Just as I stepped into the world of academia at Dartmouth, the tech landscape was jolted by the arrival of ChatGPT. Little did I know, my career shift from consulting to teaching would coincide with one of the most disruptive innovations of our time. But here's where it gets fascinating: disruption is never a neat process—it’s messy, unpredictable, and always comes with a twist. Let me take you through this journey, blending my personal experience with historical insights that reveal how AI might reshape industries in ways we’re only beginning to grasp.
In July 2022, I traded my consulting role for a teaching position, seeking a change after nearly two decades of navigating complex client challenges. Teaching, I thought, would offer a calmer pace and a chance to focus on what I found intrinsically rewarding. But just months later, in November 2022, OpenAI unveiled ChatGPT, a tool that quickly demonstrated AI’s potential to upend not just education, but consulting and countless other fields. This timing wasn’t just coincidental—it underscored the unpredictability of disruptive change.
Over the past three years, I’ve immersed myself in AI through a course I developed, ‘AI and Consultative Decision Making,’ while also writing Epic Disruptions, a book that explores how innovations like gunpowder and disposable diapers transformed the world. One recurring theme emerged: disruption is predictably unpredictable. While broad patterns exist, the involvement of humans and complex systems ensures that every disruptive story takes unexpected turns.
As the saying goes, history doesn’t repeat itself, but it often rhymes. Here are five historical lessons that shed light on how AI might—or might not—drive epic disruptive change:
1. Disruption Often Starts in Unexpected Places
Consider the transistor, developed in the 1940s by Bell Labs researchers Walter Bradeen, John Bardeen, and William Shockley. Initially intended to replace vacuum tubes in communications networks, early transistors were unreliable and required system overhauls. Yet, their first commercial success wasn’t in telecom—it was in hearing aids. Why? Transistors were small, cool, and perfect for a market where vacuum tubes were bulky, hot, and costly. This unexpected application fueled further innovation, eventually paving the way for modern computing and communications.
Similarly, while we focus on AI’s impact in advanced markets like the U.S. or Western Europe, ChatGPT’s rapid growth is being driven by emerging markets. In regions with limited access to healthcare and education, users aren’t comparing AI to skilled professionals—they’re asking, Is AI better than nothing? History suggests that emerging markets are fertile ground for spotting disruptive change early.
2. The Secret Sauce of Disruption is a Unique Business Model
McDonald’s wasn’t always a global powerhouse. Its rise began in 1948 with the ‘Speedee Service System,’ which standardized food production. But the real magic happened when Ray Kroc and his team created a unique franchising model, and later, Heny S. Sonneborn devised a real estate strategy that turned McDonald’s into a profit machine. This unique business model—not just the product—was the key to its success.
Today, AI labs like OpenAI and Anthropic are following conventional tech company models. But here’s the controversial part: if they don’t develop truly unique ways to create, capture, and deliver value, history suggests their standalone existence might be short-lived. Will they innovate their business models, or become acquisitions for tech giants like Amazon or Microsoft?
3. Disruption is Always Messy in the Middle
The rise of automobiles in the 1920s illustrates this perfectly. While Henry Ford’s Model T brought cars to the masses, cities weren’t designed for them. The result? Chaos, accidents, and public outrage. Cartoons depicted cars as death machines, and cities struggled to adapt. It took decades of technological, regulatory, and cultural changes—traffic signals, driver’s licenses, and right-of-way norms—to stabilize the automotive revolution.
AI is in its messy middle right now. Calls to minimize regulation might seem appealing, but they risk prolonging this chaotic phase and increasing harm. Futurists like Bob Johansen and Jamais Cascio propose a ‘bounce rope’ metaphor: firm boundaries with some flexibility, allowing innovation while preventing disaster. Is this the right approach, or are we underestimating the risks?
4. There’s Often a Twist in the Story
The printing press is a classic example. Johannes Gutenberg’s invention was initially embraced by the Catholic Church for standardizing religious texts. But it also empowered figures like Martin Luther to challenge the Church’s authority. The printing press became a double-edged sword, benefiting some while threatening others.
Today, consulting firms are profiting from AI, but what if clients start using AI to bypass consultants altogether? Or if AI diminishes the unique skills that make consultants valuable? Could AI become to consulting what the printing press was to the Church? This question is worth pondering—and debating.
5. It’s All About the People
Singapore’s DBS Bank transformed from a local laggard to a digital leader by 2025, not just through technology but by changing employee behavior. As Paul Cobban, DBS’s former Chief Data and Transformation Officer, put it, “Nothing changes unless people’s behavior changes.” AI adoption isn’t a tech problem—it’s a cultural and sociological one. Accenture’s Jim Wilson estimates that for every dollar spent on technology, six should be spent on managing human change.
As I reflect on the research behind Epic Disruptions, one lesson stands out: history offers a lens to navigate our complex present. AI will undoubtedly break some patterns, but the past guides us on where—and how—to look for what’s next. What do you think? Will AI follow these historical lessons, or will it chart an entirely new course? Share your thoughts in the comments—let’s spark a conversation!
