What Keeps Data Centers and Their Utility Partners Up at Night: The Power Problem

Stay Ahead, Stay ONMINE

What Keeps Data Centers and Their Utility Partners Up at Night: The Power Problem

AI has the potential to revolutionize how we manage the grid, marking a transformative shift in how utilities optimize operations, enhance reliability, and meet evolving consumer demands. Through the deployment of AI-driven algorithms and predictive analytics, utilities can anticipate grid dynamics, optimize energy flows, and proactively address challenges in real time. The integration of AI with cloud infrastructure further enhances efficiency and performance, enabling utilities to leverage vast amounts of data from diverse sources, including weather data, edge data, and advanced metering systems (AMS).

By leveraging machine learning and analytics to merge and assess data streams and sensored information, utilities can unlock new levels of efficiency and performance. The challenges of our power needs are so complex that a system will be best utilized to process the various permutations and uncertainties; this will need to be a highly sophisticated predictive tool, but if properly developed it can enhance grid equipment lifespans, apply data-driven decision making, identify issues quickly, and reduce unplanned downtime.

Utilities are increasingly recognizing the importance of leveraging AI to gain intimate insights into their customers’ energy needs and behaviors, allowing them to prepare for future power demands effectively. From improving customer experiences through innovative applications to reimagining day-to-day operations with self-healing grid technology, utilities are embracing AI to drive digital transformation and move beyond their traditional roles. This data-driven approach not only optimizes grid performance but also enhances customer experiences and drives digital transformation within the industry.

Strategic Grid Planning for Looming Demand

Part of the planning that worries them most is not just how to supply power to more data centers. At least data centers clue our local utilities in on our upcoming needs. Electric vehicles are altogether unpredictable, except for areas that have seen regulatory timelines enforced. They also tend to flock together, with charging stations handling many at a time. More than just consumer use, they have potential fleets being converted in bulk.

The proliferation of electric vehicles as well as data centers presents both challenges and opportunities for grid planners. Word on the street is that electrification of the transportation market will double energy usage in 10 years and lead to an 800% increase over the next 20 years. That’s the load that has them most worried, and calculating how many electric vehicles they can handle. They need to get uncomfortably close to what consumers and businesses are going to want in the future to predict and plan for this demand.

Strategic grid planning is essential to accommodate the surge in electricity demand while ensuring reliability and stability. Utilities are exploring innovative solutions such as smart charging infrastructure, vehicle-to-grid integration, and energy storage to manage peak demand and optimize resource utilization. With the exponential growth of EVs and data centers, grid planning has never been more critical. We must invest in scalable and resilient infrastructure to support this electrified future.

Embracing the Grid Edge and Prosumer Movement

The emergence of the prosumer movement and the evolution of the grid edge are reshaping the traditional utility-consumer relationship, transforming consumers from passive recipients to active participants in the energy transition. This shift is driven by the proliferation of rooftop solar, home energy storage, and distributed energy resources (DERs), highlighting the importance of grid-edge innovations and community energy initiatives.

Consumers are no longer merely consumers; they are prosumers actively shaping the energy landscape. Utilities must adapt to this transformation and empower consumers to become active stakeholders in the energy transition. At the grid edge, where consumers interact directly with energy systems, better data quality, validity, and granularity are achieved, leading to low latency, high reliability, and scalability. This proximity to data sources enables predictive infrastructure and empowers citizens to be part of the solution.

The path to edge intelligence involves various components, including metrology for energy, demand, and power quality, as well as anomaly detection for outage, temperature, loose neutral, and tampering. Despite existing limitations in edge technology, such as firmware-driven systems and communication bottlenecks, rapid advancements in hardware, communication protocols, and software are driving progress. Software deployed at the edge is customizable, agile, and driven by an application mindset, leveraging more advanced algorithms, especially in machine learning.

Overcoming challenges at the edge requires leveraging technologies that enable robust networks capable of making informed decisions and identifying various devices, such as EVs, solar panels, batteries, and pump controls. This necessitates funneling and utilizing data effectively to empower consumers to make informed energy decisions and optimize energy usage. Despite the complexities introduced by IP addresses and evolving technologies, the focus remains on enabling consumers to actively participate in the energy transition while ensuring the reliability and scalability of grid-edge solutions.

Renewable Energy Integration

Renewable energy integration is driving a significant transformation in the energy landscape, with solar and wind power playing increasingly prominent roles in the generation mix. Utilities are investing in renewable energy infrastructure, grid-scale energy storage, and innovative grid-edge technologies to maximize the potential of renewables and reduce carbon emissions.

With sustainability at the forefront of efforts, integrating renewable energy sources into the grid and leveraging advanced technologies are seen as crucial steps toward achieving environmental goals while ensuring reliability and affordability for customers. Last year, 84% of new installed capacity was renewables and storage, marking a substantial shift in the generation mix. Demand response, accounting for 60% of capacity, is becoming increasingly significant.

Orchestrating the energy transition requires flexible resources and demand-side capabilities, with virtual power plants (VPPs) emerging as cost-effective solutions. However, managing the transition poses challenges, particularly in forecasting net load, VPP capabilities, and battery capacity at scale. Artificial intelligence and machine learning are key applications that can help the industry navigate these transitions and keep moving forward.

Some companies are exploring off-grid solutions due to frustrations with traditional electricity networks. Off-grid technology, once frowned upon, is now considered a necessity for certain operations. Companies like Microsoft and Google are exploring options such as small nuclear plants and zero-emissions fusion power to power energy-intensive operations, although regulatory and land acquisition challenges remain significant hurdles in this endeavor.

Fostering Innovation and Scalability

In the midst of rapid change, utilities are recognizing the critical importance of innovation and scalability in navigating the evolving energy landscape. By fostering a culture of innovation, establishing strategic partnerships, and prioritizing scalability, utilities can unlock new opportunities for success and drive significant progress towards a smarter, more resilient grid.

To meet the challenges of tomorrow, it is essential to invest in cutting-edge technologies and scalable solutions. This proactive approach enables utilities to pioneer the power grid of the future while delivering tangible value to customers and communities alike.

As electrification continues to grow rapidly and new technologies emerge, such as nuclear energy, utilities are embracing innovative projects to enhance reliability and resiliency. For instance, there are some pretty cool utility-driven projects in my local area I’ve been following: Duke Energy’s floating solar project in South Florida and residential battery installations in neighborhoods like Hunter’s Creek exemplify the shift towards cleaner, more resilient energy solutions. Additionally, initiatives like the 100% green hydrogen project in DeBary, FL highlight the ongoing efforts to integrate renewable energy sources and drive sustainability forward.

Not Your Grandparents’ Power Grid

The pulse of energy shapes our present and affords our future. The job to be done itself has not changed over time: people need light and power. What has changed is the complexities that utility providers must navigate in the modern energy landscape: the convergence of AI, EV integration, grid-edge innovations, renewables, and scalable solutions are reshaping the trajectory of the power grid. By embracing these key themes and driving meaningful progress in each area, utilities can unlock new opportunities for growth, sustainability, and resilience, propelling the power grid into a new era of innovation and prosperity.

Stay Ahead

Explore More Insights

Stay ahead with more perspectives on cutting-edge power, infrastructure, energy, bitcoin and AI solutions. Explore these articles to uncover strategies and insights shaping the future of industries.

Hyperscaler backlogs show growing demand for AI infrastructure

Amazon’s backlog is now $244 billion, up 40% year over year. “There’s a lot of demand for AWS right now, in the AI space and also in the core AWS space,” Jassy said. CEO Sundar Pichai said that Google plans to spend around $180 billion on capex in 2026. And

AI for IT stalls as network complexity rises

There are a number of network-related issues that are driving enterprises to delay or abandon their AI projects, according to IDC’s special report on AI in networking. Organizations expect business benefits, including improved IT service levels, to come from using AI across their network infrastructure, according to IDC’s special report

Vår Energi lets 3-year contract for harsh-environment rig for NCS work

CERT-EU blames Trivy supply chain attack for Europa.eu data breach

Back door credentials The Trivy compromise dates to February, when TeamPCP exploited a misconfiguration in Trivy’s GitHub Actions environment, now identified as CVE-2026-33634, to establish a foothold via a privileged access token, according to Aqua Security. Discovering this, Aqua Security rotated credentials but, because some credentials remain valid during this

Latin America returns to the energy security conversation at CERAWeek

With geopolitical risk central to conversations about energy, and with long-cycle supply once again in focus, Latin America’s mix of hydrocarbons and export potential drew renewed attention at CERAWeek by S&P Global in Houston. Argentina, resource story to export platform Among the regional stories, Argentina stood out as Vaca Muerta was no longer discussed simply as a large unconventional resource, but whether the country could turn resource quality into sustained export capacity. Country officials talked about scale: more operators, more services, more infrastructure, and a larger industrial base around the unconventional play. Daniel González, Vice Minister of Energy and Mining for Argentina, put it plainly: “The time has come to expand the Vaca Muerta ecosystem.” What is at stake now is not whether the basin works, but whether the country can build enough above-ground capacity and regulatory consistency to keep development moving. Horacio Marín, chairman and chief executive officer of YPF, offered an expansive version of that argument. He said Argentina’s energy exports could reach $50 billion/year by 2031, backed by roughly $130 billion in cumulative investment in oil, LNG, and transportation infrastructure. He said Argentine crude output could reach 1 million b/d by end-2026. He said Argentina wants to be seen less as a recurrent frontier story and more as a future supplier with scale. “The time to invest in Vaca Muerta is now,” Marín said. The LNG piece is starting to take shape. Eni, YPF, and XRG signed a joint development agreement in February to move Argentina LNG forward, with a first phase planned at 12 million tonnes/year. Southern Energy—backed by PAE, YPF, Pampa Energía, Harbour Energy, and Golar LNG—holds a long-term agreement with SEFE for 2 million tonnes/year over 8 years. The movement by global standards is early-stage and relatively modest, but it adds to Argentina’s export

Market Focus: LNG supply shocks expose limited market flexibility

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); a { color: var(–color-primary-main); } .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; font-family: Inter; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #c19a06 !important; border-color: #c19a06 !important; } In this Market Focus episode of the Oil & Gas Journal ReEnterprised podcast, Conglin Xu, managing editor, economics, takes a look into the LNG market shock caused by the effective closure of the Strait of Hormuz and the sudden loss of Qatari LNG supply as the Iran war continues. Xu speaks with Edward O’Toole, director of global gas analysis, RBAC Inc., to examine how these disruptions are intensifying global supply constraints at a time when European inventories were already under pressure following a colder-than-average winter and weaker storage levels. Drawing on RBAC’s G2M2 global gas market model, O’Toole outlines disruption scenarios analyzed in the firm’s recent report and explains how current events align with their findings. With global LNG production already operating near maximum utilization, the market response is being driven by higher prices and reduced consumption. Europe faces sharper price pressure due to storage refill needs, while Asian markets are expected to see greater demand reductions as consumers switch fuels. O’Toole underscores the importance of scenario-based modeling and supply diversification as geopolitical risk exposes structural vulnerabilities in the LNG market—offering insights for stakeholders navigating an increasingly uncertain global

Libya’s NOC, Chevron sign MoU for technical study for offshore Block NC146

@import url(‘https://fonts.googleapis.com/css2?family=Inter:[email protected]&display=swap’); a { color: var(–color-primary-main); } .ebm-page__main h1, .ebm-page__main h2, .ebm-page__main h3, .ebm-page__main h4, .ebm-page__main h5, .ebm-page__main h6 { font-family: Inter; } body { line-height: 150%; letter-spacing: 0.025em; font-family: Inter; } button, .ebm-button-wrapper { font-family: Inter; } .label-style { text-transform: uppercase; color: var(–color-grey); font-weight: 600; font-size: 0.75rem; } .caption-style { font-size: 0.75rem; opacity: .6; } #onetrust-pc-sdk [id*=btn-handler], #onetrust-pc-sdk [class*=btn-handler] { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-policy a, #onetrust-pc-sdk a, #ot-pc-content a { color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-pc-sdk .ot-active-menu { border-color: #c19a06 !important; } #onetrust-consent-sdk #onetrust-accept-btn-handler, #onetrust-banner-sdk #onetrust-reject-all-handler, #onetrust-consent-sdk #onetrust-pc-btn-handler.cookie-setting-link { background-color: #c19a06 !important; border-color: #c19a06 !important; } #onetrust-consent-sdk .onetrust-pc-btn-handler { color: #c19a06 !important; border-color: #c19a06 !important; } The National Oil Corp. of Libya (NOC) signed a memorandum of understanding (MoU) with Chevron Corp. to conduct a comprehensive technical study of offshore Block NC146. The block is an unexplored area with “encouraging geological indicator that could lead to significant discoveries, helping to strengthen national reserves,” NOC noted Chairman Masoud Suleman as saying, noting that the partnership is “a message of confidence in the Libyan investment environment and evidence of the return of major companies to work and explore promising opportunities in our country.” According to the NOC, Libya produces 1.4 million b/d of oil and aims to increase oil production in the coming 3-5 years to 2 million b/d and then to 3 million b/d following years of instability that impacted the country’s production. Chevron is working to add to its diverse exploration and production portfolio in the Mediterranean and Africa and continues to assess potential future opportunities in the region. The operator earlier this year entered Libya after it was designated as a winning bidder for Contract Area 106 in the Sirte basin in the 2025 Libyan Bid Round. That followed the January 2026 signing of a

Finder Energy advances KTJ Project with development area approval

Finder Energy Holdings Ltd. received regulatory approval for a development area covering the Kuda Tasi and Jahal oil fields offshore Timor‑Leste, enabling progression toward field development. Autoridade Nacional do Petróleo (ANP) approved an 88‑sq km development area over the Kuda Tasi and Jahal oil fields (KTJ Project) within PSC 19‑11 offshore Timor‑Leste, representing the first stage of the regulatory approvals process for the project. The declaration of the development area is a precursor to the field development plan (FDP), which Finder is currently preparing for submission to ANP in second‑quarter 2026. Upon approval of the FDP, the development area would secure tenure for up to 25 years or until production ceases, allowing Finder to conduct development and production operations within the area, subject to applicable regulatory approvals and conditions. The company said its upside strategy centers on the potential for the Petrojarl I FPSO to serve as a central processing and export hub for future tiebacks of surrounding discoveries, contingent on successful appraisal and/or exploration activities within PSC 19‑11. Alternatively, longer tie‑back distances could be accommodated through a secondary standalone development in the southern portion of the PSC. Finder is continuing technical evaluation of appraisal and exploration opportunities to generate drilling targets. PSC 19‑11 lies within the Laminaria High oil province of Timor‑Leste. The KTJ Project contains an estimated 25 million bbl of gross 2C contingent resources, with identified upside of an additional 23 million bbl gross 2C contingent resources and 116 million bbl gross 2U prospective resources. Finder operates PSC 19‑11 with a 66% working interest.

Newly formed Polar LNG aims to develop nearshore LNG project on Alaska’s North Slope

Polar Train LNG LLC, a newly launched company aiming to build an LNG plant (Polar LNG) on Alaska’s North Slope, has appointed Joel Riddle as president and chief executive officer. “Alaska’s North Slope holds one of the most significant undeveloped natural gas resources in the world,” said Riddle, adding “Polar LNG is uniquely positioned to bring this resource online—delivering reliable energy for Alaska and a strategic supply for the United States… and provides trusted energy to our allies.” In a release Mar. 31, the company said it is advancing a nearshore project at Prudhoe Bay, citing “one of the shortest LNG shipping routes from North America to key Asian markets, approximately 3,600 miles to Japan compared to over 10,000 miles from the US Gulf Coast.” The company is aiming for first LNG from the 7-million tonnes/year plant—to be developed nearshore with modular infrastructure—in 2029-2030 at a cost of $8–9 billion. According to Polar LNG, natural gas would be sourced from existing infrastructure at Prudhoe Bay and transported via a short pipeline to a nearshore plant. There, a modular gravity-based structure would process and liquefy the gas. LNG would then be loaded onto specialized ice-class carriers for year-round export. The company is exploring potential repurposing of sanctioned equipment built for Russia’s Arctic LNG 2 project and is seeking permission from the US govenment to acquire parts impacted by the sanctions, according to reports. Before joining Polar LNG, Riddle served as managing director and chief executive officer of Tamboran Resources Ltd.

Asia bears brunt of energy shock as Middle East war disrupts liquid flows

Asia is facing a dual energy crisis marked by both soaring prices and physical supply disruptions as escalating war in the Middle East constrains flows through the Strait of Hormuz, according to a new report by Morningstar DBRS. The report highlights that roughly one-fifth of global crude oil and LNG supply has been affected by disruptions at the critical chokepoint, with Asia absorbing the majority of the impact due to its heavy dependence on imported hydrocarbons. About 83% of oil and LNG shipments passing through Hormuz are destined for Asian markets, amplifying the region’s exposure. Asia’s structural reliance on Middle Eastern energy imports has intensified the shock. Countries such as Japan and South Korea import nearly all of their energy needs, while China and India depend heavily on foreign supplies, much of it sourced from the Gulf. This dependence, combined with limited alternative shipping routes, has turned what initially appeared to be a price-driven shock into a broader supply and logistics crisis. Governments across the region have begun implementing emergency measures, including fuel rationing, price controls, and strategic reserve releases, to manage shortages and rising costs. Policy responses vary In North Asia, policymakers are leveraging stronger buffers. Japan has tapped strategic oil reserves and introduced subsidies to cushion consumers, while South Korea is relying on LNG stockpiles and fuel-switching capabilities. China has deployed administrative controls to stabilize domestic fuel prices and restrict refined product exports. By contrast, parts of South and Southeast Asia are more vulnerable. India has introduced tax relief and prioritized gas allocation, while countries such as the Philippines and Vietnam have declared energy emergencies and rolled out conservation measures. Several ASEAN (the Association of Southeast Asian Nations) economies have even implemented partial work-from-home policies to curb fuel consumption. Broader economic spillovers intensify Beyond energy markets, the disruption

Two New England states say no to new data centers

It’s getting harder and harder for governments to ignore the impact that data centers are having on their communities, consuming vast amounts of water and driving up electricity prices, experts say. According to a Pew Research Center analysis, data centers consumed 183 terawatt-hours of electricity in 2024, more than 4% of total U.S. electricity use. That demand is projected to more than double to 426 terawatt-hours by 2030. The impact is significant. In 2023, data centers consumed about 26% of Virginia’s electricity supply, although Virginia is notable for having an extremely dense collection of data centers. Alan Howard, senior analyst for infrastructure at Omdia, says he is not surprised at all. “The amount of national press coverage regarding what is arguably a limited number of data center ‘horror’ stories has many jurisdictions and states spooked over the potential impacts data center projects might have,” he said. It’s an evolution that’s been coming for some time whereby local legislators have embraced the idea that they don’t want to learn the hard way as others already have, he argues. “All that said, it seems unlikely that there will be broad bans on data center development that would cripple the industry. There’s lots of places to go in the U.S. and developers have warmed up to siting projects in places amenable to their needs, although not ideally convenient,” said Howard.

Nscale Expands AI Factory Strategy With Power, Platform, and Scale

Nscale has moved quickly from startup to serious contender in the race to build infrastructure for the AI era. Founded in 2024, the company has positioned itself as a vertically integrated “neocloud” operator, combining data center development, GPU fleet ownership, and a software stack designed to deliver large-scale AI compute. That model has helped it attract backing from investors including Nvidia, and in early March 2026 the company raised another $2 billion at a reported $14.6 billion valuation. Reuters has described Nscale’s approach as owning and operating its own data centers, GPUs, and software stack to support major customers including Microsoft and OpenAI. What makes Nscale especially relevant now is that it is no longer content to operate as a cloud intermediary or capacity provider. Over the past year, the company has increasingly framed itself as an AI hyperscaler and AI factory builder, seeking to combine land, power, data center shells, GPU procurement, customer offtake, and software services into a single integrated platform. Its acquisition of American Intelligence & Power Corporation, or AIPCorp, is the clearest signal yet of that shift, bringing energy infrastructure directly into the center of Nscale’s business model. The AIPCorp transaction is significant because it gives Nscale more than additional development capacity. The company said the deal includes the Monarch Compute Campus in Mason County, West Virginia, a site of up to 2,250 acres with a state-certified AI microgrid and a power runway it says can scale beyond 8 gigawatts. Nscale also said the acquisition establishes a new division, Nscale Energy & Power, headquartered in Houston, extending its platform further into power development. That positioning reflects a broader shift in the AI infrastructure market. The central bottleneck is no longer simply access to GPUs. It is the ability to assemble power, cooling, land, permits, data center

Google Research touts memory-compression breakthrough for AI processing

The last time the market witnessed a shakeup like this was China’s DeepSeek, but doubts emerged quickly about its efficacy. Developers found DeepSeek’s efficiency gains required deep architectural decisions that had to be built in from the start. TurboQuant requires no retraining or fine-tuning. You just drop it straight into existing inference pipelines, at least in theory. If it works in production systems with no retrofitting, then data center operators will get tremendous performance gains on existing hardware. Data center operators won’t have to throw hardware at the performance problem. However, analysts urge caution before jumping to conclusions. “This is a research breakthrough, not a shipping product,” said Alex Cordovil, research director for physical infrastructure at The Dell’Oro Group. “There’s often a meaningful gap between a published paper and real-world inference workloads.” Also, Dell’Oro notes that efficiency gains in AI compute tend to get consumed by more demand, known as the Jevons paradox. “Any freed-up capacity would likely be absorbed by frontier models expanding their capabilities rather than reducing their hardware footprint.” Jim Handy, president of Objective Analysis, agrees on that second part. “Hyperscalers won’t cut their spending – they’ll just spend the same amount and get more bang for their buck,” he said. “Data centers aren’t looking to reach a certain performance level and subsequently stop spending on AI. They’re looking to out-spend each other to gain market dominance. This won’t change that.” Google plans to present a paper outlining TurboQuant at the ICLR conference in Rio de Janeiro running from April 23 through April 27.

Amazon Middle East datacenter suffers second drone hit as Iran steps up attacks

Amazon was contacted for comment on the latest Bahrain drone incident, but said it had nothing to add beyond the statement in its current advisory. Denial of infrastructure Doing the damage is the Shaheed 136, a small and unsophisticated drone designed to overwhelm defenders with numbers. If only one in twenty reaches its target, the price-performance still exceeds that of more expensive systems. When aimed at critical infrastructure such as datacenters, the effect is also psychological; the threat of an attack on its own can be enough to make it difficult for organizations to continue using an at-risk facility. Iran’s targeting of the Bahrain datacenter is unlikely to be random. Amazon opened its ME-SOUTH-1 AWS presence in 2019, and it is still believed to be the company’s largest site in the Middle East. Earlier this week, the Islamic Revolutionary Guard Corps (IRGC) Telegram channel explicitly threatened to target at least 18 US companies operating in the region, including Microsoft, Google, Nvidia, and Apple. This follows similar threats to an even longer list of US companies made on the IRGC-affiliated Tasnim News Agency in recent weeks. That strategy doesn’t bode well for US companies that have made large investments in Middle Eastern datacenter infrastructure in recent years, drawn by the growing wealth and influence of countries in the region. This includes Amazon, which has announced plans to build a $5.3 billion datacenter in Saudi Arabia, due to become available in 2026. If this is now under threat, whether by warfare or the hypothetical possibility of attack, that will create uncertainty.

Data Center Jobs: Engineering, Construction, Commissioning, Sales, Field Service and Facility Tech Jobs Available in Major Data Center Hotspots

Each month Data Center Frontier, in partnership with Pkaza, posts some of the hottest data center career opportunities in the market. Here’s a look at some of the latest data center jobs posted on the Data Center Frontier jobs board, powered by Pkaza Critical Facilities Recruiting. Looking for Data Center Candidates? Check out Pkaza’s Active Candidate / Featured Candidate Hotlist Power Applications Engineer Pittsburgh, PA This position is also available in: Denver, CO and Andrews, SC. Our client is a leading provider and manufacturer of industrial electrical power equipment used in industrial applications for mission critical operations. They help their customers save money by reducing energy and operating costs and provide solutions for modernizing their customer’s existing electrical infrastructure. This company provides cooling solutions to many of the world’s largest organizations and government facilities and enterprise clients, colocation providers and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive salaries and benefits. Electrical Commissioning Engineer Ashburn, VA This traveling position is also available in: New York, NY; White Plains, NY; Dallas, TX; Richmond, VA; Montvale, NJ; Charlotte, NC; Atlanta, GA; Hampton, GA; New Albany, OH; Cedar Rapids, IA; Phoenix, AZ; Salt Lake City, UT; Kansas City, MO; Omaha, NE; Chesterton, IN or Chicago, IL. *** ALSO looking for a LEAD EE and ME CxA Agents and CxA PMs. *** Our client is an engineering design and commissioning company that has a national footprint and specializes in MEP critical facilities design. They provide design, commissioning, consulting and management expertise in the critical facilities space. They have a mindset to provide reliability, energy efficiency, sustainable design and LEED expertise when providing these consulting services for enterprise, colocation and hyperscale companies. This career-growth minded opportunity offers exciting projects with leading-edge technology and innovation as well as competitive

No joke: data centers are warming the planet

The researchers also made use of a database provided by the International Energy Agency (IEA) that the authors pointed out contains more than 11,000 locations worldwide, of which 8,472 have been detected to dwell outside of highly dense urban areas. The latter locations were then used to “quantify the effect of data centers on the environment in terms of the LST gradient that could be measured on the areas surrounding each data center.” Asking the wrong question Asked if AI data centers are really causing local warming, or if this phenomenon is overstated, Sanchit Vir Gogia, chief analyst at Greyhound Research, said, “the signal is real, but the industry is asking the wrong question. The research shows a consistent rise in land surface temperature of around 2°C following the establishment of large data centre facilities.” The debate, however, “has quickly shifted to causality: whether this is driven by operational heat from compute, or by land transformation during construction. That distinction matters scientifically, but it does not change the strategic implication.” Land surface temperature, said Gogia, is not the same as air temperature, and that gap will be used to challenge the findings. “But dismissing the signal on that basis would be a mistake,” he noted. “Data centers concentrate energy use, replace natural surfaces with heat-retaining materials, and continuously reject heat into the environment. Those are known drivers of thermal change.” He added, “the uncomfortable truth is this: Even if the exact mechanism is debated, the outcome aligns with first principles. Infrastructure at this scale alters its surroundings. The industry does not yet have a clean way to separate construction impact from operational impact, and that ambiguity makes the risk harder to model, not easier. This is not overstated, it is under-interpreted.” Location strategy must change But will the findings change

Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs). In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

Stay Ahead, Stay ONMINE