What Worries Me the Most About the Future of Education and AI

After delivering keynote addresses on the future of education and AI to independent school leaders in six major cities across three continents this past year, I’m returning home with a lingering concern:

Many — if not most — of the most innovative schools I know are not treating AI as the existential force it is rapidly becoming.

They’re intrigued, maybe even curious, but not yet moved to act in ways that match the scale of change ahead.

This is a problem. And yes, that’s what worries me most.

Let’s get something clear: this is not about the latest shiny tool. It’s about the tectonic shift already underway in how knowledge is created, accessed, and applied — and whether schools will adapt fast enough to remain relevant.

In other words, I am not worried about AI. I’m worried about the attitude of our collective industry.

What is Artificial Intelligence?
Artificial Intelligence (AI) is the field of computer science focused on building systems capable of performing tasks that traditionally require human intelligence — things like learning, reasoning, problem-solving, and understanding language. Today’s most familiar AI tools include virtual assistants like Siri or Alexa, and powerful large language models (LLMs) like ChatGPT that can generate human-like responses across a wide range of subjects.

These systems learn by ingesting vast datasets and recognizing patterns — but they’re not just parroting back information. Increasingly, AI tools can analyze, synthesize, and create entirely new insights. That’s a game-changer for education.

A Historical Lens: The Four Ages of Education
To fully grasp the significance of what AI is bringing to the table, we need to zoom out. Education, as an industry, has evolved through four major “ages,” each defined by the tools and values of the time:

1. The Knowledge Age (1950s–1990s):
   In this era, the core business of education was knowledge. It was a print-based, pre-digital era where content was scarce and controlled. Mastery meant memorization, and assessments were standardized and summative. Many of today’s school structures and accreditation systems still rest on this foundation.
2. The Skills Age (1990s–Early 2000s):
   In this era, knowledge became democratized, and we could no longer charge for simple distribution. There had to be a value-added. It was the rise of the digital world — think MIT iTunes and the early web — democratized access to knowledge. Schools began emphasizing skills and competencies over rote content.
3. The Adaptive/Assisted Learning Age (Present):
   This is our current reality. We are now living in an era where students can access, synthesize, and begin creating new understanding through AI-assisted platforms. Learning becomes personalized, contextual, and increasingly fluid.
4. The Generative Age (Coming Fast):
   This is where we are going — quickly. This is where AI doesn’t just help us understand the world — it begins to generate new knowledge. Concepts, designs, and ideas once imagined solely by human minds are now being co-created by machines. This is the frontier for which we must prepare.

Understanding where we are on this continuum is essential. Too many schools are operating with models and mindsets rooted in the Knowledge or early Skills Ages, unaware that the ground has shifted beneath them.

What Independent Schools Are Missing
In my travels across the globe, I’ve discovered something surprising: even schools that consider themselves forward-thinking often see AI as a tool to be added, rather than a transformation to be navigated. They’re building AI task forces, drafting responsible use policies, and experimenting in isolated classrooms — but many are failing to recognize that this isn’t a curricular innovation. It’s a systemic one.

Fewer than 5% of North American independent schools had invested in any kind of meaningful AI integration before 2023. Meanwhile, AI is now mentioned in nearly every strategic plan we touch — usually with tentative language and limited urgency. It’s where wellness was five years ago, or DEI a decade ago. There’s interest, but not always understanding.

A Simple Framework: The Three Stages of AI in Learning
If we overlay AI’s evolution on top of this educational timeline, we get another useful way to think about how far we’ve come — and how far we have to go:

1. Retrieval (1.0): We used the internet to find knowledge — Google search, Wikipedia, etc. This was the first 25 years of the internet.
2. Synthesis and Analysis (2.0): Tools like ChatGPT helped us analyze and synthesize that knowledge. This is where we sit today.
3. Generative (3.0): AI is now beginning to create new knowledge — drafting articles, composing music, generating research hypotheses. This presents both a staggering opportunity and a profound challenge to traditional education. This is where we are going — literally tomorrow.

Three Paths Forward
To respond meaningfully to the rise of AI, schools must move through a continuum of awareness and action:

1. Explorers: Just beginning to ask the right questions. What is AI? Where does it fit?
2. Evolvers: Actively experimenting and integrating AI tools into curriculum and operations.
3. Trailblazers: Reimagining the very purpose and process of school in light of what AI makes possible.

Only a small fraction of schools have reached the third stage — but that’s where the future lies.

A Call to Action
The shift toward generative AI represents a new educational era — one that calls us to rethink what it means to teach, to learn, and to know. If independent schools don’t take this seriously — don’t disrupt, adapt, and evolve — we risk being preserved in amber while the world moves on.

This is not about adopting a trendy tool. It’s about preserving the relevance and vitality of our schools. The window for innovation is open, but it is closing as you read this.