The hidden cost of AI: Trading long-term resilience for short-term efficiency

In the 18th century, weaving fabric was an art. Thread by thread, artisans created intricate patterns by hand — a slow, painstaking process requiring deep knowledge passed down through generations. Then, in 1804, a French merchant disrupted everything. His invention, the Jacquard machine, could weave complex patterns automatically using punch cards — much like an early form of computer programming. The impact was immediate: fabric became faster and cheaper to produce, and people feared that traditional weaving skills would vanish forever.

But they didn’t.

The finest fabric makers in France and Italy adapted. They integrated automation where it made sense, but they also safeguarded what made their craft irreplaceable — the human touch. Even today, high-end fashion houses rely on techniques that remain painstakingly manual, because efficiency alone doesn’t create value. Taste does. This pattern — technological disruption followed by adaptation — has played out throughout history. And yet, with every major breakthrough, we ask the same question: What if this time is different?

Now, we stand at the cusp of another transformation. AI is the latest in a long lineage of efficiency-maximizing tools. It promises to make research instantaneous, strip away uncertainty, and optimize everything from hiring to investment analysis. But for all the gains in speed and precision, we rarely stop to ask: What are we losing in return? Because there is no such thing as a free lunch.

The tradeoff: Efficiency vs. resilience

Automation doesn’t just make us more efficient — it makes us more dependent. And over time, dependence erodes resilience. At first, automation feels like an unqualified win. It removes friction, accelerates decision-making, and eliminates tedious tasks. But the more we offload to machines, the more we risk losing the skills, judgment, and adaptability that make us capable in the first place.

GPS dulled our sense of direction. Spellcheck chipped away at our ability to spell. In long-term investing, my business, AI can generate rapid-fire summaries of earnings calls. But it can’t walk a factory floor with a CEO, test a company’s latest product, or read the hesitation in a CFO’s eyes. In other words, research may become cheap — but the value of personal conviction will only go up.

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We’re already seeing the consequences of AI over-reliance play out in real time. Our feeds are flooded with AI-generated slop — soulless, low-effort content that looks convincing but says nothing. AI-written news articles, generic blog posts, and formulaic marketing copy are multiplying by the day. The result? A world optimized for speed, but stripped of depth.

Efficiency alone doesn’t create knowledge. It doesn’t foster insight. And it certainly doesn’t lead to wisdom. Nor does it build resilience — because resilience isn’t the product of perfect systems. It comes from the ability to adapt when those systems inevitably fail. And that’s precisely what automation threatens to erode. The real challenge isn’t just how to use AI. It’s how to harness it without surrendering the very skills that make us adaptable in the first place.

The fallacy of perfect information

A few weeks ago, I was at a dinner where someone made a bold claim. He said something like, “AI will make the world more predictable.” I had to laugh. It reminded me of a conversation I once had with a veteran entrepreneur who had lived through the early days of the internet. In the 1990s, many believed that unlimited access to information would create a smarter, more rational society. With search engines indexing human knowledge and algorithms optimizing decisions, inefficiencies would disappear and society would improve. Right? Er, not exactly.

More information didn’t lead to better decisions — it just made them faster and more reactive. We became inundated with data — but not necessarily wiser. This pattern repeats throughout history. When the telegraph first allowed stock prices and news to travel instantly, people assumed it would lead to more rational markets. When supercomputers arrived, businesses believed they could mathematically outthink the competition. And now, with AI compressing weeks of research into seconds, the assumption is that the world will become more precise, more scientific, more efficient.

But here’s the thing: the most meaningful decisions — whether in business, art, leadership, or life — have never been purely analytical. They’ve always been a blend of logic and intuition, of data and human insight. The question isn’t whether AI can make us more efficient. It’s whether efficiency actually leads to better decisions — or just the illusion of control.

Why efficiency doesn’t create enduring ideas

This is more than an abstract question for me. Over the last year, I’ve been researching some of the world’s oldest companies. And one thing is clear: the institutions that have endured and outlasted for centuries weren’t built on efficiency alone. They were built on something much harder to replicate — personal taste.

Tsuen Tea, a Japanese tea house in continuous operation for over 850 years, has survived countless technological shifts. Faster, cheaper ways of producing tea have come and gone, yet the company endures because it understands that the essence of what it provides — ritual, knowledge, experience — cannot be automated. 

Zildjian, the centuries-old cymbal maker, exists in a world where machines can mass-produce percussion instruments at a fraction of the cost. And yet, the company still relies on closely guarded metallurgy techniques, passed down through generations. Could AI optimize aspects of its production? Certainly. But the sound — the intangible essence of what makes a Zildjian cymbal unique — remains deeply human. 

The same applies to creative work. AI can generate text, images, and music, but it can’t create art that carries lived experience, emotional weight, or personal conviction. It can optimize an advertising campaign, but it can’t craft a brand that resonates on a soul-deep level. And this is the real tradeoff we now face. For all the efficiencies we gain, we lose something in return: resilience.

The risk of outsourcing judgment

AI makes the world feel more scientific than ever. It can generate business strategies, write persuasive emails, and surface patterns invisible to human analysis. But the most important decisions — the ones that lead to breakthroughs, revolutions, and paradigm shifts — are rarely the result of pure data analysis.

Some of the best ideas in history looked irrational at first. They required deep research, yes — but more importantly, they required taste. (And perhaps a bit of luck.)

Taste is an underrated concept in a world obsessed with efficiency. It’s the ability to recognize something valuable before the numbers prove it. The ability to see beyond spreadsheets and sentiment analysis and understand how an idea actually fits into the world. If everyone has access to the same AI-generated insights, the only thing that remains scarce is independent thinking. And that is precisely where the edge lies.

The role of AI in a world where judgment still wins

None of this is an argument against AI. It’s an argument for knowing what not to outsource to our robot overlords. AI is a tool. A powerful one. But it is not a substitute for intuition, nor a replacement for deep thinking. The institutions and ideas that endure the longest are those that understand what to hold onto even as the world around them changes.

History tells us that efficiency alone has never been the key to longevity. The individuals and businesses that outlast and endure recognize that while technology evolves, the fundamental drivers of value do not. Conviction. Taste. Judgment. These are the real competitive advantages. And no matter how powerful AI becomes, they always will be.