20-04-2025
The Secret To AI In Education: We Should All Be Frustrated Pragmatists
The Secret To AI In Education: Why We Should Be Frustrated Pragmatists
When it comes to AI in education, I've noticed two distinct camps beginning to form.
The first camp consists of teachers, school leaders and consultants who are focused on how AI can support the day-to-day work of educators. These are the pragmatists. The ones using AI to reduce teacher workload, automate repetitive tasks, streamline assessment and unlock extra time in increasingly stretched schedules. They see AI as a means to enhance the current system. In a global context of teacher shortages, low morale and burnout, their focus practical and, I would argue, noble.
The second camp sees things differently. For them, AI should not be a tool to help us do what we've always done, only faster or more efficiently. It's a transformative force. This group believes that the real potential of AI lies in its power to reimagine education. They are frustrated that education hasn't already changed and want AI to be the spark that ignites the revolution. They want to move beyond incremental improvements and into bold redesigns: new models of learning, new systems of assessment and new structures of schooling altogether. They are asking the big questions about relevance, purpose and the future of education.
Over the past couple of years, I've noticed a subtle but growing tension between these two perspectives. The second camp sometimes look down on the first, as if using AI to help with lesson planning or grading is somehow pedestrian, even counterproductive to real innovation. As if anything short of systemic transformation isn't worth talking about.
This, I believe, is a mistake.
Because the truth is, both perspectives are necessary. The answer isn't either/or. It's both/and.
I'm a frustrated pragmatist.
Back in 2022, I wrote a post referencing the three-box solution to innovation, a model developed by Professor Vijay Govindarajan from Dartmouth College's Tuck School of Business. I adapted it and applied it to education. I then expanded on it in my book The AI Classroom, and even more deeply in my latest book, Infinite Education. This framework offers one of the most helpful lenses through which to approach AI in education. A perspective that honours both present-day practicality and long-term reinvention.
At its core, the model divides innovation into two key categories: linear and non-linear.
Linear innovation is about optimizing and improving what already exists. It's evolutionary, not revolutionary. It enhances the current system. It can make schools run more efficiently, helping teachers manage workloads and freeing up time to focus on what matters most.
AI is proving to be incredibly effective in this space. It can support lesson planning, generate differentiated materials, summarise assessment data, automate feedback and assist with communication and reporting. These are not small upgrades. In many schools, they're game-changers.
As I work with educators around the world, I see firsthand the excitement, relief and even joy that comes from discovering AI tools that make their lives easier. These teachers aren't looking to overhaul the system, they're just trying to do their jobs well and get a bit of breathing room in the process. And when AI helps them achieve that, it's not 'false' innovation. It's real and meaningful progress.
Who are we to say that this isn't valid?
Who are we to dismiss these tools as unimportant or unimaginative? That kind of thinking is patronising and it's inaccurate.
Linear innovation may be the first step, but it's a vital one. Especially in a profession that's been pushed to its limits, finding new ways to support educators in their existing work is not a distraction from innovation. It's the foundation of it.
But we also can't afford to stop there.
Non-linear innovation doesn't seek to make the current system more efficient, but to question it. It asks: What if the way we've always done things no longer makes sense? What if there's a better model altogether?
This kind of thinking becomes crucial when new technologies arrive that don't just make old systems better, but have the potential to make them obsolete. AI is one of those technologies.
For decades, education has been shielded from true disruption. Schools have existed in protected ecosystems, relatively untouched by market forces or external competition. But with AI, that is changing. For the first time, we are seeing the emergence of powerful learning alternatives. ChatGPT apps that teach maths, AI-powered schools and fully online AI tutors.
This is the real disruptive force of AI. It's not just that it automates existing processes. It introduces competition on a level never seen before.
When students can access personalised, high-quality learning from anywhere, anytime and at little to no cost, schools must begin to ask:
As I recently said on the Joining the Dots podcast, AI isn't the ultimate goal in education; it's the lever for driving much-needed systemic reform. It's not the destination. It's the momentum builder. The accelerator. The great nudge we've needed to rethink education's purpose, design and delivery.
This is why I wrote Infinite Education. Not just to explore AI's classroom applications, but to provide a playbook for non-linear innovation. A guide for schools looking to evolve before they're forced to.
This dual innovation journey of linear and non-linear requires a new kind of leadership. Good leadership balances the linear and the non-linear. It manages the present while challenging its shelf life. It supports existing systems while creating new ones. It holds space for both security and disruption.
In education, the time has come for both managerial and heretical leaders. Managerial leaders keep the system functioning. They maintain stability, operations, safety and accountability. Their work is essential. But we also need heretical leaders. The ones who dare to imagine something different. The ones who ask uncomfortable questions. The ones who aren't afraid to disrupt their own assumptions. These leaders often face resistance, but they are the ones who move the system forward.
True educational innovation in the age of AI requires both types of leadership. Neither alone is enough.
So rather than choosing sides. Rather than dividing ourselves into camps, we must choose integration.
Let's build a culture that values both kinds of innovation:
Tools that help us survive today, and visions that help us invent tomorrow.
Let's honour the teachers using AI to reclaim time and energy and support those dreaming of systems not yet built.
Let's stop drawing lines and start building bridges between the now and the next, the practical and the possible, the performance engine and the innovation lab. Because if we can do that, we don't just adapt to AI. We lead with it.
That's the kind of education system the future needs.
