Bob Graham – Riggs Asset Management Company

Hi there, this is Bob Graham with Riggs Asset Management Company.

Today I want to talk about a topic that’s been getting a lot of attention in the news — artificial intelligence — and specifically the argument that the AI boom might be a bubble similar to what we saw in the late 1990s during the dot-com era.

Whenever markets rise significantly, you inevitably hear people say things like:

“It's a bubble.”
“It's overvalued.”
“This looks just like 1999.”

And while there may certainly be areas of the market that are ahead of themselves, I want to explain why, in my view, this situation is very different from what we experienced in 1999.

The key point many people overlook is that the late-1990s technology boom was not just the internet bubble.

It was really the Y2K technology cycle.

And that distinction is extremely important.

To understand why, let’s go back in time.

In the 1960s and 1970s, when computers were first being widely adopted, many of those systems were designed with a limitation in how they stored dates.

The systems only used two digits to represent the year.

That meant when the calendar reached midnight on December 31, 1999, computers would roll the date back to 1900 instead of 2000.

As a result, governments, corporations, banks, and businesses around the world faced a huge problem.

If they didn’t fix their systems before that date, many computer programs could stop functioning entirely.

So what happened?

Between roughly 1996 and 1999, companies and organizations across the world rushed to replace or upgrade their technology systems.

Everywhere you looked:

• Businesses replaced their computers

• Governments upgraded their systems

• Companies bought new servers and software

• Homes upgraded their personal computers

And because those systems were being replaced, companies often upgraded everything else at the same time:

• Monitors

• Keyboards

• Networking equipment

• Cabling infrastructure

Remember, Wi-Fi didn’t exist yet, so networks required physical connections everywhere.

So the entire global economy went through a massive technology replacement cycle.

Then came New Year’s Eve 1999 — the famous moment when people joked, “Party like it’s 1999.”

And after the calendar turned to January 1, 2000, something interesting happened.

No one needed to buy computers anymore.

The global replacement cycle had already happened.

Many of the biggest companies in technology — including software companies, semiconductor manufacturers, and hardware producers — suddenly faced a dramatic slowdown in demand.

In some cases, demand didn’t fully recover for four to six years.

That sudden drop in spending was a major factor behind the technology downturn that followed the dot-com bubble.

Today’s environment is very different.

Yes, artificial intelligence is driving a huge investment cycle, and some parts of the market may get ahead of themselves.

But unlike the Y2K era, there is no fixed date when demand suddenly disappears.

In fact, the opposite may be true.

Over the next several years, many companies will likely begin rebuilding their internal technology systems to better integrate with AI.

Right now, we’re seeing the buildout of AI infrastructure in areas such as:

• Cloud computing

• Data centers

• High-performance computing systems

But the next phase may involve companies re-engineering their internal technology stacks to fully take advantage of AI.

So instead of a short-term technology replacement cycle like Y2K, this may actually be the beginning of a long-term transformation in how businesses operate.

That’s why we believe this cycle could last many years.

Does that mean there won’t be volatility?

Of course not. Markets always have ups and downs.

But overall, we believe artificial intelligence will likely remain a major driver of the global economy — and an even larger driver of the U.S. economy — for the next five years or more.

So when you hear comparisons to 1999 and the dot-com bubble, it’s important to remember that the conditions driving those markets were very different.

This cycle may share some similarities, but in many ways it is dramatically different.

If you have any questions about this topic or would like to discuss how AI is affecting markets and portfolios, please reach out to your Riggs team member.

We’re always here to help.

Thank you very much, and I look forward to talking with you again soon.