The tipping point happened quietly.
Microsoft embedded AI into Word and Excel. Google baked it into Search. Suddenly, most businesses were using AI whether they realized it or not.
We crossed the line from “AI-powered” being a differentiator to being background noise.
The term stopped meaning anything special because it started meaning everything. Every product description. Every pitch deck. Every tool now has AI built in or promises it soon will.
According to TrustRadius, AI became the most annoying business buzzword of 2024. Not because the technology isn’t real. Because the term is exhausted.
We’ve Seen This Movie Before
Remember when “digital marketing” was a thing?
There was a time when you had marketing and digital marketing. Two separate categories. Then email became standard. Websites became expected. Apps became normal.
Even traditional direct mail got digitally integrated with QR codes and landing page URLs.
The qualifier “digital” faded because doing marketing without digital components became unusual. The term didn’t disappear overnight. It just slowly lost its power to differentiate.
AI is following the same path.
The Attention Economy Collapses
When companies slap “AI-powered” on their products today, they’re using a buzzword to grab attention.
Pure attention economics.
But attention-grabbing only works until everyone’s grabbing. The buzz wears off when the whole room is buzzing.
McKinsey reports that 78% of organizations now use AI in at least one business function. When nearly four out of five companies are doing something, it stops being noteworthy.
The term becomes invisible through ubiquity.
The Jargon Trap Waiting Ahead
Here’s where it gets tricky.
AI is actually an umbrella term covering wildly different technologies. Machine learning. Predictive models. GenAI. Robotics. LLMs. The list keeps growing.
So as “AI” becomes meaningless, what replaces it?
Right now, we’re heading toward a paradox. The generic term loses power, but the replacement options are acronym soup. LLMs. MSPs. GenAI. RAG. Fine-tuning.
We’re escaping one problem and creating another.
Most people find the technical jargon more confusing than helpful. We’re trading empty buzzwords for impenetrable terminology.
What Actually Works
The solution isn’t finding a new sexy label to replace “AI.”
It’s refocusing on business outcomes.
Instead of “AI-powered marketing platform,” talk about lead generation. Instead of “AI analytics,” describe customer sentiment analysis. Instead of generic “AI tools,” specify content creation or data analysis capabilities.
People don’t buy technology labels. They buy solutions to specific problems.
When digital became ubiquitous, smart companies stopped saying “we do digital marketing” and started saying what they actually delivered. Traffic. Conversions. Engagement. Revenue.
The same shift is coming for AI.
The companies that move first will skip the jargon trap entirely. They’ll speak in outcomes while competitors are still arguing about whether to call it GenAI or LLM or something else.
We’re watching linguistic evolution happen in real time. The term “AI” is becoming what “digital” became. An assumed baseline rather than a differentiator.
The question isn’t whether this will happen.
It’s whether we’ll learn from the last cycle and focus on what matters. Not what we call the technology, but what it actually does.