Every technological revolution creates two races. The first is a race for efficiency: who can adopt the new tool fastest, automate the most work, and extract immediate gains. The second is a race for imagination: who can see what the technology makes possible that was never possible before.
Artificial intelligence (AI) has clearly begun the first race. But history shows that, without exception, the companies remembered, admired, and rewarded over decades are not the ones that win the first race. They’re the ones that win the second.
Despite the breathless headlines, we’re not yet living in AI’s innovation era. We’re still in its efficiency wave: organizations everywhere are using AI to automate tasks, cut down on costs, and remove friction from existing processes. Necessary, yes. Transformative, not yet.
What comes next is both predictable and unforgiving. The organizations that dominate the second wave will not be those that deploy AI most aggressively, but those that pair it with a scarce and decisive human capability: Original Intelligence, or the ability to expand the idea space beyond what AI itself is likely to produce. That capability will define the next generation of great companies riding the AI wave.
A Predictable Pattern We Keep Forgetting
When a new technology arrives, it’s almost always used first to replicate what already exists. Not because leaders lack imagination, but because replication feels safe. It delivers immediate ROI. It fits existing metrics. It doesn’t require rethinking who creates value. Only later does the deeper opportunity emerge: the chance to do things that were previously impossible, unscalable, or even unthinkable.
The winners of every major technology shift understand this distinction early. The losers mistake early efficiency gains for lasting advantage. AI is now at that exact inflection point.
History makes this pattern unmistakable. Look no further than how earlier breakthrough technologies moved from efficiency to imagination—and how the winners emerged only in the second phase.
Film: When Cameras Did More Than Just Record
The early history of film offers a useful parallel. When motion picture cameras first appeared, they were used in the most literal way possible: to film theater. Early movies were static. Actors performed as if on stage. Cameras didn’t move. Scenes didn’t cut. The technology improved distribution, not storytelling.
This was the efficiency wave of film. Plays could now reach more people, more cheaply. The innovation wave arrived only when filmmakers stopped asking, “How do we record plays better?” and started asking a more dangerous question: “What can only be done with a camera?”
That shift unlocked close-ups and emotional intimacy, montage and time compression, visual metaphor, non-linear narrative, and entirely new genres and business models. Hollywood was not built by people who filmed plays more efficiently. It was built by people who reimagined storytelling itself.
Electricity: When Plugging In Wasn’t Enough
The same pattern appeared with electricity. When electricity entered factories, it was first used to replace steam engines one-for-one. The same layouts. The same workflows. The same hierarchies. Factories became cleaner and more reliable, but not more innovative. This was electricity’s efficiency wave.
The real breakthrough came only when leaders realized that electricity did not merely power machines; it enabled entirely new organizational designs. Decentralized motors, flexible layouts, assembly lines, mass production, and mass customization followed. The factories that won were not the ones that electrified fastest, but the ones that rethought work itself.
The Internet: When Digital Brochures Were Just the Beginning
The internet followed the same arc. In the 1990s, most companies used the internet as a publishing tool. Websites were digital brochures. E-commerce was an afterthought. The business model stayed the same. This was the efficiency wave of the internet.
The innovation wave came when companies began asking a different question: what behaviors become possible when everything is networked? That question gave rise to search as an organizing principle, platforms instead of pipelines, social graphs instead of audiences, and trust-based marketplaces instead of ownership. These companies did not simply adopt the internet. They reimagined value creation because the internet existed.
AI is now following the same path as these three transformational events. Today, it’s largely being used to replicate existing work more efficiently: writing emails, generating decks, summarizing documents, accelerating analysis, and polishing outputs. Like filmed theater, electrified steam engines, and digital brochures, these uses are useful and impressive, but fundamentally transitional. They improve speed and scale without changing the underlying logic of how value is created.
Original Intelligence: The New Scarcity in an AI-Saturated World
AI has now crossed a threshold where efficiency is no longer the constraint. Access to models, tools, and capabilities is rapidly becoming universal. What remains scarce is the ability to expand the idea space beyond AI’s probabilistic center.
This scarcity is made worse, not better, by AI itself. Large language models (LLMs) are designed to predict what is most likely, not what is most different. At scale, this produces homogenization. What looks novel in isolation becomes repetitive in aggregate. In an AI-saturated world, efficiency is table stakes, polish is commoditized, and sameness is the default. Original Intelligence becomes the only durable advantage.
Yet most organizations are still treating AI adoption as a tooling problem. They ask which model to use, which workflows to automate, and how much time can be saved. History suggests this is exactly backwards. The real question is not how powerful the tool is, but who knows how to use it to create something that did not exist before. The winners of the second AI wave will be the organizations that can identify people who expand the idea space, design teams that combine AI efficiency with human originality, and measure and protect differentiation in a world of AI sameness. This is not a creativity problem. It is a value-creation problem.
The Second Wave Starts Now
The first wave of AI belongs to everyone. The second wave will belong to the original thinkers. History does not reward those who merely adopt transformative technologies. It rewards those who understand what those technologies make possible and have the human capacity to act on that understanding. AI will not eliminate human value. It will expose who has it. The next generation of great companies will not be built by those who use AI most efficiently, but by those who pair AI with the rarest asset in the modern economy: Original Intelligence.
Every technological revolution eventually asks the same question of its leaders: are you using this technology to go faster, or to go somewhere new? In the age of AI, efficiency is easy. Originality is everything. The second wave has already begun.
Photo by Joey Huang on Unsplash
