Imagine landing on a website and, before you even search, it knows what you want. It shows you products, content, or videos that feel tailored to your taste. It feels intuitive, even a little creepy. But it’s not magic. That’s AI. And it’s been quietly working in the background for over two decades.
Before large language models, before “smart” assistants and chatbots, websites were already using AI to make decisions for users. It started with recommendation systems, the kind that suggest products, videos, or posts based on what you and others clicked before.
One of the earliest was GroupLens, launched in the 1990s by researchers at the University of Minnesota. It filtered Usenet news content based on user ratings. Primitive by today’s standards, but revolutionary for its time.
Fast forward to the early 2000s, and Amazon was using collaborative filtering to suggest “customers who bought this also bought…” That one line transformed eCommerce forever. Amazon now attributes up to 35% of its revenue to its recommendation engine.
Netflix followed with a similar strategy, launching one of the most powerful predictive engines in the entertainment world. Today, over 80% of what’s watched on Netflix is influenced by its AI suggestions.
These systems were the quiet precursors to modern machine learning, tracking behavior, identifying patterns, and personalizing experience at scale.
These early AI tools weren’t designed to wow users. They were designed to reduce friction, increase relevance, and boost retention. And they worked:
We didn’t call it AI then, but it was. It used logic, prediction, and adaptation to make digital experiences feel more human.
Those first systems laid the groundwork for everything we now associate with “AI”: personalization, prediction, and proactive interfaces.
Spotify’s “Discover Weekly”? A sophisticated evolution of collaborative filtering.
Google’s Search auto-complete? Pattern recognition trained on billions of entries.
Instagram’s Explore tab? A mix of behavior modeling and deep learning.
Even tools like ChatGPT, Shopify Magic, and Canva’s AI design assistant are built on the same philosophy: understand the user, predict their intent, serve what they need before they ask.
We’re not entering a new era, we’re extending one.
The smartest websites today aren’t waiting for AI to “arrive.” They’re building on what’s already working:
Personalization isn’t a feature anymore. It’s the expectation.
Today’s buzzwords, AI, machine learning, personalization, aren’t new concepts. They’re upgrades to an old promise: make digital more human.
If you’re building websites, brands, or experiences, remember this: the most powerful AI doesn’t shout. It whispers, through relevance, flow, and frictionless discovery. And it’s been doing that for years.
I don’t just make things look good. I make them work.Websites, brands, films and stories built to connect and built to last.
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