Nuclear goes startup: SMRs race to power AI data centers as gridlock, geopolitics, and timelines collide
The gist
Startup-driven small modular reactors (SMRs) are racing to power AI data centers, but gridlock, regulatory hurdles, and clashing timelines threaten to short-circuit the nuclear-powered AI boom.
What to know
- Tech upstarts like Everstar and Valor Atomic are fast-tracking nuclear by hacking regulatory bottlenecks, with commercial SMRs targeted for 2028.
- Hyperscale AI giants are inking major power purchase deals with Oklo, NuScale, TerraPower and others as grid capacity and U.S. electricity prices hit breaking points.
- A mismatch between decade-long SMR buildouts and AI’s three-year planning cycles could stall nuclear’s integration, with urgent questions about how to bridge the gap until next-gen reactors arrive.
Nuclear’s AI Power Play
SMRs are becoming the backbone of AI’s explosive growth, with industry heavyweights betting that only nuclear can scale fast enough to meet the sector’s relentless demand for clean, reliable energy.
Small modular reactors (SMRs) are rapidly emerging as the indispensable clean energy backbone for hyperscale AI data centers, addressing the sector's insatiable and exponentially growing electricity demands amid persistent grid bottlenecks and geopolitical energy crises. Industry leaders like Everstar’s CEO Kevin Kong emphasize that nuclear power is not a mere backup but the only scalable solution capable of supporting a future where 10 billion people enjoy abundant electrification and AI infrastructure expands relentlessly. This resurgence is underscored by strategic moves such as the reopening of Three Mile Island and a trillion-dollar global race to integrate SMRs alongside modular gas turbines, signaling a seismic shift in energy infrastructure driven by AI’s explosive growth.
Hyperscale AI operators are concretely backing SMRs through significant power purchase agreements with leading developers like Vistra, Oklo, TerraPower, NuScale, X-energy, and Kairos, reflecting a strategic pivot toward nuclear to overcome the limitations of intermittent renewables and constrained natural gas supplies. With projects such as Oklo’s Idaho National Laboratory plant targeting commercial operations by 2028, these timelines align closely with AI infrastructure buildouts aiming to break through gridlock by 2030, effectively integrating nuclear power into AI energy planning and fueling the next AI infrastructure arms race.
Startups Hack Nuclear Red Tape
Nuclear startups are bulldozing decades of regulatory inertia by importing Silicon Valley speed and ethos, forcing regulators to adapt as they push for rapid SMR deployment.
Everstar is revolutionizing the nuclear regulatory landscape by striving to transform the traditionally slow, labyrinthine approval process into one that operates at 'software speed,' borrowing agility and rapid iteration principles from the tech sector. As Kevin Kong emphasizes, the core issue isn’t physics or safety—both of which are well-established—but an outdated regulatory framework that traps critical knowledge in bureaucratic inertia, causing decades-long delays. This startup-inspired approach aims to unlock SMR deployment by streamlining approvals and applying deep tech methodologies to accelerate what has historically been a glacial process.
Valor Atomic exemplifies the disruptive startup mentality reshaping nuclear deployment by aggressively challenging the U.S. Nuclear Regulatory Commission’s (NRC) stringent oversight, arguing that the smaller scale of SMRs justifies lighter regulation. Their founder, a 27-year-old high school dropout, embodies a 'brute force' execution ethos, declaring, 'we are going to build this reactor' despite regulatory obstacles. This bold stance, coupled with a successful lawsuit against the NRC, has catalyzed controversial yet impactful reforms under the Trump administration, which loosened safety procedures and enabled Valor to accelerate construction timelines significantly.
Gridlock Fuels Nuclear Revival
Skyrocketing AI energy needs and grid bottlenecks are forcing a risky nuclear renaissance, as the U.S. scrambles to keep pace with global rivals and avoid losing its AI edge.
The explosive growth of hyperscale AI data centers is rapidly outstripping the capacity of existing electrical grids, spotlighting critical bottlenecks that threaten to throttle the AI sector’s expansion. In the U.S., this demand-supply imbalance has led to an electricity shortage, with utilities struggling under regulatory constraints and rising costs, while China aggressively expands its energy portfolio with massive investments in coal and renewables. This geopolitical energy divergence underscores the fragility of U.S. energy infrastructure despite its advantage of energy independence, as soaring electricity prices and constrained grid capacity jeopardize America’s leadership in AI innovation.
Amid these grid constraints and geopolitical tensions, nuclear power—especially the advent of small modular reactors (SMRs)—is resurging as a pivotal clean energy solution. Regulatory reforms inspired by tech industry models and advances in reactor technology are enabling nuclear to address both the urgent need for scalable, reliable power and the broader decarbonization imperative. This renaissance comes despite decades of public fear and regulatory hurdles rooted in past nuclear disasters, reflecting a high-stakes gamble that is reshaping funding models and investor confidence in the energy sector.
The mismatch between the rapid deployment cycles of AI hardware and the prolonged timelines required to build new power infrastructure exacerbates these bottlenecks, with transformer lead times ballooning from 24-30 months pre-2020 to as long as five years today. As hyperscalers fiercely compete for grid capacity, the economics of AI infrastructure are increasingly measured by the dollar per watt of contracted power, placing a premium on reliable, scalable energy sources like nuclear. This energy-centric shift is redefining competitive advantage in the AI race, making nuclear power integration not just a strategic necessity but a critical determinant of future market leadership.
Timelines Collide, Trust Falters
A deep mismatch between SMR buildouts and AI planning cycles is stalling partnerships, leaving the industry scrambling for interim solutions as nuclear remains just out of reach.
A fundamental tension exists between the decade-long development timelines required for small modular reactors (SMRs) and the hyperscale AI operators’ notably short planning horizons, which rarely extend beyond three years. This mismatch complicates the formation of long-term partnerships critical for capital-intensive projects, especially given the historical reliance on federal government support—a role that remains conspicuously absent as of 2026. Industry insiders express skepticism about near-term integration of SMRs into AI data center infrastructure, highlighting a persistent 'general feeling of lack of partnership' that undermines confidence in aligning these divergent timelines.
While there is broad confidence among experts that SMRs and fusion energy will eventually materialize as viable solutions, the pressing challenge lies in managing the energy needs of hyperscale AI data centers during the interim period before these technologies become operational. This temporal gap fuels uncertainty, as stakeholders grapple with how to bridge current grid bottlenecks and geopolitical energy risks without the immediate availability of advanced nuclear options, underscoring the urgency for transitional strategies that can accommodate the slow maturation of SMRs alongside the rapid growth of AI infrastructure.
