I’ve been in SEO since 1999.
Over time, that work extended into teaching—breaking down technical SEO concepts like manual audits into structured frameworks used by thousands of practitioners (
see course).
So when I hear
“AI is brand new”
I see it differently.
AI didn’t suddenly appear.
It became visible.
Long before ChatGPT, search was already powered by machine learning.
RankBrain (2015) — influencing rankings.
BERT (2019) — understanding context at scale.
Spam systems — AI-driven.
Search intent classification — machine learning.
If you’ve been doing serious SEO for years,
you’ve already been optimizing for AI.
Remember article rewriting tools 10–15 years ago?
They analyzed sentence structure.
Applied contextual replacements.
Reassembled content algorithmically.
Primitive compared to today’s models?
Yes.
But still algorithmic language processing.
SEO platforms like SEMrush, Ahrefs, and others?
They process massive datasets.
Detect ranking patterns.
Cluster keywords.
Surface predictive insights.
That’s applied machine intelligence.
I’ve also spent time speaking directly with the teams behind these platforms—understanding how these systems evolve in practice (see
2020 interview).
What changed isn’t the existence of AI.
What changed is:
Accessibility.
Scale.
Interface.
Public awareness.
For those of us who’ve lived inside search for decades,
this isn’t a sudden revolution.
By 2013, I was already teaching digital marketing systems and search strategy—long before AI became accessible.
(Early training program, 2013)
It’s the next phase of systems we’ve been adapting to all along.
AI isn’t new to me.
What’s new is how many companies are unprepared for it.
After 20+ years working alongside machine-learning-driven systems in search, I now advise businesses on how to leverage AI as infrastructure — not as a trend.
