A few years ago, I read Range by David Epstein and found it compelling. The core idea — that generalists thrive in complex, unpredictable environments — resonated with me. I’ve spent my career at the intersection of business strategy, media, and technology, moving across disciplines and industries. Back then, the book felt like a validation of the value of broad experience.

Lately, I’ve been thinking about it in a new way. As I’ve gone deeper into AI, I’ve started to wonder: If AI can instantly generate work that used to take years of skill-building, what happens to those of us who built careers by developing expertise across multiple domains? Do generalists become less valuable — or more?

At the same time, I’ve also been revisiting The Tipping Point and Revenge of the Tipping Point by Malcolm Gladwell. And I have a hunch that there’s an intersection here.

A Fourth Grader, GarageBand, and the AI Effect

Two years ago, when my son was in fourth grade, he took an after-school music class where the iPad, loaded with Apple’s GarageBand app, was the primary instrument. It wasn’t a free-for-all — he wasn’t just playing with the iPad on his own. A musician taught the class, guiding the students as they layered beats, arranged instruments, and built full tracks using pre-programmed snippets and automated tools.

It was fascinating to watch. My son wasn’t a complete novice to music — our house has always had instruments, and I had tried (with limited success) to get him to study drums, guitar, and piano. He had a natural sense of rhythm and an appetite for music, but structured lessons never quite stuck.

But with GarageBand, everything changed. He was creating full compositions, experimenting in ways he never had before. Without years of formal training, without needing to master an instrument, he was producing music that sounded real, structured, and intentional.

The memory of that experience resurfaced as I revisited Range, because it struck me: This is exactly what AI is doing in the professional world.

AI is making it possible to produce high-quality work — financial models, legal summaries, business strategies — without spending years developing the expertise. My son didn’t need to learn music theory to create something that sounded great. In the same way, AI is allowing people (and businesses) to bypass traditional learning curves in countless industries.

That’s a big shift. And if execution becomes a commodity, what does that mean for those of us who have spent years developing expertise across different fields?

The Strengths of AI vs. The Strengths of Humans

This is where things get interesting. AI is not a replacement for human capability — it’s a counterpart. And when you look at it that way, the distinction between generalists and specialists becomes even more important.

AI excels at:

• Encyclopedic memory — It can store and recall vast amounts of information instantly, pulling from endless sources without forgetting a single detail.
• Tactical execution at scale — AI can run multiple experiments, iterate solutions, and optimize strategies far faster than any human.
• Mass computation — It can process complex data sets, recognize explicit patterns, and generate models in ways no human brain could match.

But AI struggles with:

• Strategy — AI can optimize for efficiency, but it lacks the ability to set long-term, context-driven goals. It follows rules but doesn’t define the game.
• Intuition — Humans can make instinctive leaps, detecting opportunities and risks that don’t yet have enough data to be obvious.
• Opaque pattern recognition — AI finds explicit patterns in structured data, but humans recognize hidden patterns — trends emerging in culture, shifts in sentiment, inflection points before they tip.

This dynamic creates an opportunity. If AI is an execution machine, then the most valuable professionals will be those who can direct it toward the right problems, provide context, and interpret results in a way that leads to action.

The Generalist as an Industry Specialist

This is where generalists, particularly those with deep industry experience, become indispensable.

People often think of generalists as professionals who move between industries, dabbling in different disciplines. But there’s another kind of generalist: the industry specialist who has worked across legal, finance, operations, and strategy — someone with a broad skill set but deep industry expertise.

AI can automate technical tasks, but it lacks industry intuition. It doesn’t understand the politics of a boardroom, the hidden risks in a contract negotiation, or the unspoken dynamics of an M&A deal. AI can process vast amounts of information, but it needs the right prompts, the right framing, the right context — which only comes from experience.

The most valuable professionals in an AI-driven world won’t just be those who execute tasks efficiently. They’ll be the ones who know their industry so well that they can use AI as an extension of their expertise — guiding it, shaping it, and leveraging it in ways that others can’t.

The New Tipping Point

In Revenge of the Tipping Point, Gladwell argues that today’s world is more fragmented, making tipping points harder to reach. AI contributes to this — it spreads information at scale but doesn’t distinguish between noise and true insight. Generalists, who can navigate ambiguity, synthesize diverse ideas, and provide meaningful context, are more valuable than ever.

So maybe that’s the key. If AI is the GarageBand of the professional world — giving people access to tools that bypass traditional expertise — then the value shifts from doing to thinking. From execution to judgment. From specialization to synthesis.

And if generalists with deep industry knowledge are the ones who can feed AI with the right insights, frame problems effectively, and interpret AI’s outputs in a strategic way, then they become the essential bridge between raw automation and real business impact.

What’s Next?

I don’t think we’ve reached a clear conclusion yet — AI is still evolving, and so is its impact on careers. But I keep coming back to this: If AI levels the playing field on execution, then what truly differentiates people?

Maybe it’s range. Maybe it’s the ability to see beyond AI’s immediate outputs and understand the broader context. Maybe it’s about using AI as a tool, rather than being replaced by it.

For those of us who have built careers moving between industries, solving problems, and adapting to change, AI isn’t a threat — it’s an amplifier. And if The Tipping Point taught us anything, it’s that the people who can recognize and shape trends before they hit critical mass are the ones who drive real change.

So the question I’m sitting with is this: How do generalists actively shape AI’s impact, rather than just reacting to it?