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Author: Deepak Jain

  • Crusoe’s Reported $30B Valuation Shows AI Investors Now Pay for Power Access

    Crusoe’s Reported $30B Valuation Shows AI Investors Now Pay for Power Access

    TL;DR · 30-second read

    The Short Version

    Crusoe, a company that builds the giant computer warehouses used to train and run artificial intelligence, is reportedly raising $3 billion from investors. The deal would value the company at about $30 billion.

    Crusoe’s approach is unusual. It lines up electricity first, then builds. It got its start using gas that oil wells would otherwise burn off as waste.

    Why it matters: anyone with enough money can buy computer chips. Enough electricity to run a small city is much harder to find. A price this high suggests investors see reliable power as the scarcest ingredient in the artificial intelligence boom.

    SiliconANGLE reported on July 4, 2026 that Crusoe, a developer of data centers built for artificial intelligence workloads, is raising about $3 billion in new funding at a valuation of roughly $30 billion.

    Crusoe is privately held. It develops large AI campuses, including the Abilene, Texas site built for Oracle to serve OpenAI, and it runs a cloud service that rents out computing capacity. The round would make it one of the most highly valued private companies in AI infrastructure.

    Executive Summary

    Crusoe is reportedly raising $3 billion at a $30 billion valuation. For a company whose products are data center campuses and rented computing power rather than chips or AI models, that is a very large figure. It is best understood as a price on what Crusoe has spent years assembling: sites where large amounts of electricity can be delivered on a usable schedule.

    The round matters beyond Crusoe. AI buildout is increasingly limited by how fast power can be connected to buildings, not by how fast servers can be bought. A valuation at this level shows at least one group of investors pricing that constraint directly. Utilities, equipment suppliers, rival developers and AI customers all compete for the same energized sites.

    The terms remain thin. The lead investors, the split between equity and other financing, and the use of the proceeds have not been set out publicly. Those details will determine how much the headline number actually tells us.

    What a $30 Billion Price Tag Is Actually Paying For

    Crusoe does not design its own chips or train frontier models. The graphics processors inside its buildings come from Nvidia and are available to any buyer with enough capital and patience, and so are the servers, networking gear and cooling equipment around them. What is not interchangeable is a site where hundreds of megawatts can be switched on within months. A megawatt is roughly enough electricity for several hundred homes. Many projects instead wait years in utility interconnection queues, the waiting lists for new connections to the grid.

    Crusoe has built its business around that scarce asset. The company began by generating power on site from natural gas that oil producers would otherwise flare, and it still treats energy sourcing as the first step of development rather than the last. Its flagship campus in Abilene, Texas, developed for Oracle to serve OpenAI, is planned at roughly 1.2 gigawatts, about the output of a large power plant. Without published financials, nobody outside the company can break the $30 billion figure down line by line. Still, what separates Crusoe from any well-funded buyer of GPUs is its pipeline of powered land. A valuation at this level is therefore, in substance, a price on access to energized capacity.

    Several groups feel that directly. Rival developers compete with Crusoe for the same sites near generation and transmission. Utilities receive the requests for large new loads. AI labs and cloud customers increasingly choose where to place workloads based on when capacity can go live, and less on price per rack.

    The Arithmetic of a $3 Billion Round

    If $30 billion is the post-money valuation, meaning the value after the new cash arrives, new investors would own about 10 percent of Crusoe. If it is the pre-money figure, they would own just over 9 percent. Either way, a check this large buys a fairly modest stake. That indicates investors are paying for expected future growth, not the current asset base.

    $3 billion is also small next to the cost of the campuses Crusoe builds. Once buildings, electrical equipment, cooling and computing hardware are included, a gigawatt-scale site needs financing many times that size. Crusoe developed Abilene with capital partners including Blue Owl Capital. Equity rounds in this sector usually serve as the base layer, and project debt, lease financing and joint-venture money are stacked on top of it. The reported raise is best read as the foundation for a much larger pool of capital, not as the whole of it.

    Vertical Integration Cuts Both Ways

    Crusoe owns more of the chain than a traditional colocation landlord, which typically leases space and power to tenants who bring their own equipment. Crusoe sources the energy, develops the campus, and in some cases operates the computing itself through its cloud service. That means fewer handoffs, faster delivery, and a larger share of the margin at each layer.

    It also concentrates risk. Crusoe’s best-known project is tied to a single anchor arrangement, and gigawatt-scale construction is exposed to equipment lead times, labor shortages and permitting delays. An integrated builder that also owns the chips carries both the buildings and the hardware if AI demand slows or pricing for rented computing softens. A $30 billion valuation implicitly assumes that demand holds and that Crusoe keeps delivering capacity on schedule. Both are reasonable bets, but neither is guaranteed.

    What It Signals for the Rest of the Buildout

    One funding round is not an industry trend. It does show where a significant group of investors believes the bottleneck sits. The companies most exposed to that view are the suppliers of turbines, transformers and switchgear that power-first campuses depend on. So are the utilities and pipeline operators that serve them, and the traditional data center operators who now compete with energy-led developers for land near generation.

    For enterprise and AI buyers, a well-capitalized Crusoe means another source of large-scale capacity outside the biggest cloud providers. How much that helps depends on how much of Crusoe’s future capacity is already committed to a small number of very large customers.

    Background

    Crusoe was founded in 2018 by Chase Lochmiller and Cully Cavness. It built its first business around natural gas that oil producers would otherwise flare at the wellhead, using that gas to generate electricity for computing on site. The company later moved into cloud computing for artificial intelligence and sold its bitcoin mining operations to NYDIG in 2025 to concentrate on AI infrastructure.

    Crusoe is best known as the developer of the Abilene, Texas campus built for Oracle to serve OpenAI, planned at roughly 1.2 gigawatts and developed with capital partners including Blue Owl Capital. The broader market has shifted toward what the industry calls neoclouds, specialized providers that rent GPU capacity, and toward developers that secure power before building. The reason is that grid connection timelines have become one of the main constraints on AI expansion.

    Sources

    Source: AI data center builder Crusoe reportedly raising $3B at $30B valuation (SiliconANGLE): report on Crusoe’s new funding round and valuation.

  • Two Ransomware Crews Reportedly Team Up in Joint Campaign

    Two Ransomware Crews Reportedly Team Up in Joint Campaign

    On 4 July 2026, IT Pro reported that cybersecurity experts had issued an alert describing an ‘unprecedented’ threat campaign in which two ransomware groups appear to be collaborating rather than operating independently. The public summary characterises the activity as a coordinated effort but does not, in the material available to us, name the groups, victims, sectors, or geographies involved.

    Executive Summary

    Ransomware-as-a-service crews typically compete for affiliates, victims and press attention. A public alert describing two named groups jointly running a single campaign — if it holds up on closer inspection — would mark a shift in how the extortion ecosystem organises itself, with implications for attribution, negotiation and defensive playbooks.

    For infrastructure operators, the immediate takeaway is not a specific new indicator of compromise but a reminder that the threat model is evolving faster than many incident-response runbooks. If two crews share tooling, access brokers or leak sites, defenders can no longer assume that a given intrusion set maps cleanly to a single adversary with a single playbook.

    What ‘Unprecedented’ Actually Means Here

    The word ‘unprecedented’ is doing heavy lifting in the headline. Ransomware groups have long shared infrastructure informally: affiliates rotate between programmes, initial-access brokers sell to whoever pays, and code from leaked builders (Conti, LockBit) circulates widely. What would be genuinely new is a formal, sustained partnership in which two branded operations run a single campaign end-to-end. On the public reporting available, it is not yet clear which of those descriptions best fits the activity being flagged.

    Readers should therefore treat the alert as a lead rather than a conclusion. The substantive question for defenders is whether investigators are seeing shared command-and-control, shared negotiation portals, or merely overlapping affiliates — each of which carries a different weight.

    Why Crews Would Cooperate — and Why They Usually Don’t

    Cooperation is economically rational when it lowers cost or raises the ransom take. Sharing a proven intrusion chain, splitting proceeds on high-value targets, or pooling leverage over a single victim (double-extortion with two leak sites) can all lift returns. Law-enforcement pressure since the 2021–2024 wave of takedowns has also thinned the affiliate pool, giving surviving operators an incentive to consolidate rather than compete.

    Against that, ransomware brands are jealous of reputation. A shared campaign dilutes the ‘we always decrypt’ signal that groups use to convince victims to pay, and it creates operational security risk: every extra participant is another potential informant. Historically, crews have preferred loose federation to formal alliance for exactly that reason.

    Implications for Infrastructure Buyers

    For data-centre customers, cloud tenants and connectivity buyers, the practical response does not change dramatically because two groups are named instead of one. The controls that matter — enforced multi-factor authentication, segmented backups tested for restore, privileged-access monitoring, and rehearsed incident-response contracts — apply regardless of which brand appears on the ransom note. What does change is negotiation posture: if two crews are jointly holding data, a victim cannot assume that paying one buys silence from the other.

    Insurers and legal counsel will want to understand this quickly. Cyber-insurance policies and sanctions-screening workflows are built around identifying a specific threat actor. A joint operation complicates both attribution and any regulatory obligation to check whether payment would breach sanctions.

    How to Read Alerts Like This

    Threat-intelligence alerts serve two audiences at once: defenders who need actionable indicators, and a wider readership that includes journalists, executives and — inevitably — the attackers themselves. Strong alerts publish indicators of compromise, TTPs mapped to MITRE ATT&CK, and a clear statement of confidence. Where those elements are absent from the public summary, the honest analytical response is to note the gap rather than fill it with speculation.

    Background

    Ransomware has been the dominant cyber-extortion model since roughly 2019, when double-extortion — encrypting data and threatening to leak it — became standard practice. The ecosystem is organised around branded ‘affiliate’ programmes such as LockBit, ALPHV/BlackCat, Cl0p and their successors, most of which run as ransomware-as-a-service.

    Law-enforcement operations against LockBit and ALPHV in 2023–2024, together with source-code leaks from earlier crews such as Conti, reshaped the market. Affiliates rotated between surviving programmes, new brands emerged, and researchers have periodically flagged overlaps in tooling and personnel. Against that backdrop, a claim of formal cooperation between two named crews is notable but consistent with the direction of travel.

    Source: Cyber experts issue alert after two ransomware groups team up on ‘unprecedented’ threat campaign — IT Pro report, 4 July 2026, describing a joint ransomware campaign flagged by security researchers.

  • Heat Wave and Data Center Demand Push PJM Grid to the Brink in Northern Virginia

    Heat Wave and Data Center Demand Push PJM Grid to the Brink in Northern Virginia

    The Prince William Times reported on July 4, 2026 that a summer heat wave, layered on top of the enormous electricity appetite of the region’s data centers, pushed the regional power grid “to the brink.” The grid in question is operated by PJM Interconnection, the regional transmission organization that coordinates electricity across all or parts of 13 states and the District of Columbia — including Northern Virginia, home to the largest concentration of data centers in the world.

    The report frames a collision that grid planners have warned about for years: weather-driven peak demand from air conditioning arriving at the same moment as a structural, around-the-clock load from data centers that has grown far faster than new generation and transmission have been built.

    Executive Summary

    According to the report, the stress event unfolded in Prince William County, Virginia and the surrounding region — the heart of “Data Center Alley,” where Prince William and neighboring Loudoun County host an unmatched density of hyperscale and colocation facilities. During a heat wave, residential and commercial air conditioning drives electricity demand to its annual peaks; data centers, unlike air conditioners, draw near-constant power day and night, so their load sits underneath the weather peak rather than replacing it.

    Why it matters: grid operators plan for the single worst hour of the year. When a fast-growing baseload (data centers) raises the floor and a heat wave raises the ceiling, the margin between available supply and peak demand — the buffer that prevents emergency measures like conservation appeals or rolling outages — shrinks. A “to the brink” event is a concrete, dated data point in a debate that is often conducted in abstractions about future AI load forecasts.

    A caveat on sourcing: this is a single local-newspaper account, and the headline-level material available does not specify which emergency procedures, if any, PJM invoked, what demand peaked at, or how close reserves actually came to exhaustion. Those specifics matter, and we flag them below.

    The Peak Problem: Flat-Out Air Conditioning Meets Always-On Compute

    Electric grids are sized for their worst hour, not their average one. In PJM territory that worst hour almost always occurs on a hot summer weekday afternoon, when tens of millions of air conditioners run simultaneously. Data centers change the arithmetic because they are effectively a new floor under demand: a large AI training or cloud facility draws a high, steady load 24 hours a day, in fair weather and foul. When a heat wave arrives, that steady draw does not politely step aside — it stacks. The result is that the same heat wave that a decade ago would have been routine can now push a region toward its limits, which is precisely the dynamic the Prince William Times describes.

    For lay readers, “to the brink” typically means the grid operator is working through its escalation ladder — asking generators to defer maintenance, importing power from neighbors, calling on demand-response customers who are paid to curtail, and in the worst case shedding load (rolling blackouts). The available reporting does not tell us how far down that ladder PJM went in this event, and that distinction — between a tight day and a genuine emergency — is the difference between a warning sign and a crisis.

    Northern Virginia Is the Stress Test the Rest of the Country Is Watching

    Prince William County is not a random dateline. Northern Virginia is the world’s largest data center market, and the AI buildout has accelerated demand there just as it has become harder to site new transmission lines and generation. PJM’s own capacity auctions — the mechanism by which the operator procures commitments of future power supply — have cleared at sharply higher prices in recent cycles, a market signal that supply is not keeping pace with projected demand. A heat-wave near-miss in this region is therefore a preview: other fast-growing data center corridors in Texas, Georgia, Ohio, and Arizona face versions of the same squeeze.

    The economics cut in several directions. Utilities and independent power producers benefit from higher capacity prices and large, creditworthy new customers. Data center operators face rising power costs and, increasingly, multi-year waits for grid connections — which is pushing some toward on-site generation, long-term nuclear and renewable contracts, and demand-flexibility commitments. Residential ratepayers, meanwhile, worry about absorbing the cost of grid upgrades driven by industrial customers, a tension that is now a live political issue in Virginia and across PJM’s footprint.

    Who Bears the Risk — and Who Blinks First in the Next Heat Wave

    Events like this sharpen a policy question that regulators have so far answered only partially: when supply gets tight, whose power is interruptible? Data centers have historically demanded — and paid for — extreme reliability, backed by on-site diesel or battery backup. That backup capacity is mostly idle during grid emergencies. Proposals to enroll data centers in demand-response programs, require flexible-load commitments as a condition of interconnection, or price peak consumption more aggressively all gain momentum every time a grid operator has a bad afternoon.

    There is also a reputational dimension. The data center industry argues, with some justification, that it pays substantial sums into the grid and that load growth also comes from electrification of homes, vehicles, and factories. But headlines that pair “heat wave” with “data centers” and “brink” land hard with the public regardless of the precise load attribution. Operators that can document flexibility — shifting deferrable computing work away from peak hours, dispatching backup assets to support the grid — will have an easier time in siting battles than those that cannot.

    Background

    Northern Virginia became the world’s data center capital over two decades, thanks to early internet exchange points, cheap land, favorable tax treatment, and proximity to federal and enterprise customers. Loudoun County led the first wave; Prince William County became the frontier of the next one, with the AI boom driving proposals for ever-larger campuses. PJM Interconnection, formed from a power pool dating to 1927, operates the transmission grid across the Mid-Atlantic and parts of the Midwest and has repeatedly flagged accelerating load growth — led by data centers — as a central reliability challenge of the coming decade.

    The tension surfaced well before this heat wave: PJM’s recent capacity auctions cleared at dramatically higher prices, utilities in Virginia have proposed new rate structures for large loads, and local land-use fights over data center siting in Prince William County have become some of the most contentious in the country. A dated, weather-driven stress event adds an operational exclamation point to what had largely been a forecasting debate.

    Source: Heat wave, data centers’ huge demand push regional power grid to the brink — Prince William Times, July 4, 2026, reporting on grid strain in the PJM region amid a heat wave and data center load growth.

  • China Switches On the First Commercial Underwater Data Center

    China Switches On the First Commercial Underwater Data Center

    China has brought online what is being described as the world’s first commercial underwater data center, according to a report published July 4, 2026 by the Spanish outlet OkDiario. The facility submerges sealed server modules in the ocean and uses the surrounding seawater as its cooling medium, an approach the report says sharply reduces the energy the facility consumes.

    The report frames the launch as a template other coastal regions could adopt, naming Cartagena, Spain as the kind of Mediterranean port city where the model might be replicated. It does not disclose the operator, the facility’s capacity, or its precise location.

    Executive Summary

    The announcement matters because it moves underwater data centers from experiment to product. Submerging servers has been tested before — most famously by Microsoft — but a commercial deployment means paying customers are expected to run real workloads on seabed infrastructure, and that changes the questions from “does it work?” to “does it pencil out?”

    The core appeal is cooling. Keeping servers from overheating is one of the largest energy costs in any data center, and the deep ocean offers a vast, stable heat sink at no mechanical-chilling cost. If seawater cooling delivers the efficiency the concept promises at commercial scale, it would arrive at a moment when AI-driven demand has made power and cooling the industry’s tightest constraints.

    That said, the source report is brief and light on specifics. It attributes no capacity figures, energy metrics, customer names, or operator details. The launch is a genuine milestone in cooling infrastructure if the commercial framing holds — but the evidence available in this report is a claim of a first, not a documented performance record.

    Why Put Servers on the Seabed?

    Data centers spend an enormous share of their electricity not on computing but on removing the heat that computing generates. The industry measures this with PUE — power usage effectiveness, the ratio of total facility power to the power that actually reaches IT equipment. Conventional air-cooled facilities need chillers, fans, and often large volumes of water to hold safe temperatures, and in hot climates that overhead climbs steeply.

    The ocean solves the problem passively. Below the surface, water temperature is low and remarkably stable year-round, and water conducts heat far better than air. A sealed capsule on the seabed can reject heat directly into an effectively unlimited sink, eliminating most mechanical cooling. Subsea deployment also removes evaporative water consumption — a growing point of friction between data centers and the communities that host them — and seabed real estate near dense coastal cities is not competing with housing or industry the way urban land is.

    From Microsoft’s Experiment to Chinese Commercialization

    The concept is not new; the commercial claim is. Microsoft’s Project Natick sank a sealed server vessel off Scotland’s Orkney Islands from 2018 to 2020 and reported that the submerged servers failed at a fraction of the rate of an equivalent land-based control group — likely because the nitrogen-filled, human-free capsule eliminated oxygen corrosion, humidity swings, and accidental knocks. Microsoft judged the experiment a technical success but never turned it into a product. China, meanwhile, has been running underwater data center pilots off its own coast for several years, so a progression from pilot to commercial service there is consistent with the trajectory — even though this report does not name the company involved.

    If the commercial characterization is accurate, China would be first to market with a technology a US hyperscaler proved and shelved. That is a familiar pattern in infrastructure: the economics that don’t fit one company’s portfolio can fit another market’s constraints, particularly where coastal land, grid capacity, and water for cooling are all scarce at once.

    The Hard Economics of Subsea Capacity

    The obstacles are as real as the appeal. A submerged module cannot be serviced by a technician; a failed component stays failed until the entire vessel is raised, which pushes operators toward redundant hardware and infrequent, expensive retrieval cycles. Marine engineering, corrosion-resistant housings, subsea power and fiber connections, and specialized deployment vessels all add capital cost that the cooling savings must repay. Insurance, uptime guarantees, and repair logistics for seabed assets are largely uncharted territory for enterprise customers used to walking their auditors through a facility.

    Environmental questions also need honest accounting. Rejecting heat into the ocean is thermodynamically unavoidable here, and while small-scale trials such as Natick reported minimal localized warming, the effect of dense clusters of commercial modules on marine ecosystems is site-specific and largely unstudied. Coastal permitting regimes — fisheries, shipping lanes, protected habitats — will shape where this model can actually go, and the report offers no detail on how the Chinese deployment cleared those hurdles.

    Could Cartagena Be Next?

    The report’s suggestion that coastal cities like Cartagena could follow is speculation, not an announced project, and it is worth being clear about that distinction. Still, the logic of the shortlist is sound: Mediterranean port cities combine dense populations that want low-latency services, constrained urban land and grids, warm climates that make conventional cooling expensive, and immediate deep water. Those are precisely the conditions under which subsea capacity is most competitive against land-based builds.

    For European adoption, the gating factors would be EU environmental review, marine-spatial-planning approvals, and — not least — the geopolitics of importing a Chinese-proven infrastructure model into European digital sovereignty debates. Any operator pursuing it would more likely license the concept or develop it independently than deploy Chinese-operated modules in EU waters.

    Background

    Underwater data centers trace to Microsoft’s Project Natick, which began with a proof-of-concept in 2015 and culminated in a sealed vessel of several hundred servers operating off Scotland from 2018 to 2020. The retrieved servers had failed at a small fraction of the rate of an identical land-based group, validating the reliability case — but Microsoft ended the program without a commercial product. China picked up the thread with coastal pilot deployments in the years that followed, pursuing subsea capacity as an answer to scarce coastal land, strained grids, and the water consumption of conventional cooling.

    The timing is not incidental. By 2026, explosive AI demand had made electricity and cooling the data center industry’s defining bottlenecks worldwide, pushing operators toward liquid cooling, novel sites, and any design that cuts overhead energy. A commercial subsea launch is China staking a claim to one of those frontiers first.

    Source: China just switched on the first underwater data center, cooling servers with the ocean to slash energy use, and coastal cities like Cartagena could be next — OkDiario report, July 4, 2026, on China’s launch of the first commercial seawater-cooled underwater data center.

  • CISA’s $2.45M ANCHOR-CI Gives AI Data Centers a Door, Not a Guaranteed Seat

    CISA’s $2.45M ANCHOR-CI Gives AI Data Centers a Door, Not a Guaranteed Seat

    TL;DR · 30-second read

    The Short Version

    The United States’ main cyber-defense agency has set up a new network of private meeting groups. In them, power companies, water utilities, telecom firms and other operators of essential services can trade warnings about hackers and physical threats with government officials.

    It costs about $2.45 million a year and has up to eight federal staff. That is a small team for the whole country.

    Why it matters: the giant computer warehouses that run artificial intelligence do not fit neatly into any existing group. They will have to organize themselves to get a voice.

    The U.S. Cybersecurity and Infrastructure Security Agency (CISA) has formed the Alliance of National Councils for Homeland Operational Resilience–Critical Infrastructure (ANCHOR-CI), Industrial Cyber reported on July 2, 2026. ANCHOR-CI is an advisory framework chartered by the Department of Homeland Security (DHS) that brings government and critical infrastructure owners and operators together to share sensitive threat information and develop security and resilience recommendations.

    The framework allows four kinds of councils: sector, cross-sector, industry and regional. It is exempt from the Federal Advisory Committee Act, so all eligible meetings are closed to the public. It will run for an initial two years at an estimated annual operating cost of $2.45 million, funded by CISA, covering up to eight full-time federal employees. DHS set out the council’s composition in a Federal Register notice.

    Executive Summary

    ANCHOR-CI restores a confidential, structured channel between the federal government and the companies that run the country’s power grids, networks, water systems and other essential services. Councils will review the threat environment, discuss vulnerabilities and send recommendations to DHS through CISA. DHS Secretary Markwayne Mullin called the framework “a game changer in how the public and private sectors collaborate and share information.”

    The structure matters more than the rhetoric. Sector councils follow federally designated sectors. A new category of industry councils, along with explicit room for “emerging industries and technologies not aligned with a specific critical infrastructure sector,” creates a possible route for operators that fall between sectors. AI data centers are the most prominent example. That route is permissive rather than guaranteed, and a lean federal budget means much of the organizing is likely to fall to industry itself.

    For power and data-center operators, ANCHOR-CI creates no new rules. It creates access: a closed room where threat intelligence and operational concerns can be shared candidly, and where the recommendations DHS receives get shaped.

    A Closed-Door Forum Returns

    The most consequential line in the announcement is the exemption from the Federal Advisory Committee Act. That 1972 law generally requires federal advisory bodies to meet in public and publish their records. Because ANCHOR-CI is exempt, its councils can meet privately, and every eligible meeting will. For operators, that is the point. A utility is unlikely to describe a weakness in its substation controls in a room that ends up in the public record. The same goes for a data-center operator describing an intrusion attempt on its building-management systems.

    The framework also fills a gap. In early 2025, DHS ended the Critical Infrastructure Partnership Advisory Council (CIPAC), the earlier exempt forum through which industry-led sector coordinating councils met government counterparts. ANCHOR-CI is described as building on that previous structure while widening who can take part. The practical test is how quickly the new rooms fill. Only councils with an approved charter and a balanced membership list may hold meetings, so the forum exists on paper before it exists in practice.

    Closed meetings carry a cost that deserves a fair hearing. The councils’ output is advice and recommendations delivered to DHS through CISA, and the public will not see the deliberations behind them. The trade-off is not new, since the prior forum worked the same way. It does, however, put weight on how CISA reports what it does with the advice it receives.

    Why AI Data Centers Get a Door, Not a Seat

    Sector councils are organized around federally designated sectors. Data centers have no designated sector of their own. These warehouse-scale buildings house the servers that train and run AI models. Their computing equipment falls under information technology and their fiber links under communications, and their fast-rising electricity demand makes them a major customer of the energy sector. This applies to a hyperscaler, one of the few cloud giants that build their own campuses. It also applies to a colocation provider, a landlord that rents space, power and cooling to many tenants. For both, security concerns can end up split across several tables.

    ANCHOR-CI adds two mechanisms that could change this. First, Critical Infrastructure Industry Councils may be created for industries that “manage or control critical systems and assets but do not fit neatly within existing sector structures.” Second, membership can extend to entities from emerging industries and technologies not aligned with a specific sector. Cross-sector councils, meanwhile, are designed for exactly the interdependencies where a large AI campus and the grid that feeds it share risk.

    The operative word is “may.” An industry council is permitted, not promised. Membership outside the defined categories is at the discretion of the council or the CISA director. No council can meet until its charter is approved and its membership balanced. Nothing in the announcement names data centers or AI computing as a priority. The framework opens a door for them. Getting a seat will depend on whether operators and their trade associations put forward a credible, balanced council.

    $2.45 Million and Eight Staff: Industry Carries the Load

    CISA estimates ANCHOR-CI’s annual operating cost at $2.45 million. That covers administrative expenses, contract support and up to eight full-time federal employees, and excludes extras such as invitational travel. A full-time Designated Federal Officer must approve agendas, attend every meeting and ensure minutes are produced. That is a lean federal footprint for a framework that allows four council types spanning every designated sector plus regional and cross-sector bodies.

    The likely consequence is that much of the work of convening councils, drafting recommendations and sustaining momentum will fall to members. Non-federal participants are unpaid, may be required to sign non-disclosure agreements, and serve for two-year charter terms. For a utility or data-center operator, joining means committing senior security and operations staff time without compensation. Large firms can absorb that cost more easily than rural cooperatives or small regional operators, which are the participants the regional councils are meant to bring in.

    What Changes for Power and Data-Center Operators

    For utilities, grid operators and data-center owners, ANCHOR-CI changes the venue rather than the rules. It adds no security requirement and no reporting mandate. What it changes is access: a confidential channel for sharing threat information with government, hearing what agencies are seeing, and shaping the recommendations DHS receives.

    Regional coordinating councils may matter most where AI buildout and grid strain meet locally. Many new data-center campuses are being built wherever power can be secured, including in rural areas. The framework explicitly aims to give rural infrastructure entities a voice in national resilience planning. Operators should watch whether a regional council actually forms in a data-center corridor during the initial two-year term.

    Background

    CISA is the federal agency responsible for coordinating the security and resilience of U.S. critical infrastructure: the systems whose disruption would harm national security, the economy or public safety. That infrastructure is divided into federally designated sectors, sixteen under long-standing federal policy, including energy, communications, information technology and water. For years, industry-led Sector Coordinating Councils and their government counterparts, Government Coordinating Councils, met through the Critical Infrastructure Partnership Advisory Council, a closed forum that DHS ended in early 2025.

    Data centers have become central to that landscape without fitting neatly into it. The rapid buildout of AI computing has turned them into some of the largest new electricity customers on the grid and core dependencies for nearly every other sector. Yet they have no designated sector of their own. ANCHOR-CI’s industry and cross-sector councils are the framework’s answer to infrastructure that sits between the lines.

    Sources

    Source: CISA launches ANCHOR-CI to strengthen critical infrastructure security and resilience, improve cyber coordination, Industrial Cyber’s report on the new DHS-chartered advisory council framework for critical infrastructure operators.

  • Two Homeowners’ Suit Shows How Nebius’s AI Build Schedule Can Hinge on a Local Court

    Two Homeowners’ Suit Shows How Nebius’s AI Build Schedule Can Hinge on a Local Court

    TL;DR · 30-second read

    The Short Version

    Two homeowners in Birmingham, Alabama, have sued to stop construction of a large computer center being built by Nebius, a company that rents out the computing power behind artificial intelligence tools.

    They say the city never properly approved it, and that the building work has already brought noise, shaking, dust, heavy trucks and damage to one home. They want the work stopped, the permits cancelled and money for the harm.

    Why it matters: two neighbors and one local court could now affect when the project is finished. The first judge stepped aside, so another will be picked at random.

    Two homeowners living near the Nebius AI data center under construction in Birmingham, Alabama, have filed a lawsuit asking a court to halt the work, ABC 33/40 (WBMA) reported on July 2, 2026. The suit claims the project was never properly approved under the city’s zoning rules. It also challenges Birmingham’s new data center ordinance and alleges that construction has already caused noise, vibrations, dust, heavy truck traffic and damage to one home.

    The homeowners are asking the court to stop construction, void the project’s permits and award damages. The judge originally assigned to the case has recused herself, and the case will be randomly reassigned to another Jefferson County judge.

    Executive Summary

    On its face this is a local zoning dispute. The relief it seeks, however, reaches the core of the project: a halt to construction and the voiding of the permits the site is being built under. A data center is a building packed with servers, power and cooling equipment, and it cannot be finished without valid permits. A successful challenge would therefore send the project back through approvals rather than simply attach conditions to it.

    The suit also targets Birmingham’s new data center ordinance, the rulebook the city wrote for exactly this kind of facility. That widens the stakes beyond one site. If the ordinance itself is found wanting, other projects that rely on it inherit the uncertainty. For Nebius, a provider of GPU cloud capacity (rented access to the graphics processors that train and run AI models), the practical question is schedule: when the building can start delivering capacity. That question now partly sits with a Jefferson County court.

    The homeowners’ allegations are claims in a complaint, not findings. The court has not yet ruled on any of them.

    How Two Plaintiffs Can Reach an Entire Build Schedule

    Only two people have sued, but the leverage in a zoning case does not come from headcount. It comes from what is asked for. The homeowners want three things: damages, the voiding of the project’s permits, and a halt to construction. Damages are money and do not by themselves change the schedule. The other two can. An order stopping work idles crews and equipment on a site where power, cooling and hardware installation are sequenced in advance. Voided permits would mean re-establishing approvals before work could resume.

    The legal theory matters as much as the relief. The suit claims the project was never properly approved under the city’s zoning rules. If that argument succeeds, the problem lies in the approval itself rather than in how the site is being run. A developer cannot fix an approval problem by changing site practices. It has to be cured through the municipal process, which runs on the city’s calendar rather than the developer’s.

    The recusal adds a procedural step at the outset. The case now goes to another Jefferson County judge chosen at random. Until that judge takes the case and addresses the request to stop construction, whether work continues is an open question. The exposure runs to Nebius, its contractors, any customers expecting capacity from the site, and the City of Birmingham, whose approval is being challenged.

    An Ordinance Challenge Is a Risk for More Than One Site

    A data-center-specific ordinance normally gives developers certainty. It tells them what the city requires and what an approved project looks like. By challenging Birmingham’s new ordinance directly, the homeowners are contesting that certainty, not just this one application of it.

    That puts the city in the position of defending both its approval of this project and the framework behind it. The outcome will signal to any developer weighing Birmingham whether the ordinance is a stable path to a permit or a contested one. A ruling that upholds the ordinance would strengthen it. A ruling against it would leave projects approved under it asking whether they need to revisit their approvals.

    The same scrutiny applies to both sides. The homeowners’ zoning claim will stand or fall on the text of the ordinance and the approval record, which a court has not yet examined. The city’s and developer’s position that the project was properly approved faces the same test.

    Construction Impacts Are the Part a Developer Controls

    The nuisance allegations are noise, vibrations, dust, heavy truck traffic and damage to one home. They are a different kind of claim from the zoning challenge, because they concern how the site is being built, not whether it should be. That also makes them the category a developer can most directly address. Typical tools include truck routing and working-hours limits, dust suppression, vibration monitoring, and surveys of neighboring structures before and during construction.

    The claim of damage to a home is specific, and whether construction caused it is a factual question that evidence can settle either way. Assurances that a site is being built responsibly are testable in the same way, through measurements and records.

    For a neocloud, schedule is effectively part of the product. Nebius and its peers compete on how quickly they can bring GPU capacity online for AI developers, so a site that delivers late is a commercial problem, not only a construction one. That is why a two-plaintiff local suit deserves attention from people who track Nebius’s buildout: the case controls no chips or power, but it can affect the date the building is ready to use them.

    Background

    Nebius Group is an AI infrastructure company headquartered in Amsterdam and listed on Nasdaq. It emerged in 2024 from the restructuring of Yandex N.V., which sold its Russian businesses and kept its international operations. Nebius builds and operates data centers and sells GPU cloud capacity to AI developers. That makes it one of the so-called neoclouds, specialist providers that compete with the largest cloud platforms for AI computing work.

    Its data center project in Birmingham, Alabama, has been locally controversial. Birmingham has adopted a new ordinance specifically governing data centers. That ordinance is now under legal challenge in Jefferson County alongside the Nebius project’s approvals.

    Sources

    Source: Homeowners file lawsuit against Nebius AI data center, judge recuses herself. ABC 33/40 (WBMA) reports on two homeowners’ suit to halt construction of the Nebius data center in Birmingham and the original judge’s recusal.

  • DOE Orders Data Centers to Backup Power to Free Grid for AC

    DOE Orders Data Centers to Backup Power to Free Grid for AC

    The U.S. Department of Energy issued a directive on or around July 3, 2026 instructing data centers to switch to on-site backup generators during an active heat wave, so that grid electricity could be redirected to residential and commercial air conditioning demand.

    The action, first reported by CNN, applies during the peak-load emergency window and treats hyperscale and colocation facilities as flexible load that can be temporarily islanded from the public grid.

    Executive Summary

    Federal regulators rarely intervene directly in how private data centers source their power. This order does exactly that, framing backup generators — normally reserved for outages — as a demand-response tool the government can call on during a grid emergency.

    For an industry that has spent the past two years defending its rising share of national electricity consumption, the directive is a concrete signal that data-center load is now large enough to be actively managed by policymakers, not just utilities. It also raises immediate questions about emissions, fuel supply, wear on generator fleets, and who bears the incremental cost.

    The CNN report is short on operational specifics. What is clear is the precedent: in a heat-driven grid crunch, the federal government has publicly told data centers to burn their own fuel so households can keep the AC on.

    From Backup to Balancing Asset

    Data-center backup generators — typically diesel, occasionally natural gas — are designed as insurance against utility failure. Running them proactively to relieve the grid reframes them as a demand-response resource, a category more commonly filled by industrial curtailment contracts and battery storage. The DOE’s move effectively conscripts private infrastructure into a public reliability role during an emergency window, without (based on the reporting available) a pre-existing market mechanism to compensate that role.

    For operators, the economics are straightforward but uncomfortable: diesel fuel and generator hours are far more expensive per kilowatt-hour than grid power, and every runtime hour consumes maintenance life and emissions allowances. Whether those costs are reimbursed, absorbed, or passed to tenants under force-majeure or emergency-operations clauses in colocation contracts is not addressed in the source.

    Policy Signal for a Power-Constrained Industry

    The directive lands in the middle of an ongoing national debate over data-center power draw, particularly from AI training and inference workloads. Utility interconnection queues are years long in several regions, and multiple states are weighing tariffs and rate structures specific to large loads. An emergency order that pulls data centers off the grid on the hottest days does not solve those structural issues, but it does establish a template: when residential cooling and industrial compute compete for the same electrons, households come first.

    That template has implications well beyond one heat wave. Operators planning new sites will read this as evidence that federal and state authorities are willing to treat their facilities as interruptible when the public interest demands it, which strengthens the case for on-site generation, long-duration storage, and firm behind-the-meter power. It also gives ammunition to utilities and community groups arguing that new hyperscale campuses should arrive with dedicated generation, not just a grid connection.

    Environmental and Reliability Trade-offs

    Shifting large facilities to diesel or gas backup during a heat wave trades one problem for another. Peak summer conditions already coincide with elevated ground-level ozone; concentrated diesel runtime in data-center clusters — northern Virginia, Dallas, Phoenix, Santa Clara — could measurably worsen local air quality on precisely the days when it is most fragile. The source does not indicate whether the order includes air-quality carve-outs, geographic targeting, or emissions monitoring.

    Reliability is the other side of the ledger. Backup generators are tested regularly but not designed for sustained multi-hour or multi-day operation across an entire fleet. Fuel logistics, cooling of the generators themselves in extreme heat, and the risk of cascading failure if a facility loses backup mid-event are real engineering concerns. None of these are discussed in the reporting available, and they will determine whether the directive is remembered as a pragmatic success or a stress test that exposed hidden fragility.

    Background

    Data-center electricity demand has climbed sharply over the past several years as cloud computing and, more recently, AI training and inference workloads have expanded. Utilities in Virginia, Texas, Arizona, and the Pacific Northwest have publicly flagged multi-year interconnection queues for large loads, and several states have opened proceedings on tariffs and cost allocation specific to hyperscale facilities.

    At the same time, summer heat waves have repeatedly pushed regional grids to the edge of their reserve margins, prompting conservation appeals and, in some cases, rolling outages. The DOE has authority to intervene in electricity emergencies but historically uses it sparingly and mostly to keep specific generators running. A directive aimed at reducing data-center load is a notable inversion of that pattern.

    Source: Energy Dept. directs data centers to use backup generators during heat wave, freeing up power for AC – CNN — CNN reports the DOE ordered data centers onto backup power during a July 2026 heat wave to relieve grid demand for air conditioning.

  • WSJ: AI Data Centers’ Water Use Far Exceeds What Tech Giants Disclose

    WSJ: AI Data Centers’ Water Use Far Exceeds What Tech Giants Disclose

    The Wall Street Journal published an investigation on July 3, 2026, reporting that AI data centers consume far more water than most major technology companies publicly acknowledge. The reporting targets the gap between the industry’s sustainability disclosures and the actual water draw of the facilities powering the AI boom — a gap with direct consequences for the communities, utilities, and regulators hosting these sites.

    Executive Summary

    According to the Journal’s headline finding, the water consumed by AI data centers substantially exceeds the figures most tech giants report. That claim lands at a sensitive moment: hyperscale operators are racing to build AI capacity at unprecedented scale, and many of the fastest-growing markets for that capacity are in water-stressed regions where every megawatt of cooling has a hydrological cost.

    The significance is less about any single number and more about trust in the measurement system itself. Data center operators have spent a decade building sustainability reporting frameworks — water usage effectiveness metrics, replenishment pledges, “water positive” targets. An investigation asserting that disclosed figures materially understate real consumption challenges the credibility of that entire apparatus, and will sharpen scrutiny from permitting authorities, investors, and enterprise customers alike. It is worth noting up front that the material available at publication is the Journal’s headline claim; the underlying methodology and company-by-company figures sit behind the investigation itself, so our analysis focuses on how such a gap can exist and what it would mean if borne out.

    Why Water Is the AI Boom’s Quiet Constraint

    Data centers use water primarily for cooling. Evaporative systems — the most energy-efficient way to reject heat in many climates — work by evaporating water to carry heat out of the building, which means the water is genuinely consumed rather than borrowed and returned. AI workloads intensify this: training and inference clusters pack far more power into each rack than traditional enterprise computing, and every kilowatt of electricity ultimately becomes heat that must go somewhere.

    Power availability has dominated the AI infrastructure conversation, but water is the constraint that most directly touches neighbors. A community can rarely see the grid strain a campus causes; it can see reservoir levels, well permits, and municipal supply contracts. That visibility is why water — more than carbon — has become the flashpoint in local data center opposition, and why a disclosure gap, if substantiated, matters commercially and not just reputationally.

    How a Disclosure Gap Can Exist Without Anyone Lying

    Water accounting has honest ambiguities that reporting can exploit or obscure. “Withdrawal” (water taken in) and “consumption” (water evaporated and lost) are different numbers. On-site cooling water is different from the much larger volumes evaporated at the power plants generating a facility’s electricity — a burden that rarely appears in corporate water figures. Companies may report global averages that dilute stress in specific basins, disclose only company-owned sites while leasing heavily from colocation providers, or treat site-level data as a trade secret in agreements with local utilities.

    Each choice can be individually defensible and collectively misleading. If the Journal’s investigation shows real draw far above disclosed figures, the likeliest mechanism is not fabrication but selective scope: what gets counted, where, and at what level of aggregation. That is precisely why the methodology on both sides deserves scrutiny — an investigation comparing utility records of total withdrawal against corporate disclosures of net consumption would find a large gap even where reporting is technically accurate. Neither the companies’ frameworks nor the investigation’s comparisons should be taken on trust without seeing definitions aligned.

    Winners, Losers, and the Coming Transparency Squeeze

    If disclosure practices tighten — voluntarily or by mandate — the advantage shifts to operators who engineered for water frugality before it was scrutinized: closed-loop liquid cooling, dry coolers, air-side economization in suitable climates, and treated wastewater sourcing. Vendors of direct-to-chip and immersion cooling gain a stronger sales narrative, since liquid cooling at the rack can pair with water-free heat rejection outside. Operators dependent on open evaporative cooling in arid, fast-growing markets face the hardest repricing, because retrofits are costly and permitting timelines are long.

    Enterprise buyers and investors are the other lever. Cloud and colocation contracts increasingly carry sustainability reporting clauses, and a credible investigation gives procurement teams grounds to demand site-level water data rather than glossy aggregates. For host communities, the practical effect is likely to be harder-edged development agreements: metered disclosure requirements, drought curtailment provisions, and consumption caps as conditions of approval. The industry can resist that trend or get ahead of it; the second option is cheaper.

    Background

    Water has trailed energy as the second axis of data center sustainability for over a decade. Major operators publish water metrics alongside “water positive” replenishment pledges — commitments to restore more water to stressed basins than their operations consume. Those frameworks were designed in the era of conventional cloud computing; the AI buildout that accelerated from 2023 onward brought far denser facilities, faster construction, and expansion into hot, dry regions where land and power are cheap but water is contested.

    Local friction has grown in step. Communities from the American Southwest to Europe and Latin America have challenged data center water allocations, and operators have responded with a mix of reclaimed-water sourcing, liquid cooling adoption, and — critics argue — selective disclosure. The Journal’s investigation lands squarely on that last point, testing whether the industry’s reported numbers describe the facilities actually being built.

    Source: AI Data Centers Use Far More Water Than Most Tech Giants Report — Wall Street Journal investigation, July 3, 2026, as syndicated via Google News.

  • Texas Tops the Nation in Proposed Gas Plants for Data Centers

    Texas Tops the Nation in Proposed Gas Plants for Data Centers

    Texas now leads the United States in proposed natural gas power plants intended to serve data centers, according to reporting by the Texas Tribune published July 2, 2026. The report notes that the proposed plants would emit large amounts of greenhouse gases if built.

    The finding places Texas at the center of a national trend: as AI-driven data center demand outpaces what existing grids can deliver, developers are increasingly proposing dedicated, on-site or co-located gas generation rather than waiting in utility interconnection queues.

    Executive Summary

    The Texas Tribune’s July 2026 reporting identifies Texas as the top state for proposed power plants tied to data centers — and specifically flags the greenhouse gas consequences of that pipeline. The headline fact is simple but significant: the AI infrastructure boom is no longer just a real estate and chip story; it is a power generation story, and Texas is where the most new fossil-fueled capacity is being proposed to feed it.

    Why it matters: data centers historically plugged into the existing grid and bought power like any other large customer. The scale of AI campuses — often requiring hundreds of megawatts each, comparable to a small city — has flipped that model. Developers are now proposing their own gas plants, or pairing with generation developers, to guarantee power on their construction timelines. That accelerates buildout but shifts emissions, siting, and reliability questions onto communities and regulators who are still catching up.

    For the infrastructure industry, the report is a signal of where the market has moved: speed-to-power is the binding constraint on AI capacity, and Texas — with its independent grid, comparatively fast permitting, and abundant natural gas — has become the path of least resistance.

    Why Texas Became the Epicenter of the Gas-for-AI Buildout

    Texas offers a combination no other state matches: an independent grid operated by ERCOT (the Electric Reliability Council of Texas, which runs the grid for most of the state outside federal interconnection oversight), a deregulated energy-only power market, in-state natural gas supply from the Permian Basin, and a permitting culture that moves faster than most coastal states. For a data center developer whose customers are demanding capacity in 18–24 months rather than the five-plus years a utility interconnection can take, those attributes translate directly into revenue.

    The result the Tribune documents — Texas leading the nation in proposed data-center power plants — is the logical endpoint of that competition. When the grid cannot deliver power fast enough, developers bring their own. Natural gas turbines are the default choice because they are dispatchable (they run whenever needed, unlike weather-dependent wind and solar) and can be ordered, sited, and built faster than nuclear, though turbine order backlogs have become their own bottleneck industry-wide.

    The Emissions Trade-Off Behind the AI Boom

    The Tribune’s framing highlights the tension the industry has been navigating for two years: the same hyperscale companies that made aggressive carbon-neutrality pledges are now, directly or through partners, driving a wave of new fossil-fueled generation. Gas plants emit roughly half the carbon dioxide of coal per unit of electricity, but a large fleet of new gas capacity running at high utilization to serve round-the-clock compute loads still represents a substantial, long-lived emissions commitment — these plants typically operate for 30 years or more.

    This does not mean the criticism writes itself in only one direction. Proponents argue that new, efficient gas capacity can displace older, dirtier generation, firm up a grid that is adding record amounts of solar and storage, and that some proposed plants may be bridge solutions later paired with carbon capture or displaced by nuclear. Those arguments deserve scrutiny too: bridge claims are only as good as the retirement and conversion commitments behind them, and the release-level reporting here does not indicate such commitments exist for the Texas pipeline.

    What a Proposal Pipeline Does — and Does Not — Tell Us

    A crucial caveat for readers: “proposed” is doing heavy lifting in this story. Power plant proposal pipelines everywhere are inflated by speculative filings — developers reserve interconnection positions, file air permits, and announce projects to attract customers and capital, and a meaningful fraction never get built. The same phenomenon inflates data center announcement figures. Texas leading in proposals confirms where developer intent is concentrated; it does not tell us how many megawatts will actually enter service, or when.

    That said, the direction is unambiguous. Even a partial realization of the Texas pipeline would reshape the state’s power market — affecting gas demand, electricity prices for other consumers, water use for cooling, and ERCOT’s planning assumptions. Texas legislators have already responded to large-load growth with new interconnection and curtailment rules for big electricity users, a sign that regulators expect the trend to persist.

    Winners, Losers, and the Competitive Map

    The near-term winners are clear: gas turbine manufacturers with multi-year order books, midstream companies moving Permian gas, engineering and construction firms, and landowners in transmission-adjacent counties. Data center operators who secure firm power early gain a genuine moat, because speed-to-power — not land or capital — is currently the scarcest input in AI infrastructure.

    The open question is who bears the costs. Residential and industrial ratepayers may face higher prices if large loads strain the system faster than supply arrives; communities near proposed plants absorb local air-quality and water impacts; and operators themselves carry stranded-asset risk if AI demand forecasts prove overbuilt or if more efficient chips and models bend the power curve downward. Competing states — Virginia, Georgia, Ohio, Arizona — are watching whether Texas’s speed advantage outweighs its grid-reliability reputation, still shadowed by the 2021 winter storm failures.

    Background

    Texas has spent two decades building a reputation as the country’s most market-driven electricity system: ERCOT runs an energy-only market with no capacity payments, the state leads the nation in wind generation and has surged in utility-scale solar and batteries, and its independence from federal grid oversight speeds interconnection. That same system drew scrutiny after the February 2021 winter storm, when generation failures caused days-long blackouts — a backdrop that still colors every debate about adding large new loads.

    The AI boom collided with this landscape beginning in 2023–2024, when hyperscale cloud and AI companies began announcing data center campuses at unprecedented scale and grid operators nationwide sharply raised their demand forecasts. With interconnection queues stretching years, developers turned to dedicated gas generation, and Texas — with in-state gas supply and fast permitting — emerged as the natural home for that model. The Texas Tribune’s July 2026 reporting quantifies where that trend has led: more proposed data-center power plants than any other state.

    Source: Texas leads nation in proposed power plants for data centers, which would emit large amounts of greenhouse gases — Texas Tribune reporting, July 2, 2026, on the gas-fired generation pipeline behind the state’s data center boom.

  • New Jersey Sends Data Center Tariff Bill to the Governor’s Desk

    New Jersey Sends Data Center Tariff Bill to the Governor’s Desk

    New Jersey’s legislature has passed a bill establishing a data center tariff and sent it to the governor for signature, Utility Dive reported on July 2, 2026. The measure targets how the electricity costs of large data centers are recovered, with the aim of shielding other utility customers from grid expenses driven by data center growth.

    Executive Summary

    According to Utility Dive’s July 2, 2026 report, New Jersey lawmakers have approved legislation creating a tariff framework for data centers and forwarded it to the governor. A tariff, in utility parlance, is the regulator-approved schedule of rates and terms under which a customer class buys power — so a data center tariff bill is, at its core, a decision about who pays for the wires, substations, and generation capacity that very large computing facilities require.

    The move matters well beyond New Jersey. Electricity demand from data centers — especially AI-oriented facilities — has become the dominant growth story on the U.S. grid, and the costs of serving that growth have increasingly landed in debates over household utility bills. If signed, New Jersey would join a growing list of states acting to assign those costs to the data centers themselves rather than spreading them across all ratepayers. Notably, New Jersey is doing it through legislation rather than leaving the question to case-by-case utility rate proceedings.

    Why Data Center Power Costs Reached the Statehouse

    New Jersey sits inside PJM, the regional transmission organization that operates the grid across 13 states and procures capacity — commitments from power plants to be available — on behalf of utilities. Capacity prices in PJM have risen sharply in recent auctions, driven in part by projected data center demand, and those costs flow through to retail electric bills. That chain from AI build-out to household bill is what has turned a technical rate-design question into a live political issue in Trenton and other state capitals.

    Legislators stepping in is itself significant. Rate design is normally the province of utility regulators — in New Jersey, the Board of Public Utilities — moving deliberately through contested proceedings. A statute compresses that timeline and signals that lawmakers did not want to wait for the regulatory process to allocate these costs on its own.

    What a Data Center Tariff Actually Does

    The core principle behind large-load tariffs is cost causation: the customer whose demand triggers new infrastructure should bear its cost. Serving a single large data center campus can require new transmission lines, substations, and capacity procurement running into significant sums. Under conventional ratemaking, much of that spending enters the utility’s general rate base and is recovered from all customers. A dedicated data center rate class changes that default.

    Tariffs of this kind elsewhere have typically included features such as minimum demand charges (paying for a high share of requested capacity whether or not it is used), long contract terms, collateral requirements, and exit fees — protections against a utility building for a load that never materializes. Whether New Jersey’s bill includes these specific mechanisms is not detailed in the source report, and the final terms will determine how burdensome or benign the framework proves in practice.

    Winners, Losers, and the Competitive Map

    Residential and small-business ratepayers are the intended beneficiaries: the bill’s premise is that they should stop subsidizing infrastructure built for hyperscale computing. Utilities gain clearer cost-recovery rules and stronger protection against stranded investment, though they lose some flexibility in courting large customers with favorable terms. For data center developers, the calculus is mixed — a transparent tariff provides pricing certainty that ad hoc negotiations do not, but it likely raises the all-in cost of a New Jersey megawatt.

    The competitive question is whether developers simply build elsewhere. New Jersey offers real advantages — proximity to New York, dense fiber routes, and a deep enterprise customer base — but neighboring PJM states compete for the same projects. The counterpoint: states including Ohio and Georgia have already adopted large-load protections through their regulators, and development there has continued. Grid cost allocation is one input among many; power availability, land, latency, and tax treatment often weigh more heavily.

    The Signal to the Industry

    The larger story is a shift in the default social contract around data center growth. Through the first wave of the AI boom, states competed to attract data centers with incentives; the emerging second phase pairs that welcome with conditions, particularly on energy. For hyperscalers and colocation operators, the practical takeaway is that grid-cost responsibility is becoming a standard feature of U.S. market entry, not an outlier risk. That strengthens the case for strategies the industry is already pursuing: securing generation directly, co-locating with power sources, and engaging early with regulators rather than arriving with a load request after the fact.

    Background

    New Jersey occupies a distinctive position in the data center landscape: adjacent to New York City, laced with dense fiber routes, and home to a long-established financial-services and enterprise colocation market. Like the rest of the PJM region, it has felt the bill impacts of surging capacity prices as data center demand — increasingly driven by AI training and inference workloads — reshapes grid planning.

    The question of who pays for that growth has moved rapidly up state agendas since 2024. Utility regulators in several states have approved special rate provisions for very large loads, and legislatures have begun taking up the issue directly. New Jersey’s bill, as reported by Utility Dive, places the state among the earlier movers to address data center cost allocation by statute rather than leaving it wholly to regulatory proceedings.

    Source: New Jersey lawmakers send data center tariff bill to governor — Utility Dive’s July 2, 2026 report on the legislature passing a data center tariff measure and forwarding it for the governor’s signature.