The AI Bubble Will Burst. AI Is Still Here to Stay.

I was watching Landman this weekend, and a line from the opening scene got me thinking.

Billy Bob Thornton's character talks about the enormous amount of money the Oil & Gas industry generates. The number is staggering.

It made me think about another industry where the numbers are becoming almost impossible to comprehend: Artificial Intelligence.

Companies are pouring money into AI infrastructure, models, applications and talent.

And naturally, the questions are getting louder.

I think these are fair questions.

But I also think we may be focusing too much on whether there is a bubble and not enough on what happens after the bubble.

Because even if the AI market experiences a correction, that does not mean AI disappears.

Quite the opposite.

The AI bubble may burst. The infrastructure will remain.

History has a funny way of repeating itself.

Many transformational technologies go through periods of excessive optimism.

Eventually, reality catches up.

But the underlying technology often remains.

The internet did not disappear after the dot-com bubble.

Cloud computing did not disappear when individual providers and business models failed.

Mobile technology did not disappear simply because certain companies could not capitalize on it.

The same principle applies to AI.

That does not change the fact that AI is becoming part of the underlying technology infrastructure of modern business.

And that is the part I find most important.

AI is becoming infrastructure

When we think about AI, we often think about chatbots, image generators, copilots or the latest model.

I think the bigger story is happening underneath all of that.

AI is becoming infrastructure.

Organizations are beginning to integrate AI into customer service, software development, analytics, cybersecurity, healthcare, finance, operations, supply chains and workforce management.

The technology is increasingly becoming part of how work gets done.

That is a very different proposition from simply having an AI application.

Infrastructure tends to have a long life.

But once businesses start redesigning processes around a capability, that capability becomes very difficult to reverse.

And I believe AI is moving in that direction.

But what about the money?

This is where the bubble conversation becomes interesting.

There is absolutely a possibility that spending has run ahead of realistic short-term returns.

We should not pretend otherwise.

But that does not necessarily mean the underlying thesis is wrong.

It may simply mean that the market is figuring out what AI is actually worth.

That is a normal part of technology adoption.

The bigger question is not whether AI is overvalued

For businesses and professionals, I think there is a more important question.

What happens if AI is actually as important as people believe it will be?

That is a risk worth considering.

Because waiting for certainty sounds rational.

But in technology, certainty often arrives after the advantage has already moved somewhere else.

By the time everyone agrees that a technology is important, the early adopters have already built skills, redesigned processes and established a lead.

That is why I am not particularly interested in predicting exactly where the AI bubble will peak or when it might correct.

I am much more interested in staying relevant.

There are two choices

When I think about AI today, I see two broad choices.

Option 1: Wait for the results to be perfect.

The problem is that by the time all of those conditions are satisfied, you may already be behind.

Option 2: Stay relevant.

I am choosing option 2.

This matters even more for Workforce Management

As someone who has spent a significant part of my career in Workforce Management, I see a particularly interesting opportunity here.

WFM is full of processes that involve large amounts of data, repetitive analysis and continuous decision-making.

These are all areas where AI can potentially change how work gets done.

But the biggest opportunity is not simply automation.

It is decision intelligence.

A system that does not just tell us what happened, but helps us understand what is happening, what is likely to happen next and what action could produce the best outcome.

That is a much bigger shift.

We should stop thinking only about AI tools

This is another lesson I take from the current AI discussion.

It is easy to become obsessed with tools.

Those questions matter.

But they are not the whole picture.

The more important question is:

How does this technology change the way we work?

A company that adopts an AI tool but keeps the same processes, structures and decision-making may gain very little.

Another company may use a relatively simple AI capability but completely redesign how work flows through the organization.

The second company may create much more value.

The competitive advantage is not necessarily the tool.

It is how you use the tool.

The people who adapt will have an advantage

There is another part of this that gets lost in the AI debate.

Technology adoption is not only about companies.

It is also about individuals.

Every professional needs to ask:

For WFM professionals, that might mean becoming stronger in analytics, AI literacy, strategic planning, business partnering, process design and change management.

For leaders, it may mean learning how to redesign organizations around AI rather than simply adding AI to existing processes.

The people who stay curious will have an advantage.

The biggest risk may be waiting

I think we sometimes frame the AI decision as:

Should I believe in AI?

That is not really the question.

You simply need to recognize that AI is becoming important enough that ignoring it is itself a strategic decision.

And it may be the riskiest one.

There is no guarantee that every investment will succeed.

There is no guarantee that every technology will survive.

But there is a very good chance that the people and organizations who understand AI will be better positioned than those who choose to ignore it.

My take

I would not be surprised.

But none of that changes my view that AI is becoming a foundational capability.

And the organizations that learn how to use AI effectively today will have a very different starting position tomorrow.

So I am not waiting for the bubble question to be answered.

Because there are two ways to look at this moment.

You can spend your time asking:

What if this is all a bubble?

Or you can ask:

What if this is the beginning of the biggest shift in how we work?

I know which question I would rather prepare for.

The bubble may burst. AI is not going away.