The S&P 500 Software and Services Index is down 15% over the past 2 weeks.

Why?

Concerns about AI volatility and spending.

Amazon announced $200B in AI infrastructure spending this year, and the stock dumped 11%.

On YouTube, some people say AI is a scam, while others say it’s life-changing.

Both are true.

We are living through the Gartner Hype Cycle.

The Gartner Hype Cycle playing out with Artificial Intelligence.

AI has been insanely exciting. Companies are spending hundreds of billions on the technology.

But, Investors and banks are not convinced the return is there.

In some cases like Amazon, price to earnings ratios have been as high as 31%!

Now we see a correction.

This doesn’t mean AI isn’t impactful, but it does mean we inflated our short term expectations.

It’s unclear if we’re at the bottom of the Trough of Disillusionment, but it is clear, banks and investors are asking “what’s next”?

Is this the end of AI investment?

Hardly, but it is important to pay attention, so your skills, careers, and investments keep up with a rapidly changing world.

-Mark

Google is offering voluntary exit packages inside its Global Business Organization.

On paper, it looks like a routine workforce adjustment. In context, it tells a bigger story. Over the past year Google has reduced thousands of roles across recruiting, hardware, and other non core divisions while accelerating investment in Gemini models, AI infrastructure, and cloud capacity.

When leadership talks about alignment, it means this: every team now has to justify how it supports AI growth, AI deployment, or revenue tied to AI products.

If a function cannot clearly show that contribution, it gets reviewed.

This is capital and talent being concentrated around one engine.

Read more here.

Telstra and Accenture launched a large AI and data joint venture backed by hundreds of millions to modernize enterprise systems. Now that same venture plans to eliminate more than 200 roles.

At first glance that sounds contradictory. Why cut jobs in an AI program.

But here’s what’s actually happening.

Large technology projects require heavy staffing in the early stages while systems are being built and integrated. Once those systems stabilize and automation handles routine layers, fewer people are required to keep them running.

The investment stays, except the staffing.

This is transition from construction to efficiency.

Read more here.

Workday has reduced roughly 375 roles across business analysis, quality assurance, and sales support while competition rises from enterprise platforms embedding artificial intelligence more deeply into their products.

Now look at the category Workday operates in.

Human capital management and enterprise planning rely heavily on reporting, configuration, and first layer analysis.

AI tools now accelerate those processes significantly.

When baseline work gets faster, output per employee increases. And when output increases, companies review staffing attached to those tasks.

This is a recalculation of labor relative to productivity.

That recalculation is spreading across enterprise software.

Read more here.

“Someone is sitting in the shade today, because someone planted a tree a long time ago.” - Warren Buffet