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Power availability and skilled workers are putting pressure on AI data center expansion, but current surveys do not establish them as the universal top two bottlenecks. In a 2026 survey about scaling compute, accelerator and GPU supply ranked first, narrowly ahead of power and cooling. Which constraint matters most depends on what is being built, where it is being built, and what each survey asked.
Why AI data center growth is exposing bottlenecks
AI computing requires data centers with substantial electrical capacity, cooling systems, specialized equipment, and people to design, build, commission, and operate them. Expanding any one part faster than the others can delay capacity: a site may lack a timely power connection, equipment may arrive late, or a project may struggle to recruit people with the necessary skills.
Demand is rising, too. Computer Weekly reported that the BCS Consultancy’s Datacentre truths 2026 survey questioned 3,000 respondents in the data-center space. It found that 78% reported an AI-related demand uplift in 2025; all surveyed developers and investors and 91% of service providers reported AI-driven demand. These are survey responses about demand, not measurements of data-center capacity or a forecast of future growth. (Computer Weekly)
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What surveys say about the leading constraints
Different surveys point to related but distinct problems. Futurum Group’s April 24, 2026 release asked about the single largest constraint to scaling data-center compute. Accelerator or GPU supply was selected by 26% of respondents, while power and cooling was selected by 23%. Budget or capital-expenditure limits were selected by 15%; talent or skills shortages and networking lead times were each selected by 11%. The figures describe that survey’s answers to one question, not a ranking that applies to every project or operator. (Futurum Group)
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Uptime Institute’s July 2026 announcement of its 16th annual global data center survey lists power availability, supply-chain disruptions, high costs, capacity forecasting, and worsening recruiting and retention pressures among industry concerns. This broader list reinforces that power and staffing sit within a group of interdependent constraints. (Uptime Institute)
| Measure | Finding | What it tells you |
|---|---|---|
| Single largest compute-scaling constraint, Futurum Group, 2026 | 26% accelerator/GPU supply; 23% power and cooling; 15% budget/capex; 11% talent/skills; 11% networking lead times | GPU supply ranked ahead of power and cooling in this survey’s responses. |
| Core-role job-posting growth, 2023–2025, Deloitte Insights analysis published in 2026 | 64% in data centers; 20% in the power sector; 4% across the broader economy for the compared roles | Posting growth is a signal of rising demand for workers, not a count of vacancies. |
| Executives’ leading talent obstacle, Deloitte 2025 AI Infrastructure Survey, reported in 2026 | 63% of data-center executives cited a shortage of data-center-related skilled labor | This measures executive perceptions of hiring difficulty, not unfilled jobs. |
Power is a constraint at several stages
Power and cooling are linked, but they are not identical problems. A project may need access to sufficient electrical supply, infrastructure capable of delivering it, and cooling systems suited to the facility’s equipment and operating requirements. A delay or shortfall in one can constrain usable compute even if the other components are ready.
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That distinction matters when interpreting survey language. Futurum’s 23% figure combines “power and cooling” as a single answer option; it does not separate grid availability from cooling capacity. Uptime Institute’s announcement lists power availability among several concerns, but does not make it a universal number-one obstacle. Neither source supports treating every data center, region, or stage of construction as facing the same power problem.
Why skilled labor is under pressure
The workforce issue is not simply a shortage of generic technology workers. Data centers and power companies need people with expertise relevant to electrical systems, facility operations, and the physical behavior of cooling systems. As facilities expand, hiring needs can span design and construction as well as ongoing operation.
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Deloitte Insights reported that job postings for core roles grew from 2023 to 2025 by 64% in data centers, compared with 20% in the power sector and 4% across the broader economy for the roles compared. Deloitte also reported that 63% of data-center executives in its 2025 AI Infrastructure Survey named skilled labor shortages as their leading obstacle to securing talent. The first set of figures tracks posting growth; the second reports executive survey responses. Neither is a direct count of unfilled positions. (Deloitte Insights)
A separate global survey by DCD Intelligence and DCD Academy, conducted in June 2026, included 161 data-center-industry respondents and targeted operators. DCD’s September 18, 2026 coverage says expansion is outpacing available talent, identifies fluid-dynamics and power expertise as major drivers of workforce expansion, and notes that respondents were looking to utilities and oil and gas for workers. It also points to structured training, standardized onboarding, and upskilling as relevant approaches. These are reported workforce priorities, not evidence that any particular training method has solved the shortage. (Data Center Dynamics; DCD Intelligence and DCD Academy)
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How to read the evidence without mixing unlike measures
A “single biggest constraint” response, a rise in job postings, and a report of hiring difficulty answer different questions. Before comparing figures, check the measure, respondents, timeframe, and stage of deployment it covers.
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- Measure: Is the figure about grid power, combined power-and-cooling capacity, equipment supply, hiring perceptions, or job-posting growth?
- Respondents: Does it reflect operators, compute decision-makers, investors, developers, service providers, or executives?
- Scope and date: Is it global or regional, and when was the survey conducted or the data measured?
- Project stage: Does it concern securing a power connection or equipment, building and commissioning a site, or staffing ongoing operations?
For example, Futurum’s survey compares respondents’ selections for the single largest compute-scaling constraint, while Deloitte’s job-posting analysis describes a change in recruitment signals across 2023–2025. They cannot be combined into one universal ranking of data center problems.
What this means for AI data center projects
The evidence supports a practical conclusion: adding compute capacity depends on coordinating power, equipment, cooling, capital, networking, and skilled labor. A bottleneck can shift as a project progresses. GPU supply may dominate one decision-maker’s immediate concern, while power access or specialist staffing may be more decisive for a particular site or phase.
The supplied headline’s broad point—that power and talent are major pressures—is consistent with the cited industry reporting. But the available survey evidence does not identify a single, consistent top-two ranking, nor does it identify which specific data center firms originated that exact wording.
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