Data Centres Briefings

Ohio is getting a little less “open for business” on data centres — at least politically. U.S. Rep. Greg Landsman’s two-bill package would push operators to cover the full cost of energy and infrastructure, require environmental impact studies, and even bar NDAs that keep elected officials from talking openly about projects. Add in local anxiety about power and water for cooling, and you’ve got a familiar flashpoint that’s starting to harden into draft policy.

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Landsman’s proposals go straight at the industry’s most sensitive pressure points: who pays for grid upgrades, and how much the public gets to see while projects are being negotiated. The bills would require data centres to pay the full cost of their energy and inf

The U.S. Department of Energy just put a stake in the ground on what “AI-scale” infrastructure looks like: a 10GW data center campus at Portsmouth, Ohio, paired with up to 10GW of new generation — including 9.2GW of natural gas — and $4.2bn of grid upgrades. SoftBank/SB Energy and AEP Ohio are in the mix, and DOE says construction starts this year. If this is real execution rather than a grand render, it’s the clearest sign yet that the U.S. is willing to co-locate compute with new fossil generation at a scale that blows past today’s “hyperscale” vocabulary.

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The DOE-backed PORTS Technology Campus plan is unusually explicit about power: 10GW of data center load and up to 10GW of supply at the same site, with 9.2GW coming

NextEra says the White House has approved up to 10GW of new gas generation in Texas and Pennsylvania — explicitly tied to Japan’s $550bn investment commitment under a U.S.-Japan trade deal. That’s a blunt answer to the question everyone in this business keeps asking: when the grid can’t keep up with AI load growth, who’s willing to build firm power, and how fast? Pair it with Washington’s fresh “rate payer protection” talk and you can see the shape of the next fight: data centers want capacity now, regulators want households insulated from the bill.

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NextEra approved to build up to 10 GW gas plants is the clearest signal today that gas is being pulled back into the “AI infrastructure” conversation at industrial scale

Google just put demand flexibility on the same footing as generation: it’s baked 1GW of demand response into long-term contracts with multiple U.S. utilities, explicitly to speed up data centre interconnections by shifting ML workloads. That’s a meaningful pivot from “find more megawatts” to “make the grid behave better.” Pair it with Google’s Michigan mega-solar-and-storage plan and you can see the playbook emerging: bring your own flexibility, show your work to regulators, and get to power faster than the next queue.

The Big Stories

Google integrates 1 GW demand response into long-term contracts with utilities including I&M, TVA, Entergy Arkansas, Minnesota Power, and DTE Energy, aiming to shift or reduce ML workloads when the gr

Pure Data Centres Group just gave Europe a pretty blunt answer to the grid-constraint era: build your own. At its Dublin campus, Pure DC and AVK have switched on an on-site, dispatchable 110MW microgrid designed to let AI capacity land in phases before full grid connection — a move that feels less like “resilience” and more like a new deployment model for constrained markets.

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Pure DC unveils Europe’s first 110 MW data centre microgrid at its Dublin campus, built with AVK, using three energy centres and a 20MW BESS to deliver phased capacity ahead of full grid connection. The system uses dual-fuel Wärtsilä engines with HVO backup and is hydrogen-blend ready, and it’s being pitched as a blueprint for other tight Eur

NVIDIA is trying to turn telcos into the next compute platform. At GTC, it and a roster of big operators pitched “distributed AI grids” that would convert roughly 100,000 network edge data centres into an inference fabric—and, in the most optimistic framing, scale to “more than 100GW” of AI capacity over time. If that sounds like a moonshot, it is—but it also lines up neatly with today’s other signal: power and interconnection are now the hard constraints, so everyone is shopping for new places to put compute (and new ways to run it).

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Telecom Operators and NVIDIA Announce Distributed AI Grids is the clearest attempt yet to reframe telco edge sites as an AI infrastructure layer, not just network plumbing. AT&T, Comcast,

Meta just put a giant number on the board: a five-year agreement with Nebius Group worth up to $27bn, including about $12bn in dedicated Nvidia Rubin-based AI infrastructure that won’t start showing up until early 2027. That’s a long-dated capacity reservation at a moment when everyone is pretending supply chains and power queues will politely sort themselves out. Read it as a signal: the biggest buyers are getting comfortable underwriting “Rubin-era” scarcity now, not when the racks land.

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Meta signs up to $27B Nebius AI infrastructure deal is the cleanest expression yet of where AI infrastructure is heading: fewer spot purchases, more multi-year capacity lockups with a clear GPU generation attached. The structure matte

AWS doesn’t usually tell customers to flee an entire region — but that’s effectively what happened after drone strikes damaged at least three of its Middle East data centres. The incident hit two sites in the UAE and one in Bahrain, and AWS advised customers to reroute workloads to the US, Europe, or Asia Pacific. In one day, geopolitics turned from “macro risk” into a very literal capacity-and-latency problem.

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AWS data centres damaged by drone strikes in the UAE and Bahrain is the kind of operational shock that changes procurement conversations overnight. AWS said at least three data centres were hit and told customers to shift workloads to other Regions. Analysts are already pointing to selective knock-on demand in pl

Maharashtra is trying to brute-force its way into the top tier of global data centre markets — and it’s putting a three-year clock on it. In its latest push, the state government says it wants to become a global leader, leaning hard on Mumbai’s connectivity advantages, power infrastructure, and a promise of smoother approvals and infrastructure support. The tone is unmistakable: this isn’t “we’d like more projects”; it’s a bid to be on every hyperscaler and operator’s shortlist.

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Maharashtra aims to become global leader in data centres is a loud, time-bound political commitment: leadership “within three years,” framed around rapid investment momentum, supportive policies, and rising digital demand. The state is explicitl

Google didn’t just sign another PPA — it bought the power developer. In a US$4.75bn move, Google has finalised its acquisition of Intersect Power as it lines up renewable supply for a massive US data-centre build, including US$40bn earmarked for three Texas sites through 2027. When the same story also quotes Sundar Pichai talking about US$185bn of AI capex this year, the message is blunt: power access is becoming a balance-sheet problem, not a procurement task.

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Google buys Intersect Power to secure data centre power is the clearest example yet of a hyperscaler treating generation and storage as strategic control points. The deal is framed around securing renewables for U.S. expansion, while Intersect’s lead shareholders

Bridge Data Centers just put a big number on the board in one of the world’s most power-constrained markets: a planned S$3–5bn build-out for more than 2GW of “AI-ready” capacity in Singapore. That scale isn’t just a flex — it’s a reminder that the AI infrastructure race is now as much about power strategy as it is about land, fibre, or GPUs. And in the background, US grid modelers are increasingly blunt about what happens when demand lands faster than generation.

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Bridge Data Centers plans S$3-5bn AI-ready data centre expansion is the day’s headline because it combines capital, capacity, and geography in a way that forces competitors to react. Bridge says it will invest S$3–5bn with global partners to develop **more

Google isn’t just buying servers anymore — it’s buying the power stack. The company has agreed to pay $4.75bn for Intersect Power’s “digital power” business, a deal that lands squarely in the messy intersection of grid access, generation, and AI-scale load. Pair that with a 30GWh long-duration battery system slated to sit at a Google data centre in Minnesota, and you can see the shape of the next phase: hyperscalers trying to turn electricity into a controllable input, not a constraint.

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Google acquires Intersect Power; IPX Power launches independent IPP. Google is acquiring Intersect Power’s digital power business for $4.75bn (and assuming debt), while Intersect’s grid-tied clean-energy assets have been spun

Iran’s reported drone strikes on UAE-based Amazon data centres are a nasty reminder that “cloud region” is also a physical place with a postcode — and a blast radius. In Iran drone attacks on UAE Amazon data centres disrupt banks, the knock-on effects weren’t theoretical: Emirates NBD and ADCB saw disruption, payment apps went down, and global banks told staff they could leave the UAE and work remotely while exposures were reviewed. For an industry that sells availability, this is what systemic risk looks like when geopolitics meets concentrated digital infrastructure.

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The UAE incident is notable not just for the attack itself, but for the second-order response. Banks including Citigroup, Goldman Sachs and Morgan Stanle

Nscale just pulled in an eye-watering $2B Series C at a $14.6B valuation — and it’s not being shy about what that money is for: hundreds of megawatts of GPU capacity across Europe, the US, and Asia. That kind of cheque is a reminder that “AI infrastructure” is no longer a theme; it’s a capital market with its own gravity. The catch: the physical constraints (water, power, permitting) are starting to show up in the same news cycle as the funding.

The Big Stories

Nscale’s $2B raise, led by Aker ASA and 8090 Industries, cements a new tier of AI-first infrastructure players that want to control more of the stack (“ground to cloud”) rather than just lease space and power. It matters because it normalises hyperscale-sized capex for companies

Utah just shoved a sensitive topic into the daylight: lawmakers advanced a requirement for data centers to disclose water use, in the middle of a broader push to triage the Great Salt Lake crisis and other water pressures (Utah legislature acts on Great Salt Lake and environment). That’s not a flashy megawatt headline, but it’s the kind of policy move that can quietly reshape site selection, community relations, and permitting timelines. Pair it with today’s reminder about undersea cable security in Taiwan, and you get a clear theme: critical digital infrastructure is being pulled deeper into the politics of scarcity and security.

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Utah’s Legislature approved $30 million to help restore the Great Salt Lake and set in moti

Taiwan just printed a number that should make anyone tracking AI infrastructure sit up: January export orders hit a record US$76.91 billion, up 60.1% year-on-year, with the government explicitly pointing to AI-related servers and cloud demand as key drivers. The Lunar New Year base effects helped, but the composition of the growth is the tell — the plumbing of AI is showing up in hard trade data.

The Big Stories

​Taiwan January export orders hit record US$76.91 billion is the cleanest “AI capex is real” datapoint we’ve had in a while. The Ministry of Economic Affairs said export orders surged 60.1% YoY to US$76.91 billion, with information and communications orders jumping 102.0% to US$25.15 billion and electronic product orders rising

The most telling signal today wasn’t a new campus or a fresh funding round — it was politics catching up with physics. President Trump’s nonbinding “Rate Payer Protection Pledge” for data centers would push hyperscalers to bring on-site power and pay for grid upgrades, with Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI signing on. The catch is buried in the fine print: experts are already warning interconnection and permitting routinely run 5+ years, so “new power” simply won’t show up in time for 2027–2028 demand.

The Big Stories

The White House-backed pledge is a political attempt to stop data centers from becoming the villain in retail electricity bills. The pledge asks hyperscalers to supply on-site energy and cover grid

North American data centre demand may be red-hot, but the build machine is starting to choke on permits and power. CBRE says capacity under construction has slipped to 5,994.4MW (down 5.5% vs 2024) because zoning, permitting, and power-sourcing delays are stalling projects—and grid capacity is “largely booked through 2030.” That dovetails neatly with what’s happening on the ground: utilities are now planning multi-gigawatt transmission specifically to feed future data centre clusters.

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CBRE: Permitting and power delays constrain North American data center construction is the cleanest snapshot of the market’s new bottleneck. Despite record demand in 2025, CBRE points to project slowdowns driven by permitting, zoning, and—

The most fragile part of “cloud resilience” isn’t software — it’s geography. Drone strikes damaged multiple AWS Availability Zones in the Gulf, taking two UAE zones offline and impacting one in Bahrain, and suddenly every board-level conversation about AI uptime has a new line item: what happens when a whole campus is a target.

That shock lands on the same day as a huge power-capital deal for the data-centre supply chain, and a White House-friendly pledge from Google that (quietly) tries to rewrite who pays for grid upgrades.

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AES is being taken private in a $33.4bn enterprise-value deal by a GIP- and EQT-led consortium that also includes CalPERS and Qatar’s sovereign we

Akamai is making a very loud bet that AI inference won’t live only in hyperscale campuses. With a plan to deploy “thousands” of Nvidia Blackwell GPUs across 4,000+ locations, it’s pitching a decentralised inference fabric that it claims can cut latency by up to 2.5x and reduce inference costs by up to 86% versus hyperscalers. If that number is even directionally right, it’s less a product launch than a direct challenge to where AI margins sit—and who captures them.

The Big Stories

Akamai to deploy Nvidia Blackwell GPUs across 4,000+ locations is the most consequential move in today’s stack of announcements because it reframes “AI infrastructure” as an edge distribution problem, not a campus arms race. Akamai says it will ro