The AI Boom's Ripple Effect: When AI Giants Eat the Supply Chain

This week, I want to touch on a topic that I feel doesn’t get enough attention. The AI infrastructure buildout isn't just transforming how we work—it's reshaping the economics of every piece of hardware you buy. While it's been in the news, I don't think that the average person fully grasps the impact. 

I've been watching this unfold with growing concern. This week, Raspberry Pi announced another round of price increases, with CEO Eben Upton explaining that "the cost of some parts has more than doubled over the last quarter." The 8GB Pi 5? Up another $30. The 16GB Compute Module 5? Add $60.

The culprit isn't a supply chain disruption from a pandemic or a natural disaster. It's artificial intelligence. Or, more precisely, the insatiable appetite of hyperscalers building out AI infrastructure at a pace we've never seen before.

The math is brutal. 

Microsoft, Google, Amazon, Meta, and a handful of AI startups are collectively spending hundreds of billions of dollars on GPUs, high-bandwidth memory (HBM), and the LPDDR5 RAM that modern AI workloads demand. When you're buying components by the container ship, everyone else competes for the scraps.

Even Apple isn't immune. Reports suggest their profit margins are facing pressure from AI-driven memory chip costs. When Apple—a company that literally designs its own silicon and negotiates from a position of unmatched volume—feels the squeeze, you know the market dynamics have fundamentally shifted.

The same AI tools that are making developers more productive and businesses more efficient are simultaneously making the hardware those businesses need more expensive. That $35 Raspberry Pi, perfect for edge computing projects or teaching kids to code, is now pushing $60-70 for the same capability.

So, when does this stabilize? 

I see two paths:

1. A slowdown in AI infrastructure investment — Extremely unlikely. The competitive pressure to build AI capabilities is only intensifying, and we're nowhere near the plateau of the S-curve.
   
   
2. A massive increase in production capacity — This is coming, but fabricating advanced memory and compute isn't something you spin up overnight. New fabs take years to build and ramp.

Honestly, we're probably looking at years of this dynamic before supply catches up to demand. 

What This Means For IT Leaders

For IT leaders, this means hardware budgets need to account for inflation that is not reflected in traditional economic indicators. If you zoom out just a little further, you can see that those same hardware costs will have knock-on effects on so much more. Computers are a fundamental aspect of nearly all businesses. If a business has to shoulder higher costs, then they will have to raise their prices, cut costs elsewhere, or more likely both.

The tactical takeaway: Don't underestimate the global impact of the AI race on all businesses. Leaders should be planning with the assumption that their business will be impacted by market forces beyond their control, even if they're not directly impacted by RAM's skyrocketing prices and supply shortages.