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Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy.

The report also revealed that power availability is driving data center development decisions as the industry moves into a new set of power-friendly regions. Together, these findings suggest a significant structural market shift for "AI factories" and other high-density data centers.

The report's findings indicate that:

Power availability is creating new geographic winners and losers

Texas is poised to capture nearly 30% of U.S. data center market share by 2028 and Georgia's market share is expected to grow by 75% (from 4% of the total data center market to 7%) as developers expand deeper into the Southeast. In contrast, California, Oregon, Iowa, and Nebraska's respective relative market shares are expected to drop by more than 50%.

More data centers are approaching gigawatt scale

Over 50% of new data center campuses are predicted to exceed 500 MW by 2035 and nearly one-third of new data center campuses to exceed 1 GW, with each 1 GW campus consuming roughly as much electricity as the entirety of San Francisco.

The power expectation gap is widening in key hubs

Utilities project delivery timelines are approximately 1.5-2 years longer than hyperscalers and colocation providers expect. Over the past six months, the expectation gap has widened in three critical hubs – Northern Virginia, the Bay Area, and Atlanta.

Data center developers plan to make big bets in off-grid power

Hyperscalers and colocation providers expect that roughly one-third of data centers in 2030 will use 100% onsite power, a 22% increase from the previous report six months ago. Developers surveyed believe that, by 2030, onsite power will be a leading solution to minimizing development timelines and costs.

Higher-voltage and DC electrical architectures are moving from roadmap to reality

As AI campuses scale to gigawatts, operators are redesigning power systems to handle denser loads and faster build schedules. 45% of respondents expect to adopt direct-current (DC) distribution architectures in their new data centers by 2028. These designs are likely to be incorporated into data centers entering development this year.

"Data center and AI factory developers can't afford delays. Our analysis and survey results show that they're moving into power-advantaged regions where capacity can be secured faster—and increasingly designing campuses to operate independently of the grid," said Natalie Sunderland, Bloom Energy's Chief Marketing Officer. "The surge in AI demand creates a clear opportunity for states that can adapt to support large-scale AI deployments at speed."

Methodology: The 2026 Bloom Energy Data Center Power report is based on surveys commissioned via a double-blind process between Bloom Energy and respondents. Surveys were conducted in November 2025 with 152 decision-makers across the data center power ecosystem, reflecting perspectives from hyperscalers, colocation developers, utilities, and GPU service providers. Interviews were also conducted with industry leaders to pressure test findings and assess real-world implications.

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Data Centers Plan to Reduce Reliance on Grid

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy.

The report also revealed that power availability is driving data center development decisions as the industry moves into a new set of power-friendly regions. Together, these findings suggest a significant structural market shift for "AI factories" and other high-density data centers.

The report's findings indicate that:

Power availability is creating new geographic winners and losers

Texas is poised to capture nearly 30% of U.S. data center market share by 2028 and Georgia's market share is expected to grow by 75% (from 4% of the total data center market to 7%) as developers expand deeper into the Southeast. In contrast, California, Oregon, Iowa, and Nebraska's respective relative market shares are expected to drop by more than 50%.

More data centers are approaching gigawatt scale

Over 50% of new data center campuses are predicted to exceed 500 MW by 2035 and nearly one-third of new data center campuses to exceed 1 GW, with each 1 GW campus consuming roughly as much electricity as the entirety of San Francisco.

The power expectation gap is widening in key hubs

Utilities project delivery timelines are approximately 1.5-2 years longer than hyperscalers and colocation providers expect. Over the past six months, the expectation gap has widened in three critical hubs – Northern Virginia, the Bay Area, and Atlanta.

Data center developers plan to make big bets in off-grid power

Hyperscalers and colocation providers expect that roughly one-third of data centers in 2030 will use 100% onsite power, a 22% increase from the previous report six months ago. Developers surveyed believe that, by 2030, onsite power will be a leading solution to minimizing development timelines and costs.

Higher-voltage and DC electrical architectures are moving from roadmap to reality

As AI campuses scale to gigawatts, operators are redesigning power systems to handle denser loads and faster build schedules. 45% of respondents expect to adopt direct-current (DC) distribution architectures in their new data centers by 2028. These designs are likely to be incorporated into data centers entering development this year.

"Data center and AI factory developers can't afford delays. Our analysis and survey results show that they're moving into power-advantaged regions where capacity can be secured faster—and increasingly designing campuses to operate independently of the grid," said Natalie Sunderland, Bloom Energy's Chief Marketing Officer. "The surge in AI demand creates a clear opportunity for states that can adapt to support large-scale AI deployments at speed."

Methodology: The 2026 Bloom Energy Data Center Power report is based on surveys commissioned via a double-blind process between Bloom Energy and respondents. Surveys were conducted in November 2025 with 152 decision-makers across the data center power ecosystem, reflecting perspectives from hyperscalers, colocation developers, utilities, and GPU service providers. Interviews were also conducted with industry leaders to pressure test findings and assess real-world implications.

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...