A Half-Life Crisis: The Importance of Laddering in Data Centres
A data centre decays like an isotope, not a building...an operator’s share decays, but the landlord’s share enriches. A novel approach to the valuation and lease structure to factor this in.
There’s seems to be a $176 billion argument raging through the AI industry right now, but I personally think everyone in it is holding the wrong end of the problem.
Michael Burry, of Big Short fame, has accused the hyperscalers of flattering their earnings by stretching the accounting life of their GPUs; Microsoft depreciates over six years, Meta over five and a half, while Nvidia ships a new architecture roughly every year and the founder of Groq argues the real economic life of an AI accelerator is closer to one or two. Burry puts the understated depreciation at $176 billion between 2026 and 2028.
Both sides are arguing about one component, on one balance sheet. My problem is with everything wrapped around it.
A data centre is a single facility running on several clocks at once. The silicon ages in about three years; the mechanical and electrical fit-out in ten to fifteen; the shell and the land underneath it on a timescale where, in the current market, they may not be ageing at all. And critically, those layers usually sit on different balance sheets. Most data centres are leased: a freeholder owns the shell, a tenant operator owns the kit inside it and holds a leasehold that runs down to zero on a fixed date. Any calculation that treats the facility as one asset with one owner, including the version of this argument I first sketched out, gets the answer wrong before it starts.
So rather than join the fight over whether a GPU lives three years or six, I want to ask two questions the whole discussion seems to be overlooking:
What is the blended lifespan of each party’s stake in the building?
And what happens when the fast clock and the lease clock strike midnight in the same year?
Whose building is it anyway?
We need to start with the split, because it changes the context of everything.
To the freeholder, the age of the servers is close to irrelevant. They own a powered shell with a grid connection, planning consent and a covenant from the tenant; as far as they’re concerned, the tenant’s kit could be bleeding-edge Blackwell, or frankly, a rack of abacuses. It’s better than irrelevant, in fact: while the operator’s equipment has been decaying, the capital value of the site has in most markets will have likely been appreciating, driven by power scarcity, interconnection queues and the sheer difficulty of consenting new sites. By virtue of those facts the freeholder’s isotope isn’t decaying, it’s actually enriching.
To the tenant operator, the picture is the exact opposite, and far worse than the depreciation debate suggests. The operator’s stake is a stack of three assets, every one of them wasting: the servers on roughly a three-year economic life; the mechanical and electrical fit-out they installed on ten to fifteen; and the leasehold interest itself, which amortises down to precisely zero on the day the term expires, however lovingly the building has been maintained by them.
The whole industry regularly argues about the first item on that list; but in reality, it’s the third that really bites.
A borrowed idea from the physics department
I’m a sucker for stealing the homework of more successful parallel universes, and the physicists did this particular piece of homework a century ago.
A mixture of radioactive isotopes doesn’t have a single expiry date; each component decays on its own curve. So if you want to know how alive the mixture is, you don’t average the labels on the tin, you sum the decay curves and read the total.
This is the correct mental model here too, albeit with one amendment: you must run it separately for each balance sheet. The remaining value of a party’s stake at time, t is:
Where v is the share of that party’s capital in each layer and T is the layer’s half-life. Their half-life is the point where half their stake, by value, has expired:
Established maths (borrowed openly); applying it per-balance-sheet to a data centre lease is my own synthesis, so treat the numbers that follow as illustrative.
If we take a tenant operator on a fifteen-year lease of a 100MW campus. Say their invested capital splits 65% servers and networking (three-year life), 25% fit-out (twelve years), 10% leasehold interest (amortising to zero at year fifteen).
Plot these curves and the operator’s half-life lands around 4.4 years. Half of everything they’ve put into that building, gone before the first rent review. The freeholder, over the same period, may well be sitting on an asset worth more than they paid for it. It’s the same building but with two half-lives (and one of them suggestively negative – or actually enriching).
The scissors in the lease
The widely considered server-depreciation argument often mistakes the lease itself as a passive backdrop. But it’s really not at all; infact, it’s specific terms drive the calculation.
A leasehold interest is worth, roughly, the gap between the rent that’s being paid and the rent the market would charge today, capitalised over the years left until the maturity, or term date:
Two forces pull on that number in opposite directions, which is why I think of it as a pair of scissors. The annuity factor shrinks as expiry approaches; fewer years left, less to capitalise. But if market rents are growing, the rent gap widens every year the operator sits on their current rental rate.
In a market where prime capacity is scarce and rents are climbing, a leasehold can be appreciate through the middle of its term before the shortening tail drags it to zero. So the wider that gap grows, the more brutal the reset at renewal date. At 5% annual rental growth, the market rent in year fifteen is more than double the passing rent. Your appreciating leasehold is a countdown to a doubled rent bill.
The lease terms decide how sharp the scissors are, and they deserve more attention in these calculations than the servers do. Upward-only rent reviews, still standard in UK commercial leases, mean the gap only ever closes one way. Indexed reviews with caps and collars soften the path but not the terminal reset. Break clauses shift the effective maturity. Dilapidations and reinstatement obligations add a lump of end-of-term cost that scales with how much equipment the tenant bolted to the fabric of the building. And a lease contracted out of the 1954 Act gives the operator no security of tenure at all: renewal at open market rent, if the freeholder fancies renewing with you.
When both clocks strike midnight
This is where it turns from an accounting curiosity into a cashflow problem: does the equipment’s decay line up with the leasehold’s? On many standard structures, catastrophically, it would appear to be a ‘yes’.
A fifteen-year lease with a three-year server cycle puts refreshes at years three, six, nine, twelve and fifteen. Year fifteen is also lease expiry. So in a single year, our example tenant operator faces: a renewal negotiation at a market rent that could be double what they’ve been paying, with the negotiating leverage of somebody whose entire operation is bolted to the floor of the landlord’s building; a full server fleet purchase; likely the tail end of the fit-out’s life too; plus dilapidations on the way through. Every layer of that stack demanding capital simultaneously, in what may also be the year lenders are least keen to extend, because the collateral (that leasehold) has just amortised to zero. It’s the duration mismatch that would make a 2008 mortgage banker blush, and it’s baked into the standard lease template.
Corporate treasurers solved this decades ago and named it: laddering. You never let your debt maturities land in the same year, precisely so no single refinancing wall can kill you. The same logic should govern data centre leases, and it gives us a design rule. Stagger the maturities so the lease event lands mid-way through a refresh cycle:
On a three-year refresh, that means preferring a sixteen-to-seventeen-year term over the tidy fifteen, or negotiating breaks and reviews at years that sit between refreshes, or deliberately offsetting the refresh programme itself. The point is the same in every version: significant capital events, spread as evenly as possible across the operational lifetime of the building, so the operator walks into every renewal with a young fleet and a strong covenant rather than an expiring everything.
Whose half-life is it anyway?
Which brings me back to valuation, and a better way to do it than my own first attempt. It would suggest that there is actually no such thing as the half-life of a data centre.
There is the freeholder’s curve (shell, land, grid connection, often appreciating), and;
The operator’s curve (kit, fit-out and a wasting leasehold, half-gone in under five years).
The two must be computed separately because the parties can, and increasingly do, sit on opposite sides of the table at renewal. Any single blended number for the facility smuggles in an owner-occupier assumption, and outside the hyperscalers’ own campuses, that animal is rare.
Read the Burry row through that lens and it shrinks. A six-year depreciation schedule against a three-year chip is an error of 2x on one layer of the tenant’s/operator’s costs. A fifteen-year lease that concentrates a rent doubling, a fleet purchase and a dilapidations bill into the same trading year is a structural error across the whole stack of costs.
Where the isotope leaks
As with most of my more novel takes, I appreciate it’s not quite as simplistic as originally suggested; silicon doesn’t decay on a smooth curve; cascading kit from training to inference flattens the early years, and if you stretch the server life to four or five, our operator’s half-life moves out towards six. Those are all fine and sound arguments; but every lease structure above is still mismatched. The leasehold formula also ignores renewal goodwill, sunk connectivity and the practical reality that moving 100MW of live load is so painful that operators will nearly always likely renew on bad terms rather than migrate, which is of course exactly the leverage the maths is pricing. And the model measures replacement value, not earning power; an old chip that still books revenue is dead on my curve and alive on the P&L. There is nothing to suggest that just because an AI-based chip is obsolete for the latest models, it can’t be repurposed as part of a simpler compute unit either – in which case the depreciation isn’t a straight line on that asset either.
However, I still think the core of it holds. The building’s paperwork keeps the freeholder’s time, amd the value inside it keeps the operator’s. Until leases are structured around both clocks, with maturities laddered the way any competent treasurer would ladder debt, the industry will keep concentrating its capital demands into coincidence years and calling the resulting distress a surprise – but in all honesty, it never was - it was actually on the calendar from the day the lease was signed.
TH