AI as Infrastructure: The Quiet Shift
AI is making the same transition electricity made a century ago
Key Takeaways
- Transformative technologies follow a pattern: novelty → tool → infrastructure → invisible utility
- AI is currently in the “tool to infrastructure” transition
- The sign that a technology has matured is that people stop noticing it
- The real impact of AI will be felt when it disappears into the background
In the early 1880s, electricity was a spectacle. People paid admission to see it. Cities held public demonstrations of electric streetlights, and crowds gathered to watch them glow. Thomas Edison staged elaborate shows at his Menlo Park laboratory. Electricity was a thing — a novelty, a wonder, a topic of conversation.
Nobody talks about electricity anymore. Not because it stopped being important, but because it became so important that it disappeared. It became infrastructure. You flip a switch and the lights come on. You don’t think about the grid, the generation plants, the transmission lines, the decades of engineering that make it all work. You think about what the light lets you do.
AI is in the early stages of the same transition. And most of the conversation about it hasn’t caught up.
The Pattern
Every transformative technology follows roughly the same arc. First it’s a novelty — something that exists in labs, at conferences, in breathless magazine articles. Then it becomes a tool — something specific people use for specific tasks, still conspicuous, still commented on. Then it becomes infrastructure — embedded in systems, assumed rather than remarked upon. And finally it becomes invisible — so woven into daily life that its absence, not its presence, is what would be remarkable.
The internet followed this path. So did cloud computing. So did GPS. Each one went through a period of intense public fascination, followed by widespread adoption, followed by quiet ubiquity. When was the last time you thought about the fact that your phone knows exactly where you are on the planet, at all times, using a constellation of satellites in orbit?
Where AI Is Now
We’re somewhere between “tool” and “infrastructure.” AI is no longer just a novelty — millions of people use it for work every day. But it’s not yet invisible. People still remark on it, debate it, write think pieces about it. The tools still feel like tools rather than capabilities that are simply present.
You can see the transition happening in real time. Email clients that draft responses for you. Search engines that synthesize answers instead of listing links. Code editors that complete your functions. Photo apps that sort your images by the people in them. Each of these is AI, but increasingly, users don’t think of them that way. They just think of them as features.
That’s the tell. When people stop saying “the AI did this” and start saying “I did this” — even though AI was involved at every step — the transition to infrastructure is underway.
What Changes When AI Becomes Infrastructure
When electricity became infrastructure, the interesting question stopped being “what can electricity do?” and became “what can you build when electricity is available everywhere?” The answers — radio, television, refrigeration, computing — were mostly things nobody predicted.
The same shift is beginning with AI. The interesting question is no longer “can AI write an essay?” or “can AI pass a bar exam?” Those are spectacle questions — the equivalent of watching electric streetlights glow. The interesting question is: what becomes possible when intelligence is a commodity that any piece of software can access, at negligible cost, instantly?
We don’t know the full answer yet. We’re too early. But we can see the shape of it forming. Software that adapts to individual users rather than forcing users to adapt to it. Information systems that synthesize rather than merely store. Interfaces that understand intent rather than requiring precise commands.
The Implication for Individuals
If AI is becoming infrastructure, then the strategic response isn’t to become an “AI expert.” It’s to become very good at the things that infrastructure enables. Nobody built a career as an “electricity expert” — they built careers in the industries that electricity made possible.
The people who will benefit most from AI-as-infrastructure are the ones with deep domain knowledge, clear thinking, and the ability to direct tools toward meaningful work. The premium isn’t on knowing how AI works under the hood. It’s on knowing what to build with it.
This is why I keep coming back to the same advice: develop a daily practice, build fluency with the tools, but don’t mistake fluency with the tools for fluency with the work. The tools are the electricity. The work is what you plug in.
The Quiet Part
The most important phase of any technology’s life cycle is the boring phase — after the hype, after the backlash to the hype, after the backlash to the backlash. It’s the phase where people stop arguing about the technology and start building quietly with it. That’s where the real value compounds.
AI is entering that phase for early adopters right now. The headlines will continue — there will be new models, new capabilities, new controversies — but underneath the noise, a growing number of people are simply using AI the way they use any other infrastructure: without thinking about it, to get their actual work done.
That’s not a story anyone can sell a subscription to. But it’s the story that matters.
This guide expands on two pieces I published on LinkedIn: AI Is Starting to Behave Like Infrastructure and Something Important Has Changed in AI. Both caught the attention of people who are past the hype cycle and thinking seriously about what comes next.
I’ve been watching technology transitions for a long time — first in emergency services, where I saw AI arrive in a Michigan 911 center, and now more broadly through my writing on Medium and LinkedIn. The pattern is consistent: the most important phase of any new technology is the phase where people stop talking about it and start building with it.
