The 53-Month Problem: Why Data Center Wait Times are Making the "Picks and Shovels" Trade Even Better

Here's something Wall Street isn't pricing in yet: the same bottleneck that's delaying data centers is actually making infrastructure stocks safer bets.

I'm talking about the 53-month interconnection wait time that's quietly reshaping the entire AI infrastructure trade.

📉 What the 53-Month Problem Actually Means

Data center projects currently face four and a half years just to connect to the power grid.

Not four and a half years to build. Four and a half years to get permission to plug in.

This isn't a regulatory fluke or temporary slowdown: it's structural. The grid wasn't designed for the kind of power demands AI data centers require. And the equipment needed to upgrade it? That's where things get interesting.

Transformer lead times alone:

• Standard units: 80–120 weeks (nearly 2 years)

• Transmission-class transformers: 3–6 years

• Specialized AI data center equipment: Even longer

The Trump administration recently pushed for emergency procurement because power demand for data centers is accelerating, but the equipment pipeline remains stuck. Governors in the mid-Atlantic are echoing the same concerns.

This is the opposite of a demand problem. It's a capacity problem. And capacity problems create multi-year revenue visibility for the companies supplying the equipment.

🔧 Why Bottlenecks Favor the "Picks and Shovels" Play

In our AI Infrastructure Playbook, we laid out three pillars: Power, Cooling, and Connectivity.

Power is Pillar 1 for a reason. Without it, nothing else works.

And right now, the companies making transformers, generators, and grid interconnection equipment have something chip makers don't: guaranteed, years-long backlogs.

Here's the thing: when equipment availability becomes the primary bottleneck (not financing, not demand, not regulatory approval), the suppliers become the essential gatekeepers. Every single data center project has to wait for them.

That's different from betting on Nvidia $NVDA ( ▼ 1.1% )  or AMD $AMD ( ▲ 5.01% ), where quarterly earnings can swing 20% on inventory adjustments or guidance changes. Infrastructure suppliers don't have that volatility. Their order books are full through 2028 and beyond.

📊 The "Latte Metric": Backlog / Revenue

Here's a simple framework I'm using to evaluate data center power stocks: the Backlog-to-Revenue ratio.

Take a company's total backlog (publicly disclosed in 10-Ks and earnings calls) and divide it by annual revenue.

What it tells you: How many years of locked-in revenue the company has, assuming current run rates.

• Ratio below 1.0: Less than a year of visibility. Risky.

• Ratio of 1.5–2.5: Solid pipeline. Normal for industrial companies.

• Ratio above 3.0: Multi-year revenue locked in. This is what we want for long-term investing in infrastructure.

Companies supplying transformers and electrical systems for data centers are pushing ratios above 4.0 right now. That means they could stop winning new contracts today and still have four years of revenue in the pipeline.

That's not speculation. That's math.

⚡ Equipment Delays = Structural Advantage

The 53-month interconnection wait isn't going away. If anything, it's getting worse as AI demand compounds.

But here's what makes this a picks and shovels AI stocks opportunity: the delays don't kill the projects; they just defer them. And every deferral extends the runway for equipment suppliers.

Think about it:

• Google $GOOG ( ▲ 1.06% ), Microsoft $MSFT ( ▼ 1.33% ), and Amazon $AMZN ( ▲ 2.37% )  aren't canceling data center builds because of power delays

• They're just pushing timelines out

• Which means equipment orders shift from 2026 to 2027, from 2027 to 2028

• The backlog grows, not shrinks

This is the exact opposite of cyclical demand. It's structural scarcity.

And scarcity in infrastructure, especially in something as unglamorous as transformers, creates pricing power. These aren't commodities you can suddenly manufacture in six months. The supply chains are complex, the lead times are long, and the barriers to entry are high.

🏗️ Contrast: Chip Stocks vs. Infrastructure Stocks

I've been tracking both chip makers and infrastructure suppliers since mid-2025. The difference in volatility is striking.

Chip stocks move on:

• Quarterly guidance misses

• Inventory concerns

• Competition from new architectures

• Sentiment shifts around AI adoption rates

Infrastructure stocks move on:

• Quarterly backlog updates (almost always up)

• Long-term power demand forecasts

• Multi-year contract announcements

• Regulatory changes to grid interconnection (rare)

One is a sentiment trade. The other is a capacity trade.

If you're building a position for AI infrastructure stocks that compounds through 2028 AND beyond, the equipment suppliers have a clear path.

We've already highlighted a few names in earlier posts: Quanta Services is one worth revisiting: but the broader thesis holds: the bottleneck creates the moat.

🎯 The Takeaway: Backlog = Safety in 2026

The 53-month problem isn't a bug. For infrastructure investors, it's a feature.

It means every hyperscaler that wants to build AI capacity has to get in line. And the line is long. And the suppliers at the front of that line have multi-year revenue visibility that most public companies would kill for.

This is why I'm prioritizing data center stocks focused on power over chip plays this year. The upside might be slower, but the downside risk is significantly lower. When your backlog-to-revenue ratio is above 3.0, you're not guessing about demand: you're just executing on contracts already signed.

If you want to go deeper on the full infrastructure thesis, check out the complete AI Infrastructure Playbook here. We've also just published an analysis on why liquid cooling concerns are overblown, covering Pillar 2 in detail.

The power buildout is happening. The question isn't if: it's who's supplying the equipment. That's where I'm looking.

George ☕️