AI’s voracious appetite is straining energy grids, prompting new power strategies and longer planning horizons
In sum — what to know:
A gating factor: Power is now the biggest gating factor for AI infrastructure, with water to follow next.
Bring your own power: To avoid grid struggles, business must consider adopting bring your own power (BYOP) strategies which involve tapping into multiple energy sources, years in advance.
Nuclear power, a distant solution: CEO of DigitalBridge notes that nuclear power as an alternative energy source for AI remains years away.
AI infrastructure is at a crossroads. While on one hand demand for infrastructure is growing at a manic speed, power constraint is choking structural expansion plans.
That’s the message that came from Marc Ganzi, CEO of DigitalBridge — an asset management firm in the digital infrastructure space which was acquired by SoftBank late last year — at Metro Connect USA in Fort Lauderdale.
Speaking at the keynote, Ganzi said, “To enable AI, we all know the cliche is, power availability becomes the currency. That’s really the currency that’s driving critical workloads, that’s driving new data centers, and ultimately drives an ecosystem that feeds off of those data centers.
While there is a lot of free land, he reminded that land without power is of no value, nor a “will-serve” letter from an utility provider stating that it has capacity and intent to supply service.
“A will-cert letter does not mean you have a connection date,” he said, noting that developers today are looking at connection dates between 2030 and 2032.
He said that gaining access to energy is now a power play which really comes down to how politically connected one is in that state.
He argued that it essentially makes the digital infrastructure business more like power enablement business, where, to sidestep state-level politics and long grid queues, developers must orchestrate grid-independent power, micro-grids and multi-source energy strategies as a core part of their business model. Now popularly called bring your own power (BYOP), the strategy promotes onsite power generation over reliance on public grids.
Ganzi reminded that the power problem is here to stay. The industry currently leases 12 gigawatts of power every year, while adding four gigawatts of incremental capacity.
“You guys can do the math,” he said. “We have a deficit of power,” adding that the gap will only widen in the coming years.
And as the energy discourse turns towards nuclear power as an alternative source that can meet AI’s appetite for “baseload” power, Ganzi’s message was blunt but clear: “We don’t believe that magically 40 to 60 gigawatts of nuclear power is going to show up in eight years. It’s not.” He added that it will take another decade and then some years for it to pan out practically.
“If we’re all hoping for some magic bullet to save the power problem, I’m here to tell you it’s not going to happen,” he emphasizes.
With the data center industry already facing public backlash from local communities for building projects in their backyards, Ganzi predicted that the next challenge will be water.
“The next page to turn is the sector is going to be hit hard with water. We’ll have to defend our water usage.” He noted that it is pressing on the industry to design water cooling systems that require no loss of water, adding that work is already underway.
Ganzi urged the industry to think in longer timelines and planning horizons. He recommended a 36 to 48 month build cycle instead of a five-year model, and advised companies to start planning to solve tomorrow’s power supply issues today with several years of time on hand.
“That’s the mentality you have to have for success…The opportunity is huge. The challenges are different. Every year the chessboard changes, and it’s a lot of fun,” he concluded.
Facts Only
Marc Ganzi, CEO of DigitalBridge, spoke at Metro Connect USA in Fort Lauderdale.
DigitalBridge is an asset management firm in digital infrastructure, acquired by SoftBank in late 2023.
Power availability is now the primary constraint for AI infrastructure expansion.
Land without guaranteed power access is considered valueless, even with utility "will-serve" letters.
Developers are facing grid connection dates between 2030 and 2032.
The industry leases 12 gigawatts of power annually but adds only 4 gigawatts of new capacity.
A "bring your own power" (BYOP) strategy is emerging, involving onsite generation, micro-grids, and multi-source energy.
Nuclear power is not expected to provide a viable solution within the next decade.
Water usage is predicted to become the next major challenge for data centers.
The industry is developing water cooling systems with no water loss.
Ganzi recommends a 36-48 month build cycle instead of a five-year model.
Public backlash against data center projects is increasing due to local community concerns.
Executive Summary
The AI industry is facing a critical bottleneck: power availability has become the primary constraint on infrastructure expansion, with water usage emerging as the next major challenge. Marc Ganzi, CEO of DigitalBridge, highlighted this issue at Metro Connect USA, emphasizing that land without guaranteed power access is effectively worthless. Developers now face connection timelines stretching to 2030-2032, forcing a shift toward "bring your own power" (BYOP) strategies—onsite generation, micro-grids, and multi-source energy solutions—to bypass grid limitations. The industry currently leases 12 gigawatts annually but only adds 4 gigawatts of new capacity, creating a growing deficit. While nuclear power is often proposed as a long-term solution, Ganzi dismissed it as unrealistic within the next decade. Additionally, data centers are facing public resistance over water consumption, pushing the sector toward closed-loop cooling systems. Ganzi urged companies to adopt longer planning horizons (36-48 months) and proactive energy strategies to navigate these constraints.
The situation reflects a broader tension between AI's exponential growth and the physical limits of energy and water infrastructure. Political influence increasingly determines access to power, while nuclear energy remains a distant prospect. The industry's response—decentralized power solutions and water-efficient designs—signals a shift from reliance on public utilities to self-sufficiency. However, the gap between demand and supply continues to widen, raising questions about scalability and sustainability.
Full Take
The strongest version of this narrative is that AI's rapid growth is colliding with the physical limits of energy and water infrastructure, forcing the industry to rethink its reliance on traditional utilities. Ganzi’s arguments are grounded in observable trends: grid constraints, political hurdles, and the slow pace of nuclear development. His call for BYOP strategies and longer planning horizons reflects a pragmatic response to an unsustainable status quo. The emphasis on water as the next frontier adds credibility, as data centers already face scrutiny over resource consumption.
However, the narrative leans heavily on Ganzi’s perspective, which may overlook alternative solutions or downplay the potential of nuclear energy. The framing of power as a "currency" and the political nature of access could imply a zero-sum game, potentially obscuring collaborative opportunities between public and private sectors. The dismissal of nuclear power as a near-term solution, while likely accurate, risks reinforcing a sense of inevitability about the crisis without exploring interim innovations.
Root cause: The paradigm here is one of exponential demand outpacing linear infrastructure growth. The unstated assumption is that AI’s energy needs are non-negotiable, which may sideline discussions about efficiency gains or demand-side management. Historically, this echoes past industrial revolutions where resource constraints forced technological and policy adaptations—think of the shift from coal to oil or the rise of renewable energy.
Implications: Human agency is tested here. Companies with political influence or capital to invest in BYOP will thrive, while smaller players may struggle. Local communities bear the costs of water usage and land disputes, while the benefits of AI accrue to global tech giants. Second-order consequences could include accelerated innovation in energy storage, decentralized grids, or even policy shifts toward nationalizing critical infrastructure.
Bridge questions: What if AI demand were met with aggressive efficiency standards rather than just supply-side solutions? How might public-private partnerships reshape energy distribution to avoid a "power feudalism" dynamic? What role could regulatory frameworks play in balancing AI growth with resource equity?
Counterstrike scan: A bad actor pushing this narrative might amplify the sense of crisis to justify deregulation or corporate control over energy resources, framing BYOP as the only solution while dismissing public utility investments. However, the content does not align with this pattern—it presents a genuine industry challenge without overt manipulation. The focus remains on practical constraints rather than ideological agendas.
Patterns detected: none
Sentinel — Human
The article shows strong signs of human authorship, including a distinct speaker's voice, specific attributions, and uneven stylistic patterns inconsistent with AI generation.