Episode Overview
Artificial intelligence is rapidly becoming part of university life, but successful adoption depends on more than selecting new technologies. Institutions must make decisions about leadership, governance, trust, and how AI aligns with their educational mission.
In this episode of Learning with AI, host Gladys Mercier sits down with Dr. Tim J. Herd, higher education researcher, governance scholar, and organizational strategist, to explore how colleges and universities can develop thoughtful approaches to AI implementation.
Drawing from his research on university governing boards and his experience advising institutional leadership on scalable generative AI adoption, Dr. Herd discusses why AI should be viewed as an institutional strategy rather than simply a technology initiative.
Together, they explore governance, shared decision-making, faculty engagement, and the structures universities need to support meaningful AI adoption.
Governance Shapes AI Adoption
Universities rarely make significant institutional changes through a single office or department.
Instead, decisions emerge through relationships among governing boards, presidents, provosts, faculty, staff, and students.
Dr. Herd explains how these governance structures influence the way institutions approach AI, why implementation often varies across departments, and how shared governance can either accelerate or slow institutional change.
Rather than viewing AI as an isolated technology purchase, universities have an opportunity to integrate it into broader conversations about academic priorities, student success, and long-term institutional strategy.
"A lot of administrations were really seeing AI not as a governance and strategy issue, but more as a technical procurement issue."
From Technology to Institutional Strategy
Many AI conversations begin with tools.
This conversation begins with institutional leadership.
Dr. Herd argues that adopting AI successfully requires alignment across multiple levels of the university—from governing boards and executive leadership to faculty and academic departments.
Instead of asking which platform to purchase first, institutions benefit from asking broader questions.
How does AI support the university's mission?
How will faculty be supported?
How will success be evaluated?
Who should participate in these decisions?
Viewing AI through this institutional lens helps create more sustainable strategies that extend beyond individual technologies.
Faculty Need Support, Not Just Access
Throughout the conversation, Dr. Herd shares insights from his work as Practitioner in Residence at De Anza College, where he partnered with faculty and institutional leadership to better understand how instructors were approaching generative AI.
Rather than focusing solely on training faculty to use new tools, the initiative emphasized dialogue, resource sharing, and understanding where educators were in their own AI journey.
Some faculty were already experimenting confidently.
Others wanted practical guidance before bringing AI into their classrooms.
Supporting both groups required creating opportunities to learn together rather than expecting immediate adoption.
Building Trust Across Campus
Technology alone does not create institutional change.
People do.
One recurring theme throughout the episode is trust.
Faculty are more likely to embrace new initiatives when they feel included in the process and when institutional leaders create opportunities for collaboration rather than top-down implementation.
Dr. Herd suggests that successful AI adoption depends on partnerships between universities and external technology providers, while also empowering faculty champions and AI fellows within the institution to help bridge those conversations.
Building trust creates stronger implementation and encourages participation across campus.
Preparing Students for an AI-Enabled Future
As AI becomes part of everyday work, universities face an important responsibility: preparing students to use these technologies thoughtfully.
Dr. Herd discusses how institutions can help students develop practical AI skills while preserving critical thinking, academic integrity, and meaningful learning.
Rather than avoiding AI, higher education has an opportunity to teach students how to engage with it responsibly and intentionally.
The conversation also explores why AI literacy should become part of students' broader professional preparation, regardless of discipline.
About Dr. Tim J. Herd
Dr. Tim J. Herd is a researcher, strategist, and self-described social architect whose work focuses on improving complex institutional systems.
He recently earned his Ph.D. in Higher Education & Organizational Change from UCLA, where his research examined university governing boards, power dynamics, and institutional decision-making.
As Practitioner in Residence in the Social Science & Humanities Division at De Anza College, he advised institutional leadership on scalable generative AI adoption.
Beyond his academic work, Dr. Herd serves as Director of Strategy & Culture for the Doctoral Student Writing Collective, supporting more than 700 historically underrepresented doctoral students through writing and professional development. He also serves as Chief Visionary Officer of Black Doctors Creative, where he develops programs that foster professional growth and interdisciplinary collaboration for doctoral-level practitioners across the Los Angeles area.
Key Takeaways
- AI implementation is fundamentally an institutional leadership challenge.
- Shared governance plays a central role in how universities adopt emerging technologies.
- Faculty engagement and collaboration strengthen institutional AI strategies.
- Trust between leadership, faculty, and technology partners supports successful adoption.
- Resource hubs and faculty communities help scale AI adoption across disciplines.
- Universities have an opportunity to prepare students for a future where AI becomes part of everyday professional practice.
Episode Transcription
Intro: Welcome to Learning with AI, a ScholarStack podcast. In each episode we explore how artificial intelligence is changing the way we learn, teach, and think. Through conversations with educators, researchers, students, and academic leaders, we discuss the ideas and challenges shaping the future of learning.
At ScholarStack, we believe AI doesn't replace learning—it enhances it.
We hope you enjoy this conversation. Let's get started.
Gladys Mercier: Welcome to Learning with AI, a podcast from ScholarStack. We bring together voices from across higher education to explore how AI is changing the way we teach, learn, lead, and think. No hype, no easy answers—just honest conversations about an important moment in education.
I'm your host, Gladys Mercier, and today I'm joined by Dr. Tim Herd.
Tim is a higher education researcher, organizational strategist, and self-described social architect whose work focuses on improving complex institutional systems. His research examines university governance, leadership, and institutional decision-making, and he has advised colleges on scalable approaches to generative AI adoption.
Tim, welcome.
Dr. Tim Herd: Thank you so much for having me. I'm excited to be here and to talk about governance, higher education, and artificial intelligence.
Gladys Mercier: Before we dive into AI, I'd love for our audience to learn a little more about your background. You've described yourself as a social architect. What does that mean, and what led you to focus your research on university governance?
Dr. Tim Herd:
I describe myself as a social architect because I'm interested in understanding complex institutional systems and designing structures that help improve them.
That interest began during my undergraduate years at Michigan State University, where I founded a mentorship organization for Black male students after seeing classmates leave the university because they didn't feel supported or connected.
Working closely with university leadership through that initiative introduced me to institutional governance. I became fascinated by how decisions are made, how universities create change, and how leadership shapes student experiences.
That curiosity eventually led me to study higher education at the University of Pennsylvania and later earn my Ph.D. in Higher Education and Organizational Change at UCLA, where I focused my research on university governing boards and institutional decision-making.
As generative AI emerged, I became increasingly interested in the intersection between governance and AI adoption, particularly through my work with De Anza College.
Gladys Mercier:
Governance isn't something many people think about unless they've worked inside university leadership.
Could you explain how governance works in higher education and why it matters when institutions are making decisions about AI?
Dr. Tim Herd:
Universities operate through systems of shared governance.
Although structures vary from one institution to another, major decisions typically involve governing boards, university leadership, faculty, staff, and students.
Governing boards focus on the long-term mission of the institution, while administrators and faculty help translate that mission into day-to-day practice.
Because so many groups participate in decision-making, implementing institution-wide change takes time.
Understanding those relationships becomes especially important when universities begin developing AI strategies.
Gladys Mercier:
You recently worked at De Anza College helping faculty and institutional leaders think about generative AI.
What did that work involve?
Dr. Tim Herd:
As Practitioner in Residence, I worked with faculty in the Social Science and Humanities Division to better understand how instructors viewed AI and how they were—or weren't—using it in their teaching.
Some faculty were already experimenting with AI.
Others wanted to better understand its possibilities before incorporating it into their courses.
Part of my role was conducting an environmental assessment to understand those different perspectives while also creating resources that could help faculty explore AI in ways that aligned with their teaching goals.
Gladys Mercier:
Earlier you mentioned your work at De Anza College, where you helped faculty and institutional leadership think about generative AI adoption.
Could you tell us more about that experience and what you learned from working directly with faculty?
Dr. Tim Herd:
Absolutely.
I worked primarily with faculty in the Social Science and Humanities Division at De Anza College, located in the heart of Silicon Valley.
The dean wanted faculty to become more familiar with AI as conversations about the technology were becoming increasingly common across education and the workforce.
My role involved helping faculty better understand generative AI while also conducting an environmental assessment to learn how instructors were already engaging with these tools.
Some faculty members had already begun incorporating AI into their teaching.
Others wanted to better understand how it worked before deciding whether it belonged in their classrooms.
The goal wasn't to encourage everyone to adopt AI in the same way. It was to understand where faculty were, what questions they had, and how the institution could support them moving forward.
Gladys Mercier:
How long has that work been underway?
Dr. Tim Herd:
It's a relatively recent initiative that officially began earlier this year.
One outcome has been developing shared resources that faculty can use to explore AI, exchange ideas, and learn from one another.
Another important lesson has been recognizing that faculty and students are experiencing AI differently.
When I was a student, AI wasn't part of the learning process. You studied, wrote your papers, and solved problems independently.
Today's students have access to tools that can summarize information, organize ideas, and dramatically improve efficiency.
That creates opportunities, but it also raises important questions.
How do we encourage students to use AI to support learning instead of allowing it to replace learning?
That's one of the biggest conversations happening across higher education today.
Gladys Mercier:
That's something many institutions are wrestling with right now.
From your perspective, how are faculty and university leaders responding to this moment?
What does the process of developing an institutional AI strategy actually look like?
Dr. Tim Herd:
One thing I've noticed through both my work at De Anza College and my collaboration with the Gates Foundation is that institutions often approach AI in very different ways.
Some universities see AI primarily as a technology issue.
Others recognize it as a broader institutional strategy.
That distinction matters.
If AI is treated simply as another technology purchase, conversations tend to focus on procurement, budgets, and software.
But if AI is viewed as part of institutional strategy, the discussion becomes much broader.
It includes questions about student success, equity, teaching practices, governance, and the long-term mission of the institution.
Every university also operates under different circumstances.
Resources vary.
Budgets vary.
Faculty experience varies.
Student populations vary.
Because of those differences, there's no single implementation model that works for everyone.
What matters is developing an approach that reflects each institution's mission while ensuring students have equitable opportunities to benefit from AI.
Gladys Mercier:
I really like that distinction.
Some people see AI as a technology decision, while others see it as an institutional strategy.
When those perspectives differ, who actually makes the decision?
Does the governing board become involved?
Does leadership decide?
Or does each department move independently?
It seems like a very complicated process.
Dr. Tim Herd:
It can be.
That's where shared governance becomes especially important.
Universities are complex organizations.
Faculty, administrators, governing boards, and academic leadership all have different responsibilities and different perspectives.
Because decisions involve many stakeholders, progress often happens more slowly than people expect.
Different departments may also move at different speeds.
One department may already be experimenting with AI while another is still evaluating whether it fits within their discipline.
That variation is natural.
One approach I've found especially helpful is creating institution-wide resource hubs that faculty across departments can access while still allowing each discipline to adapt AI according to its own educational needs.
That creates consistency without eliminating the flexibility that universities value.
Gladys Mercier:
Universities have traditionally given departments a great deal of autonomy because every discipline teaches differently.
The needs of a theater department aren't the same as those of engineering or chemistry.
When institutions begin developing AI strategies, do you think they should create one campus-wide approach, or should each department be free to decide how AI is implemented?
Dr. Tim Herd:
I think there's room for both.
One lesson I've learned through working with faculty is that theory and practice don't always align.
An idea may sound excellent at the institutional level, but when faculty begin applying it inside their classrooms, they quickly discover challenges that weren't initially obvious.
That's why institutions benefit from having a shared foundation while still allowing departments to adapt AI according to their own disciplines and teaching practices.
A university can establish guiding principles that reflect its mission and values, while individual departments develop approaches that fit the needs of their students.
That flexibility allows institutions to remain aligned without forcing every program to use AI in exactly the same way.
Equally important is ensuring that governing boards, executive leadership, deans, and faculty all share a common understanding of why AI is being adopted and what educational goals it is intended to support.
Gladys Mercier:
That balance between institutional consistency and departmental flexibility seems especially important.
Another challenge universities face is the pace of change.
Higher education typically moves carefully, often taking years to evaluate major initiatives.
Meanwhile, generative AI has evolved incredibly quickly.
How can institutions respond more effectively without sacrificing thoughtful decision-making?
Dr. Tim Herd:
One responsibility universities have is preparing students to think critically while also helping them develop the skills they'll need after graduation.
That includes understanding how AI is changing the workplace.
Many students are already asking difficult questions.
They've invested years earning a degree, and now they're hearing that AI may fundamentally change the jobs they expected to pursue.
During several commencement ceremonies this year, conversations around AI generated strong reactions from graduates because these concerns feel very personal.
At the same time, AI is becoming part of everyday life.
It's integrated into search engines, productivity tools, and countless technologies people use every day.
Ignoring that reality doesn't prepare students for the future.
Instead, universities have an opportunity to help students understand how to work thoughtfully with AI while continuing to develop the critical thinking skills that remain uniquely human.
As someone recently said, AI itself isn't necessarily replacing people.
The people who know how to use AI effectively will increasingly shape the future of work.
That makes AI literacy an important responsibility for higher education.
Gladys Mercier:
You've mentioned resource hubs and faculty collaboration.
What else could institutions do to help faculty adopt AI successfully across campus?
Dr. Tim Herd:
One approach I've found especially promising is identifying faculty leaders who can help support AI adoption within their own departments.
Some institutions have begun creating roles such as AI Fellows or faculty AI specialists.
These individuals understand both the academic culture of their institution and the practical realities of teaching within a particular discipline.
Because they're already trusted members of the university community, they can help bridge conversations between faculty, leadership, and external technology providers.
That creates a much smoother implementation process than simply introducing a new platform and expecting everyone to adopt it immediately.
Faculty often feel more comfortable learning from colleagues who understand their teaching context and the specific challenges they face.
Gladys Mercier:
That also seems like an effective way to build trust.
If an outside company arrives and says, "Here's our solution," faculty may naturally have questions.
But when institutions develop those partnerships internally, the conversation becomes much more collaborative.
Dr. Tim Herd:
Exactly.
Trust plays an enormous role in institutional change.
Technology providers bring valuable expertise, but universities also possess deep knowledge about their own students, faculty, and educational culture.
Successful partnerships happen when those perspectives come together.
External organizations contribute technical expertise.
Faculty contribute pedagogical expertise.
Institutional leaders contribute strategic direction.
When those groups collaborate, AI implementation becomes much more thoughtful and much more likely to succeed.
Rather than asking faculty simply to adopt a new technology, institutions create opportunities for shared learning and continuous improvement.
Gladys Mercier:
As universities continue developing AI strategies, what responsibilities should institutional leaders keep in mind beyond teaching and learning?
Dr. Tim Herd:
Universities have a responsibility to think holistically about the impact of AI.
That includes educational outcomes, but it also includes financial sustainability, institutional priorities, and long-term planning.
Before implementing AI at scale, institutions should evaluate the resources required, the costs involved, and the ways these technologies support their educational mission.
Every institution operates under different circumstances, so there isn't a single model that works for everyone.
Leaders need to understand both the opportunities and the tradeoffs before making decisions that affect the entire campus community.
There's also an environmental dimension that deserves more attention.
As AI continues to expand, so does the infrastructure that supports it.
Data centers consume significant amounts of energy and resources, making environmental sustainability another important consideration for institutional leaders.
Thinking carefully about financial, social, and environmental impacts allows universities to make more informed decisions as AI becomes part of higher education.
Gladys Mercier:
It sounds like you're encouraging institutions to think intentionally about the kinds of AI solutions they adopt.
There are companies offering general-purpose AI tools, while others are building platforms specifically designed for education.
Have you seen universities discussing those differences?
Dr. Tim Herd:
Yes.
Organizations like OpenAI and Google are actively engaging with higher education, introducing programs and initiatives designed for universities.
Those conversations are valuable, but successful adoption depends on more than simply introducing new technology.
Faculty often place greater trust in people who already understand their institution.
That's why partnerships are so important.
External organizations contribute technical expertise, while faculty and institutional leaders contribute knowledge about their students, curriculum, and educational goals.
When those perspectives come together, implementation becomes much more collaborative.
I've also seen institutions appoint AI Fellows or faculty leaders who work across multiple departments, helping educators understand how AI can support teaching within different disciplines.
Those kinds of internal champions help build trust while creating stronger connections between universities and technology providers.
Gladys Mercier:
I really like that idea.
Instead of expecting one solution to work everywhere, institutions can create local expertise that understands the unique needs of each department while still contributing to a broader campus strategy.
That seems like a much more collaborative way to approach change.
Dr. Tim Herd:
Exactly.
Universities have always been communities of learning.
AI shouldn't change that.
It should strengthen opportunities for collaboration, dialogue, and shared problem-solving across the institution.
Gladys Mercier:
Before we wrap up, I'd love to ask one final question.
What would you say to educators and institutional leaders who are still hesitant about AI?
Dr. Tim Herd:
I'd encourage them to become familiar with it.
Many people hesitate because they worry about using AI in ways that compromise learning or academic integrity.
Those concerns are understandable.
But AI is becoming part of the systems we use every day.
It's already integrated into search engines, phones, productivity software, and countless professional environments.
Understanding how these technologies work gives people the opportunity to participate in the conversations shaping their future instead of reacting to decisions made by others.
The goal isn't to adopt AI uncritically.
It's to understand it well enough to evaluate it thoughtfully, use it responsibly, and help shape how it evolves within our institutions.
Higher education has an important role to play in ensuring that AI supports people rather than leaving them behind.
Gladys Mercier:
That's a great perspective.
Tim, thank you for joining us today and for sharing your insights on governance, leadership, and institutional strategy.
Dr. Tim Herd:
Thank you so much for having me.
I really enjoyed the conversation.
Gladys Mercier:
And thank you to everyone watching and listening.
The references mentioned throughout today's conversation will be available alongside this episode.
Learning with AI is a production of ScholarStack, offering AI-native infrastructure for education built on learning science and powered by artificial intelligence.
Thank you for joining us, and we'll see you next time.
Outro: Thank you for listening to Learning with AI, a ScholarStack podcast.
We created this space for educators, researchers, students, and academic leaders to explore how artificial intelligence is shaping the future of learning.
To continue the conversation, follow ScholarStack on LinkedIn and visit scholarstack.ai for more resources and insights.
If there's a question you'd like us to explore or a guest you'd like to hear from, let us know.
The future of learning is something we're building together.
Thanks for listening, and we'll see you in the next episode.