EdTech Connect Podcast

Episode: Matthew Seitz – Humans + AI = Business Impact at UW Madison’s AI Hub

Host: Jeff Dillon
Guest: Matthew Seitz, Director, AI Hub for Business, University of Wisconsin–Madison
Release Date: October 31, 2025

Episode Overview

In this standout episode, host Jeff Dillon sits down with Matthew Seitz to dig into how artificial intelligence (AI) is actively transforming business education and the broader world of work. As Director of UW–Madison’s AI Hub for Business (and a former Google executive), Seitz shares insider knowledge on integrating AI ethically, leveraging human–AI partnerships, preparing students for future careers, and driving real business impact. The conversation is energetic, insightful, and filled with actionable observations for higher ed and beyond.

Key Discussion Points and Insights

1. Ironman Training as a Metaphor for AI Transformation (03:15–05:45)

• Shared Challenges: Seitz compares preparing for Ironman triathlons to leading AI change in organizations, emphasizing that people often fear the hardest-sounding component (like swimming), which is not necessarily the biggest challenge.
  • Quote:

    "People are afraid or concerned about some really big things...that in their minds aren't the biggest issues really to deal with when you start digging into it. And so I think that's the bridge I'll make on it." —Matthew Seitz (05:22)

• Lesson: Facing the fear of starting—whether with Ironman or AI—is often tougher than the journey itself.

2. Four Technical Revolutions and Why AI is the Biggest (06:14–07:15)

• Seitz reflects on witnessing the rise of the PC, the Internet, the smartphone, and now AI. He argues AI is transformational because it builds on all previous revolutions.
  • Quote:

    "AI will be the biggest. It builds on the other three, but I think it'll be the biggest." —Matthew Seitz (06:18)

3. UW–Madison AI Hub: Mission and Activities (07:29–08:44)

• Vision:
  The AI Hub is a shared service and a leader—a resource for AI-driven research, industry partnerships, and hands-on education.
• Connecting Industry and Academia:
  Seitz leverages decades of business experience, making the AI Hub a bridge between industry needs and academic innovation.
• Forward-Looking Programs:
  The Hub hosts an annual summit, produces weekly newsletters, and organizes webinars for continuous AI literacy and application.

4. AI Governance and Faculty Readiness (08:44–10:16)

• Faculty Spectrum:
  • 30% are eager adopters, 30% are uninterested, and the remainder are unsure—mirroring the typical curve in tech adoption.
  • Policy and guidance are crucial, but the AI Hub supports, rather than leads, governance efforts.

5. Critical Skills for the AI Era: The “Barbell” Analogy (10:22–11:25)

• Three Core Competencies for Students:
  1. Domain Mastery: Know your subject deeply.
  2. AI Literacy: Be “AI ready”—companies expect it.
  3. Adaptability: Tech revolutions are accelerating; adaptability is now a must-have.
• Quote:

  "If you're coming out of school in marketing, you better know marketing cold because the AI might get it wrong...you better know AI...and adaptability." —Matthew Seitz (10:33–11:16)

6. Humans + AI = Business Impact (13:58–15:03)

• Roles of Humans:
  • Humans define goals, provide creative input, oversee budgets, and interpret AI outputs.
  • In fields like marketing, supply chain, HR, and legal, AI augments—not replaces—the human expert.
• Practice Over Theory:
  • Real business impact comes from thoughtful human–AI partnerships.
  • Quote:

    "Impact from a business perspective is a human working with AI...the human is critical to work with the AI to find results." —Matthew Seitz (13:58–14:45)

7. Industry Partnerships and Student Engagement (15:03–17:23)

• The AI Hub is building an impressive advisory board from top-tier companies (e.g., Google, Reddit, Medtronic).
• Explosive student interest: Over 80 students already in the new AI-focused student org; six industry speakers lined up for the term.
• Curriculum Evolution:
  • Moving quickly to update syllabi, but also leveraging speakers and case studies to keep things relevant.

8. Common Myths and Misconceptions About AI Adoption (17:23–18:50)

• Polarized Perceptions:
  • Some leaders expect AI to solve everything; others reject it after a single bad experience (“it hallucinated once”).
  • Reality is nuanced—both magic bullet and total flop are inaccurate extremes.
• Adapting Established Processes:
  • Traditional software lifecycles must evolve to accommodate the unique needs (and uncertainties) of AI systems.

9. Judging AI Use: Coding vs. Creative Writing (20:21–22:23)

• Double Standards:
  • Coding with AI is publicly celebrated—even when imperfect—while using AI for writing still carries a stigma.
  • Underrepresented groups face higher bias if they disclose using AI tools for creative work.
  • Quote:

    "If someone says, I used AI to do this, they're regarded less well...it's even worse if...minority groups or underrepresented groups have a higher bias, and so they'll often...be less open about using them." —Matthew Seitz (21:02–21:21)

10. AI and Learning: The MIT Study (23:32–24:53)

• MIT: "Your Brain on ChatGPT"
  • Students who used ChatGPT from the start produced less original work, had less recall, and lower ownership.
  • The best learning occurred when students drafted first, then used AI for revision and ideas.
• Teaching Approach Insight:
  • Blending standalone creativity with AI-assisted revision may be ideal for fostering both skills.
  • Quote:

    "Those students actually learned the most because they first tried to do it themselves and really did that hard work, and then they had a new round of ideas come in." —Matthew Seitz (24:40)

11. Industry vs. Academia: What’s Cheating, What’s Expected? (26:02–26:25)

• Fascinating Paradox:
  • What’s considered “cheating” in class (using AI to generate essays) is expected in industry.
  • Education must walk a tightrope: preserve foundational learning and produce AI-savvy graduates.

12. Integrating Research, Practice, and Humanity: Fashion AI Study (26:38–28:04)

• Highlight of UW research:
  • AI-designed fashion outperformed human designs but leveraged human-created data (crowdsourced), creating a symbiotic model.
  • Quote:

    "They had a way of humans plus AI that delivered the results that was then both valuable for research, but also had businesses saying, okay, now I can think about how to use AI in design that preserves the humanity but also has a at it." —Matthew Seitz (27:14)

13. Advice for Aspiring AI Superheroes: The Running Shoes Analogy (28:43–30:19)

• Nike’s carbon-plated shoes changed the marathon game; now AI presents a similar era.
• Key Takeaway:
  Now is the moment to adopt AI tools—early users get ahead, just like early adopters of “super shoes” in running.
  • Quote:

    "If you use the tools now, you can actually be ahead because a lot of people aren't...It's a moment right where we are and I think people should take advantage of." —Matthew Seitz (29:10, 30:13)

Notable Quotes & Memorable Moments

• On starting things that seem hard (Ironman/AI):

  "How many things don't you start because the beginning is hard? ...It's all hard, but not a little intimidating, but not that bad." —Jeff Dillon (05:45)

• On stigma in creative AI use:

  "My sense is that goes away in three years...just like, you know, Google or all the other tools, like using a calculator..." —Matthew Seitz (21:33)

• On future-proofing careers:

  "We're kind of like that right now...Now is a unique moment to take advantage. Right. And really be a leader." —Matthew Seitz (29:10)

Important Timestamps

• 03:15–05:45: Ironman–AI transformation parallels
• 06:14–07:15: Experiences through four tech revolutions
• 07:29–08:44: AI Hub mission and strategy
• 10:22–11:25: Essential skills for students in the age of AI
• 13:58–15:03: Humans + AI for business results
• 20:21–22:23: Coding with AI vs. writing stigma
• 23:32–24:53: MIT study: Best practices for AI in learning
• 26:38–28:04: Case study: Human-AI synergy in fashion research
• 28:43–30:19: Take your “free speed”—adopt AI now for a competitive edge

Recap & Actionable Insights

• For Higher Ed Leaders: Consider how policies and culture can encourage wide, responsible AI adoption and bridge the “cheating” vs. “expected skillset” gap with industry.
• For Faculty: Share best practices and prompt libraries; think creatively about mixing foundational work with AI augmentation for deeper learning.
• For Students & Professionals: Become fluent in both your discipline and AI—early, active adoption sets you apart in a rapidly changing workforce.

"We're kind of like that right now. If you use the tools now, you can actually be ahead because a lot of people aren't. And so you're more Effect. You're that superhuman and your peers aren't."
—Matthew Seitz (29:10)

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