At the turn of the millennium, we witnessed the Dotcom bubble.

Investors were pouring billions into Internet startups with little more than a “.com” in their name. Valuations skyrocketed, expectations exploded — until reality caught up. 💥
The bubble burst.

Hundreds of companies disappeared.

And yet — the Internet itself didn’t just survive. It thrived.
Two decades later, the digital economy is worth a multiple of everything that was ever invested back then.
Today, I see clear parallels with Generative AI.

The hype is extraordinary.

Hundreds of billions are being spent on data centers, GPUs, and model training — in some cases on a scale that no realistic business model could justify.

Even major players are funding each other’s growth in circular systems that feel uncomfortably similar to 2000.
But here’s the catch:

Just because we’re in a bubble doesn’t mean the underlying technology isn’t real.

AI will absolutely change how we live and work — the question is simply how fast and at what cost.
Humans have always been bad at judging innovation:

- ⚡ We overestimate it in the short term — expecting overnight transformation.
- ⚙️ And we underestimate it in the long term — missing the quiet revolutions that follow.
Every breakthrough — from electricity to the Internet — has gone through the same “Hype → Crash → Plateau” pattern.
So common, in fact, that it has a name: Amara’s Law, or the Hype Cycle.
And AI might currently be climbing toward its (first) big fall.
From my own experience, I can say: the impact of AI is already tangible tough.

I already see AI reshaping how we collaborate, communicate, and even how we think. — even this post was crafted with the help of (precisely directed) AI.


At the same time at my agency, we evaluate every use case critically.

We deploy AI only where it delivers measurable, sustainable value.

Because long after the hype has faded, the real differentiator will not be who used AI first — but who used it wisely.
Let’s not get blinded by the noise.

Let’s build the systems, ethics, and human judgment that make AI truly valuable — after the bubble bursts.
Where would you place AI on the curve today? Are you building for the hype — or for what comes after?