AI Has a Workforce Problem

AI Has a Workforce Problem (And It’s Not What Most People Think)

In my last article I shared that before I worked in infrastructure, I grew up on a farm.

You learn quickly that nothing operates in isolation, every decision affects something else.

I later worked in construction, running a labouring and landscaping business, where I saw how plans hold up in the real world.

That mindset carried into infrastructure.

And after more than 20 years delivering at scale, I can tell you this:

Projects don’t fail because of strategy.

They fail because of execution.

And execution depends on people.

What People Think

When people talk about AI, they focus on:

·         Models

·         Compute

·         Investment

And occasionally:

·         Talent in software and machine learning

But that’s only part of the picture.

Because AI at scale isn’t just a software problem.

It’s an infrastructure delivery problem.

What’s Actually Happening

Behind every AI system, there’s a chain of physical delivery:

·         Data centres being built

·         Networks being deployed

·         Power systems being upgraded

·         Cooling systems being installed

And all of that requires people.

Not just more people, the right people.

Where It Breaks

This is where theory and reality separate.

On paper:

“We’ll scale the workforce.”

In reality, it doesn’t work like that.

1. Skilled Workforce Is Limited

You need:

·         Engineers

·         Project managers

·         Fibre specialists

·         Construction crews

·         Commissioning teams

These aren’t always interchangeable.

And they take years to develop, you can’t teach experience!

2. Timing Is the Real Constraint

It’s not just availability.

It’s when those people are available.

In large-scale delivery, you need:

·         The right skills

·         At the right time

·         In the right location

Miss that alignment, and projects slow down.

3. Geographic Challenges

AI infrastructure is increasingly being built:

·         Near power sources

·         In regional or remote locations

But skilled workforce pools are concentrated in cities.

Which creates:

·         Travel requirements

·         Relocation challenges

·         Increased cost

·         Slower mobilisation

4. Competing Demand

This workforce isn’t dedicated to AI.

It’s shared across:

·         Energy projects

·         Telecommunications

·         Civil infrastructure

·         Construction

So now you have multiple industries, competing for the same people.

Operator Insight: This Is Where Projects Stall

I’ve seen projects where:

But delivery slowed.

Because the workforce wasn’t aligned.

Not absent, just not where it needed to be, when it needed to be there.

That’s a very different problem.

The Real Constraint: Alignment, Not Headcount

This is what most people miss.

The issue isn’t:

“Do we have enough people?”

It’s:

“Can we align the right skills, at the right time, in the right place?”

Because infrastructure delivery is sequential.

If one phase slips, everything behind it shifts.

Where This Fits in the 5 Constraints

Workforce isn’t separate.

It interacts with everything:

This is where constraints compound.

What This Means for Industry

We’re moving into a phase where:

·         Workforce availability becomes a strategic risk

·         Delivery capability becomes a differentiator

·         Labour constraints shape timelines and cost

·          

And importantly:

Experience matters more than ever.

Because scaling infrastructure isn’t just about numbers, it’s about capability.

What Happens Next

Over the next few years:

·         Competition for skilled infrastructure workers will increase

·         Project timelines will extend due to workforce constraints

·         Costs will rise as demand outpaces supply

·         Organisations with strong delivery capability will outperform

And we’ll start to see:

Workforce becoming a primary constraint, not just a supporting factor.

Final Thought

In infrastructure, nothing gets built without people.

You can have:

But without the right workforce.

At the right time.

Nothing moves.

References & Further Reading

Footnote
This article is part of a series exploring the physical infrastructure behind the AI economy.

Disclaimer
The views expressed in this article are my own and are intended for general information and discussion purposes only. They do not represent the views of any employer, organisation, or client.

© 2026 Rodney Terry – Digital Backbone. All rights reserved.