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  • Utilities Turn to AI for Data-Center Load, but 84% Need 1+ Year to Scale a Pilot

    Utilities Turn to AI for Data-Center Load, but 84% Need 1+ Year to Scale a Pilot

    TL;DR · 30-second read

    The Short Version

    Power companies across America are racing to keep up with the giant computer warehouses that run artificial intelligence, which use enormous amounts of electricity.

    A new survey of 134 innovation chiefs at American power companies found that most now use artificial intelligence themselves to manage that demand. The catch: 84% say turning a small trial into something used across the whole company takes more than a year, and that delay is getting longer.

    Why it matters to you: 83% of those leaders say the cost of serving these warehouses is showing up in household electricity bills.

    National Grid Partners, the venture capital and innovation arm of UK and US energy company National Grid, released its third annual Utility Innovation Survey on September 18, 2026, at the NextGrid Alliance Summit in Boston. The survey of 134 innovation leaders at U.S. utilities, collected between May 20 and July 7, 2026, found that 78% are deploying or operationalizing at least one AI application to manage interconnection demand, while 74% say AI-driven data center load growth is affecting grid reliability.

    The survey also found that 84% of organizations take more than a year to move projects from pilot to full rollout, up from 66% in 2024, and that grid reliability has overtaken net zero as a top-three priority. National Grid Partners also announced investments in two startups, Terragrit and LineVision, and noted that National Grid has joined the newly formed AI Energy Management Alliance as a founding member.

    Executive Summary

    The headline number is adoption: nearly four in five U.S. utility innovation leaders say they are putting AI to work on the flood of requests to connect new load, much of it from AI data centers. That is the industry using the technology driving its demand problem as part of the answer to it.

    The more consequential numbers sit underneath. Innovation budgets rose at 72% of respondents, yet the share needing more than a year to scale a pilot has climbed for three consecutive surveys, from 66% to 78% to 84%. Most spending (59%) goes to incremental improvements, only 16% to transformational projects, and 87% say regulatory and rate-case frameworks written before the AI demand boom limit returns on innovation.

    Taken together, the survey describes an industry that has accepted AI as a grid-planning tool but cannot yet deploy it at the pace data-center load is arriving. For data-center developers, utilities, regulators and ratepayers, the practical constraint is increasingly how fast utilities can change the way they plan, not only how much they build.

    The Constraint Is Speed, Not Willingness

    The survey rules out the easy explanation that utilities are reluctant to adopt AI. Seventy-eight percent say they are deploying or operationalizing at least one AI application to manage interconnection demand, meaning the queue of customers waiting for permission and capacity to plug into the grid. Seventy-two percent report bigger innovation budgets this year, and only 1% say they have no plans to work with early-stage technology companies.

    What has not improved is the time it takes to turn an experiment into standard practice. Eighty-four percent of organizations now need more than a year to move a project from pilot to full rollout, up from 78% in 2025 and 66% in 2024. The trend has worsened for three straight surveys even as money has flowed in, which points to a structural bottleneck rather than a funding one. Respondents cite a shortage of workers skilled in AI and the industry’s traditionally cautious culture, and spending patterns reinforce the picture: 59% of innovation dollars go to incremental improvements against 16% for transformational initiatives.

    That matters downstream because 74% of the same leaders say AI data center load is already affecting grid reliability. The pressure is present now; the tools meant to relieve it face a year-plus path to scale at most utilities. Data-center developers waiting in interconnection queues, utility planners fielding large-load requests, and the software vendors selling into utilities all operate on that clock. A tool that could, for example, help a utility study or approve a connection faster only helps once it is embedded in how the utility actually works.

    Reliability Moves Ahead of Net Zero

    The sharpest year-over-year shift in the survey concerns priorities. Asked to rank organizational priorities, 73% of utility leaders placed reliability in their top three, up from 43% in 2025. Net-zero goals fell from 54% to 16% over the same period.

    This is a forced ranking of top-three priorities, so it measures relative emphasis rather than abandonment of climate commitments. Still, a swing of that size in one year is a clear signal about what is occupying planning attention. When a single data-center campus can represent a large new load on a regional system, keeping the lights on becomes the dominant planning question, and decarbonization targets compete for a smaller share of management focus.

    Rate Cases Written for a Slower Era

    Utilities in the U.S. generally recover investment through rate cases, the regulatory proceedings in which state commissions decide what a utility can charge customers and what return it may earn. Eighty-seven percent of respondents say those frameworks, developed before the current demand boom, are limiting returns on innovation investment. If a software tool that frees up grid capacity earns a utility less than building new poles, wires and substations, the incentive structure itself slows adoption, which is consistent with the lengthening pilot timelines.

    The cost question cuts the other way for households. Eighty-three percent of respondents say the cost of building infrastructure to serve AI data centers is being passed on to residential customers through higher bills. That is the view of the utility leaders surveyed rather than a measured cost allocation, and the survey does not quantify it, but it is a notable admission coming from inside the industry, and it frames why regulators are likely to scrutinise who pays for data-center grid upgrades.

    Flexible Data Centers as a Grid Resource

    National Grid’s answer, alongside its investment activity, is flexibility. The company has become a founding member of the AI Energy Management Alliance, whose announced members include Google, NVIDIA, Anthropic, Emerald AI, RWE, Constellation and NRG. The group says it will push for policies encouraging flexible data centers that automatically reduce power use during peak demand, buffering nearby communities from price spikes.

    The supporting evidence cited is a UK pilot last December involving Emerald AI, a National Grid Partners portfolio company, together with National Grid and NVIDIA, which found AI software could cut data center energy use by more than a third in under a minute during simulated grid strain while protecting critical workloads. That is a meaningful proof of concept, though it was a single pilot under simulated conditions. Whether flexibility becomes a dependable planning resource depends on data-center operators contractually committing to curtail, and on utilities trusting those commitments enough to connect load sooner, which brings the question back to how fast planning practices and rules can change.

    Background

    National Grid supplies electricity and natural gas to more than 80 million people in the UK, New York and Massachusetts, and is running major transmission programmes including the Great Grid Upgrade in the UK and the Upstate Upgrade in New York. Its venture arm, National Grid Partners, launched in 2018, is based in Silicon Valley with offices in Boston, London and New York, and describes itself as the utility industry’s only Silicon Valley-based corporate venture capital group.

    National Grid also founded the NextGrid Alliance, which says it includes more than 1,000 senior decision-makers from over 170 utilities in 25 countries and has facilitated more than 500 introductions between utilities and startups. The survey arrives as U.S. utilities face surging requests to connect large AI data centers, a demand shift that is pressing on grid planning, reliability and how infrastructure costs are allocated among customers.

    Sources

    Source: 2026 Utility Innovation Survey: Industry leaders turning more to AI as data-center boom reshapes grid planning, National Grid Partners’ announcement of its third annual survey of U.S. utility innovation leaders, via PR Newswire.

  • National Grid’s $1.75B Joulent Deal: When Interconnect Delays Force Utilities to Buy

    National Grid’s $1.75B Joulent Deal: When Interconnect Delays Force Utilities to Buy

    National Grid has struck a $1.75 billion deal with Joulent, according to a Data Center Knowledge report published July 1, 2026. The report frames the transaction as a response to mounting interconnection delays driven by AI data center demand — utilities, unable to connect new load fast enough through conventional build-out, are increasingly spending to acquire capacity and capability rather than queue for it.

    Executive Summary

    The reported transaction pairs one of the world’s largest electricity transmission and distribution operators with Joulent in a deal valued at $1.75 billion. The headline framing is the important part: the deal is attributed not to routine portfolio strategy but to AI interconnect delays — the growing backlog of requests to connect large new loads and generation to the grid, a process that in many regions now takes years.

    Why it matters: if the reporting’s framing holds, this is a data point in a broader shift. Utilities have historically grown connection capacity by building — new substations, transformers, transmission lines — on regulated timelines. When AI-driven demand outruns those timelines, acquisition becomes the faster path. A $1.75 billion commitment suggests National Grid sees the capacity crunch as durable, not a passing spike. That said, the available source is a single news headline; the deal’s structure, scope, and closing conditions are not detailed in the material we can verify, and readers should treat specifics beyond the reported figure and parties with appropriate caution.

    Why Buying Beats Building When the Queue Is the Bottleneck

    Interconnection — the engineering and regulatory process of physically wiring a new data center, factory, or power plant into the grid — has become one of the defining constraints of the AI build-out. Studies, permitting, equipment procurement, and construction stack into multi-year waits in many markets, and lead times for critical hardware such as large power transformers and high-voltage switchgear have stretched dramatically since the early 2020s. In that environment, anything that already exists — installed equipment, an established delivery capability, a workforce, a manufacturing slot — carries a scarcity premium.

    A utility that spends $1.75 billion to acquire capacity or capability it would otherwise wait years to build is making a straightforward time-for-money trade. The economics can work because the cost of delay is now enormous on both sides of the meter: hyperscale customers measure the cost of a stranded, unpowered data center shell in the millions per month, and utilities that cannot connect large customers forgo years of revenue from their fastest-growing load class.

    National Grid’s Position in the AI Load Story

    National Grid sits at the center of this dynamic in two major markets. It operates the high-voltage transmission network in England and Wales — where grid connection queues became a widely acknowledged national bottleneck and the subject of regulatory reform efforts — and it owns large regulated electricity and gas utilities in New York and Massachusetts, in the demand path of the US Northeast’s data center and electrification growth. Few companies feel interconnection pressure from as many directions at once.

    That context makes the reported deal legible even without full details: a transmission-heavy utility facing connection backlogs on two continents has clear motives to secure capacity, equipment supply, or delivery capability by acquisition. It also carries risk. Large deals struck during a scarcity cycle can look expensive if the cycle turns — if AI load forecasts moderate or supply chains normalize, capacity bought at peak-crunch prices may earn a thinner return than capacity built patiently through the regulated process.

    What $1.75 Billion Signals — and What It Doesn’t

    The figure itself is the strongest signal in the reporting. Utilities are conservative, regulated businesses; a commitment of this size typically requires board conviction that the underlying driver — here, sustained AI-driven demand outpacing conventional grid expansion — will persist long enough to pay back the investment. In that sense the deal is a vote of confidence in continued data center growth, made by a party with unusually good visibility into actual connection requests rather than press-release pipelines.

    What the number does not tell us is the mechanism. “Buying your way to capacity” can mean acquiring a company outright, purchasing assets, locking up equipment manufacturing capacity, or securing services under a long-term contract — and each has very different implications for competitors, regulators, and customers. The single-source material available does not specify which of these the National Grid–Joulent transaction is, what Joulent brings to the arrangement, or how the spend will be recovered. Those distinctions matter: an acquisition that removes a supplier or contractor from the open market can tighten conditions for every other utility shopping in it, while a capacity contract merely reallocates near-term supply.

    Background

    National Grid built its position over decades as the operator of Great Britain’s electricity transmission backbone before expanding into the US Northeast, where it serves millions of electricity and gas customers in New York and Massachusetts. In both markets it entered the mid-2020s facing an unprecedented problem: connection requests from data centers, electrified transport, and new generation arriving faster than networks could be studied, permitted, and built, prompting queue-reform efforts by regulators on both sides of the Atlantic.

    The AI boom sharpened that squeeze into a defining industry constraint. Transformer and switchgear lead times stretched, hyperscale campuses began requesting connections measured in hundreds of megawatts, and ‘time to power’ displaced real estate as the data center industry’s scarcest resource — the backdrop against which a utility paying $1.75 billion to shortcut the queue becomes a rational, if notable, move.

    Source: AI Interconnect Delays Spur $1.75B National Grid-Joulent Deal — Data Center Knowledge report, July 1, 2026, on National Grid’s $1.75 billion deal with Joulent amid AI-driven grid interconnection backlogs.