The American electric power sector has not grown appreciably for
twenty years. To be sure, consumers pay plenty to replace
infrastructure, to “transition” the sector away from the most
carbon-intensive sources of energy, and to find ways to allow utilities
to cram a wide variety of underutilized capital spending (think “smart
meters”) into their regulated “rate base.” But demand has been stable or
declining.
To the degree that profits in the sector have grown, it is because
the economic regulation of the utility industry provides for a “spend
more, make more” ecosystem whose profits are a function of its capital
investment. The sector is still one of the few that is actively
regulated through government price-setting, even in places sometimes
mistakenly termed “deregulated.” So, even when demand is not rising, the
business must find ways to grow earnings by spending more to serve the
same level of demand. This has meant that rates, which otherwise might
be declining, have been at best steady, even without increasing grid
capacity, and in fact, much utility spending has been undertaken to retire reliable capacity.
This was the uninspiring landscape of American electric utilities on
the eve of the boom in data centers needed to fuel the technological
revolution in AI. Electricity demand forecasts are now sharply up for
the balance of this decade, and a majority of this growth is
concentrated in data center power needs, with growth in manufacturing a
distant runner-up.1
For a power system that serves as a basis for Americans’ everyday lives
and the economy writ large, it is unusual to see such a concentration
amid one particular sector for its growth.
The rising power demand of the data center industry almost appears
like an industry running within the integrated grid but outside the
usual paradigm of the traditional electric utility sector. Indeed, it
should be treated as such. Doing so calls for a variety of policy
solutions that accurately price grid capacity in order to facilitate
efficient usage of that scarce asset, impose regulatory requirements to
furnish power generation to the system, and in the alternative, allow
power demand that is more flexible to better use residual capacity. Such
reforms can accomplish two important policy aims simultaneously. First,
they would insulate legacy customers who have already paid their fair
share and then some for the grid. Second, they would allow power
industry growth in support of data centers to be unchained from
traditional utility practices, which often do not reward speed or
innovation.
Both of these aims, customer protection and growth, are embodied in
the Ratepayer Protection Pledge, a March 2026 declaration at the White
House undertaken jointly by the Trump administration and seven major
hyperscaler AI companies. The 485-word document begins with an
endorsement of data center infrastructure as “the foundation of the
internet, cloud computing, and artificial intelligence (AI),” noting the
national security implications of this. But it qualifies that “the
American people should not be footing the bill for the benefit of
private companies.”2
The central proposals of the Pledge are that AI companies “will pay
for all new power delivery infrastructure upgrades required to service
their data centers” and “will bring, build, or buy the new power
generation resources and electricity needed to satisfy their new energy
demands.” By directly incurring these costs, the “companies agree to
protect American consumers from price hikes due to data center energy
and infrastructure requirements, and lower electricity costs for
consumers in the long term.” These ambitions are easier to proclaim than
accomplish.
Power grids are characterized by joint costs: poles and wires,
transformers, and substations that together form a network. Both the
typical practice and the financial incentives of most local utility
monopolies militate toward a broad socialization of costs to consumers.
They do this by having rates set by utility commissions on the utility’s
average, embedded costs, rather than pricing based on marginal costs or
on a new customer’s willingness to pay. The Pledge wisely points the
way toward value-based pricing for grid access that recovers at least
the incremental cost of serving customers. This seemingly mundane
change, if well implemented in an open season where data centers vie for
grid access, is capable of not just protecting legacy ratepayers, but
producing massive investment in the American power grid.
Meanwhile, for the power plants that generate electricity for data
center consumption, the proposition that the AI industry furnish its own
supply is both straightforward and, sadly, unlawful in a majority of
states, which maintain local monopolies that prevent this. In these
places, many proposals purporting to fulfill the Pledge fall well short
of the mark. But this is not to say it is an easy story of letting the
market go to work. Even in those regions where competition has been
introduced to the sector, investment has been slow to materialize. The
Pledge suggests clearing away barriers to new power generation, but with
a corresponding regulatory mandate to match the Pledge’s ambition that
AI companies bring their own generation to the grid.
The purpose of this essay is threefold: to examine the broader
economic and institutional context that the Pledge must address; to put
some meat on the bones of its spare but purposeful declarations; and
also to take aim at some bad ideas masquerading as fulfillments of the
Pledge’s ambitions. Since the two sides of the industry—price-regulated grid costs and more commoditized power generation—operate
on so different a basis today, it is best to consider them in turn, but
with reforms that ultimately come together, like the grid itself, in
sound operation.
The Economics of Regulation
Amid a framework of economic regulation that exists for the electric
power industry and very few others, utility commissioners at the state
and federal levels fix prices based on a utility’s “cost of service.”
This form of price regulation allows the utility to recover both its
invested capital and a regulated return on that capital, while generally
passing operating expenses through to customers without any markup.
The math that results from cost-of-service regulation is, at its
core, one big division problem. The numerator is a sum of the utility’s
costs; the denominator, the volume of services the utility sells; the
quotient is the rate you pay. Pricing in competitive markets settles
around the cost to serve marginal demand, at least according to the
basic principles of microeconomic theory. Utility pricing, however, is
principally concerned with recovering the sunk costs of infrastructure,
which usually serve to flatten and socialize the volatile tendencies
that would be expressed in a competitive, commoditized market. “Notice
how, at once, the traditional practices of public utility price
regulation diverge from economic principles,” the economist and utility
regulator Alfred Kahn once dryly observed of the difference between
marginal-cost and average-embedded-cost pricing.3
Kahn’s ironic observation has great import today. This divergence
between competitive and utility pricing has substantial implications.
Consider what happens when incremental demand manifests in
price-regulated utility service. In the division problem, if the
numerator (costs) rises more slowly than the denominator (demand), then
all other customers’ rates would decline as a result of adding a new
customer to the grid when utility commissioners next reset utility
rates.
There are many examples of this happy phenomenon in the utility
sector, beginning in its 1920s heyday, where investment and sales
volumes soared, even while rates fell.4
More recently, unassuming North Dakota emerges as the winner of the
demand growth Olympics in a magisterial study conducted by Lawrence
Berkeley National Laboratory and Brattle Group that evaluated retail
electricity rates from 2019 to 2024; the state simultaneously notched
the highest percentage demand growth and the steepest percentage reduction in retail electricity prices.5 New Mexico and Nebraska are in much the same situation.
Some have taken these historical occurrences to stand for a general principle that a rising tide of demand lifts all
boats. Would that were so. The early industry’s victories on economies
of scale have long been priced in. Indeed, for decades now, the sector’s
new classes of capital assets have been trending smaller,
predicated on diversifying risk and modular, nimble deployment. When
studied closely, these recent successes are idiosyncratic demonstrations
of the ingredients one would need to make a return to those halcyon
days a reality. North Dakota, for example, had residual grid capacity
remaindered from previous oil booms, and on the commodity side, cheap
fuels and a surplus of power generation stimulated by federal tax
incentives pointed at renewables. In both situations, the marginal cost
to serve was lower than the average, embedded cost rate, and this
supported what was, in effect, a subsidy from newcomers to legacy
customers: the type of subsidy everyone cheers.
These happy conditions no longer obtain. In the circumstances that
have coalesced lately, a grid with little residual capacity during peak
demand conditions means that a lot of new, uninterruptible demand for
power placed upon it necessitates capital spending to expand the grid.
The materials on which such an expansion is predicated have inflated in
price rapidly. Wires and cables, transformers, switchgear, and wood
poles have inflated 152 percent, 89 percent, 77 percent, and 50 percent,
respectively, since the beginning of 2019, while the overall consumer
price index recorded only 29 percent cumulative inflation in the same
period.6
The cost of financing these capital assets has also become more
expensive. Although utilities have earned generous returns on their
equity investment, their debt costs have only captured a modest premium
over Treasuries, with many utility customers paying rates that reflect
historical debt costs in the 3–4 percent range. With Treasuries well
above that today, electric utility issuances of ten- and thirty-year
debt so far in 2026 have approached 5 percent and 6 percent,
respectively. This double whammy of materials’ price inflation and
higher capital costs means that nearly every megawatt of demand added to
an American utility will incur costs that exceed the embedded, average
cost to serve the same unit. Under such circumstances, if new customers
are brought online paying the same rates as legacy customers pay, it
will axiomatically result in a cost shift from legacy customers to new
customers: the type of subsidy no one can stomach.
In the normal operations of utility regulation, that is usually what
would happen. Utilities typically have a legal obligation, in exchange
for their monopoly, to serve new customers under their prevailing rates.
New data center customers would be classified into existing “rate
classes” and begin paying the same rates as, say, a paper mill or
chemicals refiner.7
For much of the past several years, the data center industry’s hill
to die on at public utility commissions was an insistence that they
should not be treated in fundamentally different ways than other
customers. It is hard to think of a more arcane subject for outsiders to
the craft of utility regulation than the procedures by which customers
are separated into rate classes. But to long-time practitioners, this
debate raised the question of whether regulators were going to labor
under the premise that data centers were just another category of
customer that fit within the extant practices of utility ratemaking.....
