If you walk into almost any cabinet meeting this year, you will likely hear some version of the same conversation. Someone raises artificial intelligence, and the room gets split into two groups: 1) those who want a policy yesterday and 2) those who want a pilot first. A few months later, the institution has a task force, a gen-AI policy and maybe a virtual chatbot for admissions. Leadership calls it progress; however, it isn’t agility. Rather, it is what happens when an institution finally confronts a challenge that exposes how little capacity it has built to adapt.
The misstep is treating AI as disruption rather than as evidence of a deeper challenge. The real issue is that most colleges and universities have struggled for years to adapt academic programs, policies and institutional practices as quickly as the world around them changes. AI has clearly made that gap impossible to ignore. At its core, AI is the flashlight revealing a problem that existed long before ChatGPT came on the scene. Most colleges have not built agility—the capacity to move people, budgets and processes at the speed their environment demands—into the way they operate.
Think of an institution as an ocean liner: hundreds of people aboard, multiple decks and elaborate procedures. When the water is calm, the structure works swimmingly. However, enrollment shifts, or the state changes its funding formula, or a competitor launches a new program in four to six weeks that would take your institution an entire academic year to approve. The state of the water changes faster than the ship can turn, and the giant liner is still debating which way to steer while the speedboat is already gone.
The issue is not a lack of urgency or willingness to act. It is that our decision-making structures are often too bureaucratic, requiring multiple approvals, involving too many people and taking too long to respond when circumstances change at a breakneck pace. Even when leaders recognize the need to move quickly, the institution may not be designed to do so.
That is the actual change facing higher education, and interestingly, this is not a new concept. Scholarly attention to organizational agility in higher ed has grown exponentially since 2021, and the research suggests something more uncomfortable than “we just need an AI strategy.” It says most institutions have not invested the sweat equity required to build agility as an organizational muscle. They have built compliance, consensus and caution, then tried to layer urgency onto it whenever a crisis arrives. Agility doesn’t work that way given that it’s a muscle. A talented athlete, for example, doesn’t wait for the big game to start training.
Agility Isn’t Deployed but Built
According to the literature, agility in a college or university means having the ability to move both resource and process when circumstances change. Resource agility includes, but is not limited to, faculty, technology and infrastructure. Process agility includes, but is not limited to, curricula, pedagogy, assessment and research priorities. Having one without the other doesn’t help the cause—you need both. An institution can have faculty ready to experiment and a curriculum approval process that moves at a glacial pace. It can have flexible technology and ample resources paired with a governance structure that requires an Act of Congress to approve a new certificate or program. Either way, the capacity to change exists, but the system quietly precludes it from becoming action.
Curricula, arguably, is the clearest example. Colleges rarely lack ideas about what students need next, as faculty members see it shifting in their fields, employers signal it, and students—and their families—arrive already expecting it. Oftentimes, the gap is between recognizing the need and actually moving. A 2022 study by Shalini Menon, M. Suresh, and R. Raghu Raman, published in the Journal of Further and Higher Education, examined what drives curricular agility in higher education. They found that three factors were especially important: 1) who leads the curriculum process, 2) how governance is structured and 3) how much autonomy faculty have to act on what they see in their classrooms. Leadership, governance and autonomy determine whether a good idea becomes a course while it’s still relevant or a case study in what the institution missed.
This is why task forces built around a single disruption so rarely produce lasting change. They add a resource, a policy and a pilot, but they do not touch the foundation underneath. What matters is how fast a curriculum change clears governance, how quickly resources shift when a program stops meeting demand and how fast a policy reaches the people who must implement it. Layering AI onto an 18-month process doesn’t make the institution more agile. It just gives the 18-month process one more thing to process.
Agility Is the Infrastructure
Institutions that treat agility as a project will lose time and time again to institutions that treat it as infrastructure. When a project ends, infrastructure compounds. The leadership discussion needs to move from asking what its AI policy is to a more thought-provoking question: Do we have a systematic, repeatable way to reposition the institution when the environment around us shifts, and can we point to it? Not a strategic plan revisited every few years but a working capability assessed on a regular basis across key dimensions most institutions currently manage in silos:
- Culture: Does the institution reward calculated risk and fast iteration or the person who avoided a mistake by avoiding a decision?
- Systems: Can data move seamlessly from enrollment to academic affairs to the budget office without a significant lag? Can a curriculum change clear governance in a semester when the case is rather compelling?
- People: Are faculty and staff developed expecting their roles will evolve, or are job descriptions treated as static, permanent contracts with reality?
- Policies: Do policies specify outcomes and let units adapt the path, or do they specify the path and hope the outcome follows?
Institutions that assess themselves honestly against these dimensions on an ongoing basis will be in a better position to absorb the next disruption in months instead of years. Those that can’t will keep producing task forces. A task force is what you build when you don’t yet have a capability. It should be a starting point, not the solution we mistake for the capability we need.
Stop Waiting for Calm Water
Every institution reading this likely already has an AI committee, a strategic plan and a set of learning outcomes. What many of them are lacking is an honest audit of whether culture, systems, people and policies are pulling together or working against each other. That audit won’t generate a press release, but it’s the actual work, and higher education has spent long enough treating agility as something you invoke in a crisis rather than something you build in the calm before the storm.
The institutions that figure it out first will not be the ones with the best AI policy. However, they’ll be the ones who no longer need to ask what their AI policy should be because they are already reading the current before it shifts.