The AI infrastructure boom is rapidly reshaping how the data center industry thinks about power. What was once a relatively straightforward utility procurement exercise is evolving into a complex strategy spanning onsite generation, fuel logistics, financing, and system architecture.

That reality framed a recent special edition of The Data Center Frontier Show Podcast, which recast and updated a pivotal DCF Trends Summit 2025 session: From Grid to Onsite Powering: Optimizing Energy Behind the Meter for Data Centers.

Moderated by Fengrong Li, Senior Managing Director at FTI Consulting, the panel explored how operators are responding as interconnection timelines stretch and AI workloads surge. Li’s framing emphasized a core shift: onsite power is moving from contingency planning to critical-path infrastructure.

From the OEM perspective, David Blank of Siemens Energy noted that behind-the-meter deployments have accelerated sharply over the past year as developers confront multi-year waits for firm utility capacity.

“Everyone would prefer grid power,” Blank said. “But in many cases, reliable access isn’t available for five, ten, even ten-plus years.”

Panelists agreed that AI’s scale and speed are driving a structural rethink. Brian Gitt of Oklo described the moment as a return to industrial roots, with large loads once again building dedicated generation to meet growth timelines.

At the same time, new technical pressures are emerging. AI clusters can produce sharp load swings, forcing developers to deploy fast-response buffering technologies such as batteries, flywheels, and supercapacitors to maintain stability.

Despite differing technology paths—including gas turbines, hydrogen fuel cells, and advanced nuclear—the panel aligned on one common theme: modularity. Phased power blocks increasingly mirror how AI campuses are actually built and financed.

The discussion also highlighted the growing importance of contract structures. Long-term offtake commitments, capacity reservations, and credit support are increasingly required to unlock equipment queues and fuel supply.

Other panelists included Marty Trivette of AlphaStruxure and Yuval Bachar of ECL. The event was hosted by Data Center Frontier’s Matt Vincent.

The takeaway was clear: in the AI era, energy strategy has moved to the critical path—and for many operators, that path now runs behind the meter.

The data center industry is racing into the AI era with bigger campuses, tighter timelines, and unprecedented infrastructure complexity. But in this episode of The Data Center Frontier Show Podcast, 7x24 Exchange International founding member and Mission Critical Global Alliance (MCGA) board member Dennis Cronin argues the industry’s biggest constraint may be the one it talks about least: people.

Cronin’s message is direct: the “talent cliff” isn’t coming; it’s already here. Based on recent research into open roles, he estimates 467,000 to 498,000 openings in core data center positions (facilities and ops leadership, electrical, generator/UPS, HVAC, controls), plus another ~514,000 emerging roles tied to AI infrastructure, sustainability, and cyber-physical security—bringing the total to roughly one million jobs the industry needs to fill.

A major driver is what Cronin calls the “five-year experience trap”: employers require five years of experience even for entry-level roles, but newcomers can’t get experience without being hired. The result is widespread talent poaching, involving workers jumping from site to site for 10–20% raises, without expanding the overall labor pool.

Cronin also highlights a frequently missed reality in public policy debates: the job multiplier effect. While data centers may have lean direct staffing, they support a much larger ecosystem of contractors, service providers, and manufacturers, from generator and UPS technicians to security integrators and the electrical/mechanical supply chain, many of whom are already scrambling to hire.

On training, Cronin explains why company-run programs and commercial training aren’t enough on their own. Internal academies often produce siloed specialists trained for a single operator’s environment, while commercial courses, often ~$1,000 per day per person, are typically designed to upskill people already in the industry, not onboard new entrants.

MCGA’s strategy focuses on community colleges as the most scalable on-ramp: affordable programs, scholarships, and hands-on labs that can produce strong technicians in two-year degrees. Cronin cites programs at Cleveland Community College (NC), Northern Virginia Community College, and Southside Community College (VA), noting that dozens of schools are exploring data center curricula but funding remains a barrier.

Cronin’s proposed solution is a true workforce ecosystem: outreach, standardized curriculum, certification labs, structured apprenticeships, and employer commitments. He also advocates replacing the “five years” requirement with an entry-level certification that proves foundational knowledge, i.e. acronyms and language, reading one-lines, SOPs/MOPs, and crucially, safety and situational awareness in electrical and mechanical environments.

Finally, Cronin tackles the money question. With $60B in data centers announced this year, he says the industry needs a major, shared investment across operators, vendors, contractors, and manufacturers to fund training and scholarships at scale. The stakes are operational: in an era of gigawatt AI facilities and shrinking margins for error, workforce readiness is now a mission-critical issue.

In the latest episode of The DCF Show Podcast, Data Center Frontier founder Rich Miller joins present DCF Editor in Chief Matt Vincent and Senior Editor David Chernicoff to examine where the data center industry stands as AI infrastructure moves from announcement to execution.

Miller also discusses his new Data Center Richness podcast and Substack project, which explores how data center professionals consume content and learn about the rapidly evolving industry. With information overload now a reality, Miller’s goal is to distill the most important signals shaping infrastructure decisions.

The conversation then turns to what defines 2026 for data centers: execution. After a year filled with megaproject announcements, the industry now faces the harder task of actually delivering campuses at AI scale—often under severe power constraints.

With utilities struggling to keep pace, on-site generation is shifting from temporary solution to long-term strategy, as developers seek reliable ways to power projects while easing community concerns about grid impacts.

Public resistance has also become a major factor. Miller notes that community opposition is now delaying or halting billions of dollars in projects, forcing operators to rethink how they engage with local stakeholders. Issues like power pricing and water usage are increasingly central to project approval.

On the technology front, Nvidia’s roadmap continues to reshape infrastructure planning, with rack densities rising sharply, liquid cooling becoming standard, and new power distribution models emerging to support AI factories. At the same time, Miller expects the market to stratify, with some operators specializing in AI factories while others serve cloud and enterprise demand.

The discussion also touches on nuclear power’s future role, with data centers positioning themselves as anchor customers, though meaningful SMR deployment remains years away.

Ultimately, Miller argues that the industry is moving faster than ever, and 2026 will reveal how well today’s massive investments translate into real deployments.

As he concludes: the next phase belongs to those who can deliver.