They all followed a similar pattern (at least so far).

Last week, I was in France to attend a family funeral and had an opportunity to catch up with someone I had worked with 34 years ago.

Back then, we were trying to bring Minitel to the United States. For anyone who doesn’t remember it, Minitel was a combination of a small in-home terminal and an online service that existed before the web became mainstream. Messaging, chat, dating, directories, commerce, and information services all existed there in some form. Looking back, parts of it were surprisingly ahead of their time.

Later that week, I found myself at Station F in Paris, a startup campus built inside a converted train station. There were founders, investors, startups, and larger technology companies all mixed together.

I decided to walk there rather than take the metro, from where I was staying in the 2nd arrondissement to Station F in the 13th. Since it was one of the many (many) long holiday weekends in France during May, or what the French call “les ponts de mai,” things were quieter than usual.

Walking around, I kept thinking about how much had changed. Thirty-four years ago, we were taking our own shot at bringing Minitel to the US. Now I was standing in a place full of startups trying to build the next thing.

It made me realize that I’ve now had the chance to watch several major technology shifts happen up close: personal computers, client/server systems, the web, SaaS, cloud, mobile, and now AI.

At the time, every one of them felt completely different.

Looking back, I think they may have followed a surprisingly similar pattern.

Every Wave Feels Different While You’re Living Through It

Each shift changed something meaningful. Personal computers changed who had access to computing. The web changed how people and systems connected. Cloud changed how infrastructure was delivered. Mobile changed where computing happened. AI may change the relationship between people and software itself.

The technologies changed significantly each time, which is probably why each wave felt unique while living through it.

But the patterns surrounding them often looked more familiar than I realized at the time.

The Pattern Seems to Repeat

Something new becomes possible, and the early versions are usually rough. Some people become convinced it changes everything, while others become convinced it changes nothing.

Then money and excitement start pouring in. Expectations get ahead of reality. Sometimes bubbles form.

Eventually, reality catches up. Infrastructure matures. Real use cases emerge. Some ideas disappear while others survive and become much larger than anyone expected.

Parts of this should sound familiar because Gartner formalized pieces of it through the Hype Cycle. Roy Amara captured another part years ago with the observation that we tend to overestimate the impact of technology in the short term while underestimating it over longer periods.

I think the pattern goes beyond technology itself. It seems to happen as much around people and behavior as around technology.

They Don’t Just Repeat. They Build on Each Other.

One thing I hadn’t really appreciated while living through these shifts is that they rarely replace what came before them. They usually build on top of it.

Personal computers put computing in individuals’ hands. Networks and client/server systems connected those computers. The web standardized access and distribution. Cloud made infrastructure elastic and accessible. Mobile put computing into people’s pockets.

AI is now arriving on top of decades of software, infrastructure, connectivity, and digitized workflows.

A smartphone without cloud services, APIs, app stores, GPS, and broadband connectivity would have been a very different experience. AI without large amounts of data, scalable infrastructure, and software embedded throughout businesses would likely look very different, too.

We often talk about technology revolutions as replacement events. Looking back, many of them feel more like layers.

Each one creates conditions that make the next one possible.

Eventually, the Technology Disappears

This may sound backward, but the technologies that become most important often stop being talked about as technologies.

Nobody says “internet shopping” anymore. It’s just shopping. We don’t think about whether email runs in the cloud or whether ride sharing started on a smartphone.

The technology fades into the experience itself.

The computer scientist Mark Weiser described something similar in 1991, arguing that the most profound technologies are the ones that disappear into everyday life.

Looking back, that feels increasingly right.

You stop thinking about the technology because it simply becomes part of how things work.

Why I Think AI May Follow the Same Path

Years ago, when I worked in BI and analytics, we used to make the case that analytics should appear within the workflows and applications people already used rather than existing as standalone tools.

The argument was fairly simple. Most people do not wake up in the morning wanting analytics. They want to hire employees, approve budgets, close deals, build products, or solve problems.

Analytics becomes valuable when it appears inside the work itself.

I increasingly see AI through a similar lens.

Today, AI feels like its own category. You see it everywhere: AI-native companies, AI-native products, AI-native applications, AI-native PMs, AI copilots, and AI assistants.

That probably makes sense right now because we are still early.

It’s possible this one is genuinely different. Plenty of very smart people think AI breaks the pattern rather than follows it. Still, the pattern has repeated often enough that I’d bet on it rhyming again.

But as AI becomes more embedded, I suspect it eventually stops being “the thing.” Instead, it becomes part of the roles, workflows, and applications people already use.

People ultimately won’t care whether something is AI-enabled. In some cases, they may not even want to think about AI at all. They’ll care whether it helps them do something better, faster, or more effectively.

Back to Station F

Walking around Station F, I was in a place built around people building what they believe may become the next generation of products and companies.

Some of those ideas won’t survive. Some companies won’t survive. Some of today’s assumptions probably won’t survive either.

But if previous technology revolutions are any guide, parts of today’s AI wave will eventually become ordinary.

And maybe that’s when you know a technology revolution has really happened.

Not when everyone is talking about it.

When nobody needs to anymore.

For those who are curious, here is a link to the Station F website: stationf.co.