Podcast

Ep 137 – Hyperscalers’ $2T bet (Charles Fitzgerald)

March 30, 2026

This week’s guest

Charles Fitzgerald

Managing Director Platformonomics, LLC

Hyperscaler CAPEX investments are staggering: Amazon, Google, Microsoft, and Meta spent more than $400 billion on infrastructure in 2025 and are expected to reach over $600 billion in 2026. They’re on pace to surpass $2 trillion in cumulative CAPEX spend before the year is over. Meanwhile, U.S. telco CAPEX sits at $50 billion for 2025—and it’s shrinking.

For this episode, Charles Fitzgerald, Managing Director at Platformonomics, returns for his fourth (!) appearance on Telco in 20 to break down his tenth annual Follow the CAPEX report. We dive into the hyperscaler spending surge, the two big telco AI plays coming out of MWC 2026—sovereign cloud and AI-RAN, and why the gap between infrastructure spenders and operators is impossible to close.

Listen now to hear:

How AI supercharged hyperscaler CAPEX—and changed the math for telcos [02:59];
Why sovereign cloud may already belong to the hyperscalers [05:57];
How AI-RAN looks more like an NVIDIA play than a telco strategy [09:54]; and
Why Oracle’s catch-up bid is a cautionary tale [13:25].

Links and resources

Read Charles Fitzgerald’s annual 2025 Follow the CAPEX report.
Check out Charles Fitzgerald’s 2024 retrospective on public cloud CAPEX spending and check out his Cloud Reactor Tracker.
This was Charles’s fourth appearance on our podcast. Check out his previous episodes:
Is Oracle’s CAPEX bet genius or madness? Fortune breaks down the numbers.
Learn more about the Totogi Ontology and how it’s helping Tier-1 operators turn AI into actual profit.
Read the Appledore Research report on Totogi: Telecom-specific Ontology, the key to AI-native telco (paywalled).
Charles has been on the podcast four times—one more and we may have to get him a Five-Timers Club jacket, SNL-style.
Check out this episode on our YouTube channel.
You can find the episode transcript here.

Wanna talk AI and public cloud? Telco execs, set up a meeting with our team to learn how to tap the immense business value it can bring.

Guest bio

Charles Fitzgerald is a Seattle-based angel investor, with a focus on developer platforms and infrastructure. Previously, he spent 20+ years working on platform businesses at Microsoft and VMware. He can see the cloud from his house.

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Podcast credits

Executive Producer and Host: Danielle Rios, TelcoDR
Senior Producer: Lindsay Grubb, TillCo Media
Senior Editor/Brand Manager: Alisa Jenkins, Springboard Marketing
Audio Editor: Andrew Condell
Supervising Producer: Amanda Avery
Associate Producer: Kriselda Dionisio
Music: Dyami Wilson

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More episodes from Telco in 20

Ep 136 – MWC26 Wrap Up (Mobile World Live)

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Ep 135 – Telco has a context problem (John Abraham)

Appledore Research's John Abraham joins DR to explain why context, not data, is the real blocker for AI at scale, and how ontologies give AI the business logic it needs to actually work.

Ep 134 – Show me the money (MWC)

In this special episode, DR explains the one tough question you should be asking vendors before you buy AI and why the Totogi Ontology is key to delivering real world results.

Frequently Asked Questions

1. How much are the hyperscalers actually spending on AI infrastructure?

Amazon, Google, Microsoft, and Meta collectively spent over $400 billion on infrastructure in 2025—up 66% from the prior year—and are guiding to more than $600 billion in 2026. They will surpass $2 trillion in cumulative CAPEX before the year is over. Ten years ago, this same group spent only $28 billion combined. The inflection point was the launch of ChatGPT in November 2022, after which their CAPEX growth rates doubled and absolute spend nearly tripled. Read Charles Fitzgerald’s full Follow the CAPEX report.

2. Can U.S. telcos realistically compete with hyperscaler AI spending?

Not on raw spend. U.S. telco CAPEX sits at roughly $50 billion—and it’s falling—while Meta alone outspent all three major U.S. telcos combined, with $20 billion to spare. As Charles Fitzgerald puts it, telcos are integrators and operators: they buy and operate technology, they don’t create it. That distinction is decisive when you’re competing against companies with tens of thousands of software engineers and hundreds of globally distributed data centers.

3. Why is sovereign cloud such a long shot for telcos?

Sovereign cloud bets that local regulations will favor local players over hyperscalers. But building competitive cloud infrastructure means constructing the software layer from scratch—something telcos have never done. When Charles searches “sovereign cloud,” the results are dominated by hyperscalers, not telcos. The EU’s Euro3C consortium, led by Telefónica, has committed €75 million—a figure Charles describes as a rounding error against hyperscaler spend. His verdict: telcos have probably already missed this boat.

4. What’s Danielle Rios’ take on why telcos keep falling short on software?

Danielle Rios points out that people underestimate how much of the hyperscaler advantage is software, not just infrastructure. The big clouds don’t just build data centers—they build the sophisticated tooling that helps customers create and manage workloads at scale. Telcos have never had that capability, and you can’t buy it off the shelf. DR also flags the AI hardware refresh cycle—18 to 24 months—as a treadmill telcos can’t keep up with. Watch DR’s MWC26 Agentic AI Summit talk, Show Me the Money.

5. What does Oracle’s cloud push tell us about the cost of playing catch-up?

It’s the most instructive cautionary tale in tech right now. Oracle dismissed cloud for years, then lost half its database market share and scrambled to catch up from a nearly standing start. Despite borrowing heavily and spending over $3 in CAPEX for every dollar of cloud revenue (versus AWS’s ~$0.75), Oracle’s cloud business remains small and its free cash flow deeply negative. At least Oracle can write software. Telcos can’t even claim that advantage.

6. If telcos can’t out-CAPEX the hyperscalers, what game should they be playing—and how does Danielle Rios see the Totogi Ontology fitting in?

DR’s takeaway is that telcos need to compete on what compounds for them: deep operational knowledge. Rating rules, provisioning workflows, product specs—this knowledge currently sits locked in vendor code and people’s heads, invisible to AI systems. The Totogi Ontology captures that knowledge and makes it executable, so AI can act across systems. Every action—resolving a dispute, applying an offer, provisioning a service—makes the next decision smarter. Revenue goes up, costs go down, and unlike hardware, the advantage widens every day. Read the Appledore Research report on Totogi’s telecom-specific ontology.