Celebrating National AI Literacy Day
The Opportunity: How AI’s Promise for Learners Depends on How Fast Institutions Can Change
A National AI Literacy Day reflection for leaders who are ready for the next conversation
March 2026 | Daniel Gannon, Director, T3 Advisory
Let’s start with what we know.
AI, when done well, is a massive opportunity to grow human capacity.
It may not be “the best thing” to happen to education in a generation, but it is certainly the most significant disruption in the proverbial ivory towers.
But learners deserve better than hype. If IHEs can use AI to its full potential on campus and in their curriculum, something genuinely significant is within reach: a future where a student’s ZIP code, family income, or prior academic preparation is no longer the ceiling on what they can learn, how fast they can learn it, or what they can become.
When fully realized, AI-powered tools can meet students where they are, in ways that traditional instruction, designed for the middle of the learning curve and constrained by time and scale, never fully could. We can provide personalized feedback at 11 pm. Transfer credit can be evaluated more effectively, saving students time and money. Guided pathways can adapt in real time to a student’s actual goals. Learners who arrive underprepared can get personalized support, not by lowering the bar, but by participating in smarter onramps.
That potential is real. And National AI Literacy Day exists, in part, to celebrate learning and in part to help learners and educators see it clearly.
The question is no longer whether AI can unlock something important for learners. It can. The question is whether institutions are built to move at the speed required to fully realize this opportunity.
We Have Moved Past “What Is AI?”
For many of the higher education leaders T3 works with, the foundational questions: what AI is, whether we should engage with it, and whether this is a passing trend, etc., are largely settled. The technology is here. It is reshaping the labor market in real time. Students are already using it, whether or not institutions have policies for it.
The conversation has moved beyond these. And for leaders who are already bought in, a new and harder question has taken its place:
How do we build institutions and an academic strategy that can keep up?
Because the pace of AI development is not slowing down to wait for governance committees, shared faculty governance processes, or annual policy review cycles. The tools available to students and educators today are meaningfully different from those available 18 months ago. The tools available in 18 months will be meaningfully different from today's.
That is not a reason for anxiety. It is a design challenge, and, if we’re being positive, an opportunity to be better. It is the most important opportunity in higher education right now.
The Real Bottleneck Is Not the Technology
In our discovery work, the most common barrier to AI adoption is not access to tools, budget constraints, or even faculty skepticism, though all of those are real.
The most common barrier is organizational. Institutions were not designed to change this quickly.
Policy processes that take 18 months to produce a deliverable are already outdated by the time the product arrives. Professional development models are designed for periodic upskilling rather than continuous adaptation. Governance structures that distribute authority so carefully that moving quickly requires extraordinary effort. Change management that treats AI adoption as a project with a start and end date, rather than a new operating condition.
None of this is anyone’s fault. These structures exist for good reasons; they protect faculty autonomy, ensure deliberate decision-making, and guard against top-down mandates that erode institutional trust. Those values are worth keeping.
But they need to be redesigned for a different tempo.
The institutions that will serve learners best in the coming decade are not the ones that adopted AI the fastest. They are the ones who built the organizational muscle to keep adapting, continuously, responsibly, and with students at the center.
What Change Management at the Speed of AI Actually Looks Like
The institutions making real progress right now share a few recognizable characteristics. They are worth naming because they are learnable.
They have identified a change champion to work at speed. Someone with sufficient institutional authority to drive change and sufficient credibility to bring people along. Not a committee. A person. Someone who can make a decision on a Tuesday and have the executive capacity and resources allocated to implement new practices by the following semester.
They have built living governance structures rather than static policies. They build AI frameworks with evergreen review cycles baked in from the start, because they understand that typical policies designed to last five years in the context of AI are destined to fail. They do not let perfect be the enemy of good and encourage their teams across campus to design with more flexibility, establishing rapid, imperfect processes that keep pace with the speed of change.
They have invested in faculty as the engine of sustainable change. Not through generic professional development, but through discipline-specific, peer-led communities of practice where faculty and staff can experiment, share, and build confidence together. The institutions where AI adoption has taken root are almost always the ones where faculty and staff feel ownership of how it shows up in their courses, rather than compliance with a top-down directive.
And they have reframed the question from “how do we adopt AI” to “how do we become an institution that can keep learning.” That shift in framing changes everything downstream: how PD is designed, how governance is structured, how success is measured.
Seeing Through the Trees: The Learner At the Center
It is easy in conversations about governance frameworks and change management infrastructure to lose sight of what it is all for.
It is for the student who arrived at a community college underprepared and needs more than a traditional classroom can give her.
For the adult learner returning to education after a decade away, trying to build skills for a labor market that looks nothing like the one they’re familiar with.
For the first-generation student who deserves the same quality of academic support as her peers at better-resourced institutions, and for whom AI, done well, might actually provide it.
That is the kind of opportunity worth building toward. Not just AI for efficiency and certainly not as a shiny object, we have enough of those. AI is a tool that, in the right hands and the right institutional conditions, genuinely expands what is possible for learners who have historically been underserved by the systems meant to help them.
National AI Literacy Day is a celebration of that possibility. The possibility becomes reality only when institutions build the capacity to deliver on it continuously and at the speed the moment requires.
That is the work. And it is genuinely exciting.
Work with T3 Advisory
T3 works with colleges, universities, and state systems to build governance structures, faculty engagement strategies, and change-management capacity that make AI adoption sustainable and student-centered. Visit t3advisory.com or connect with us on LinkedIn.
Daniel Gannon is a Director at T3 Advisory, specializing in academic strategy and AI transformation consulting for institutions, systems, non-profits, and foundations.
This post originally appeared on LinkedIn: https://www.t3advisory.com/