or programming language is their competitive advantage are going to find themselves in a very uncomfortable place very quickly. The students who will thrive are the ones who are genuinely comfortable saying “I don’t know yet, but I know how to figure it out.” That orientation toward continuous learning isn’t just useful, it’s essential.
The second is ethical clarity. At Qlik, we used to talk about putting the power of data in everyone’s hands. That’s an extraordinary thing—and an extraordinary responsibility. AI is amplifying that power by orders of magnitude. The professionals who will be most trusted, and most valuable, in the coming decade are the ones who approach that power with a strong moral compass. Who ask not just “Can we do this with the data?” but “Should we?” That kind of judgment doesn’t come from a machine-learning course. It comes from a broad, rigorous education that forces you to grapple with human complexity—which is exactly what Dickinson is designed to deliver.
"I’ve been fortunate throughout my career to have people who opened doors, offered candid guidance and helped me see around corners I couldn’t see on my own. I wanted to make sure Dickinson students—regardless of their background or connections—had a real shot."
The third is the ability to communicate across boundaries. Data and AI are becoming embedded in every function of every organization—finance, marketing, operations, healthcare, government. The professionals who will have the most impact are the ones who can move fluidly between the technical and the human—who can sit with an engineering team in the morning and translate their findings for a board of directors in the afternoon. That is a rare skill, and it is a learnable one. But it requires training that goes beyond the technical.
And finally—and perhaps most important—I’d say curiosity. Not curiosity as a personality trait, but curiosity as a discipline. The best data professionals I’ve worked with over my career share one common habit: They are never satisfied with the first answer. They probe, they challenge, they look for what the data isn’t showing them as much as what it is. In an AI-driven world where answers are increasingly easy to generate, the ability to question those answers intelligently is going to be the defining human advantage.
When I think about what Dickinson is building—combining rigorous data and analytics training with the broad intellectual development of a liberal arts education—I see an institution that is genuinely preparing students for that future. Not just to find jobs in the data economy but to lead it. That’s why I keep investing. And frankly, that’s why I’m proud to be a part of it.
TAKE THE NEXT STEPS
Published July 2, 2026