Simon Hodgkins
Why AI Adoption Matters More Than AI Hype with Simon Hodgkins Ep 272 - The Global Discussion
In this episode of The Global Discussion, Host Simon Hodgkins steps away from the traditional interview format to explore a pivotal shift underway in the world of artificial intelligence.
The first act of AI was loud. This second act is potentially far more powerful.
Drawing on real-world trends and patterns across technology cycles, Simon makes the case that we have already moved beyond the infrastructure arms race. The spotlight is no longer solely on chips, data centers, and model size. Instead, the focus has shifted to something more consequential: adoption.
This episode challenges listeners to think differently about what progress in AI really looks like, and why the most transformative changes rarely make headlines.
From Infrastructure to Integration
In the early phase of the AI boom, the narrative was clear: bigger models, faster compute, more capital, and global competition. The headlines followed the spectacle and the speculation.
The first wave was about building the rails: hardware, platforms, and foundational tools.
But history tells us something important.
Every major technology wave follows a similar arc:
First, infrastructure.
Then, integration.
Finally, enduring value creation.
The internet, smartphones, and cloud computing all followed this pattern. AI is no different, except this time, everything feels accelerated.
The second act is not about possibility. It’s about behavior change.
AI Adoption: The Quiet Revolution
Adoption doesn’t arrive with fireworks.
It doesn’t announce itself with mass job displacement overnight or dramatic corporate reinventions.
Instead, it looks like:
A security team reducing investigation time by 30%.
A legal department accelerating document review.
An advertising team shifting from manual optimization to AI supervision.
Enterprise software tools quietly becoming indispensable.
These changes compound.
They reshape workflows, margins, and competitive advantage, gradually, then suddenly.
This phase rarely produces viral demos. But historically, this is where long-term value is built .
Advertising as an Early Indicator
Marketing has long been an early adopter of new technology, not because it chases novelty, but because its feedback loops are immediate.
If performance improves, you see it.
AI in advertising is not simply about automating creative production. That has been happening for years. The shift now is deeper:
Human judgment is moving upstream.
Execution is increasingly supervised rather than manually controlled.
Attribution models are becoming probabilistic and adaptive.
Measurement is continuous rather than static.
The human role is evolving — from operator to interpreter.
And that pattern is repeating across industries.
Security, Investigations, and Data Overload
In domains like cybersecurity, fraud detection, compliance, and risk management, the problem has never been a lack of data; it’s too much data.
AI changes the shape of work.
Instead of hunting blindly for anomalies, professionals are:
Validating insights.
Contextualizing findings.
Making decisions faster.
This doesn’t look like a disruption.
It looks like fewer late nights and smarter workflows.
But that operational shift changes what becomes possible.
Where Durable Value Lives
Historically, infrastructure providers capture early attention.
Application and workflow platforms capture enduring value.
Why?
Because once AI becomes embedded into daily operations, switching costs rise. Organizations build muscle memory around tools that feel less like software and more like collaborators.
As Simon emphasizes, this is not about adding chat interfaces to products. That’s table stakes.
It’s about redesigning workflows around intelligence.
This is slower work. It requires trust, change management, and cultural alignment. But it is where long-term advantage resides .
The Cultural Shift: The Hardest Challenge
Technology adoption is rarely limited by capability.
It’s limited by comfort.
AI challenges assumptions about:
Expertise
Ownership
Accountability
Performance evaluation
If AI drafts at a higher level, what becomes your role?
If decisions are augmented, where does accountability sit?
If output improves but processes change, how do you measure success?
These are not technical problems.
They are human ones.
Organizations that treat AI as a cultural transformation, not just a technical rollout, are moving faster.
When the Hype Cools, Builders Win
There is always a moment in every technology cycle when attention shifts elsewhere.
The hype fades.
The headlines quiet down.
Speculation gives way to execution.
That is when real value creation begins.
This second act is making intelligence “boring in the best possible way”, embedded, reliable, and indispensable.
The winners won’t necessarily be the loudest companies.
They’ll be the ones customers can’t imagine working without.
A Question for You
We are no longer asking whether AI is possible.
We are learning how to live with it, work with it, and depend on it.
So the real question becomes:
What are you doing to move faster in this AI-driven world?
About The Global Discussion
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