Artificial intelligence is forcing the data center industry to confront an energy problem unlike anything it has faced before. Hyperscale campuses increasingly require hundreds of megawatts of continuous electricity, while grid interconnections, transmission development and new generation can take years to deliver. Small modular nuclear reactors promise an unusually attractive combination of firm power, low operational carbon emissions, high energy density and a relatively small physical footprint. The question is no longer whether nuclear power could support AI infrastructure. The question is whether SMRs can move from promising technology to commercially deployable infrastructure quickly enough to matter.
Artificial intelligence may be digital technology, but the infrastructure supporting it is becoming one of the world's largest physical energy challenges. Every GPU, server rack, and data center ultimately depends on electricity, and AI's extraordinary growth is pushing individual campuses toward power requirements that would have been almost unimaginable for conventional data centers only a decade ago. Developers are increasingly evaluating projects measured not in tens of megawatts but in hundreds of megawatts, while some proposed campuses contemplate electricity demand approaching or exceeding a gigawatt.
That growth is changing the fundamental economics of data center development. Historically, developers selected locations based on fiber connectivity, land, latency, tax incentives, customer proximity and access to an established utility system. Electricity was important, but the underlying assumption was that utilities could eventually provide whatever capacity a project required. That assumption is becoming increasingly difficult to make as utilities face massive interconnection requests, transmission constraints, and generation shortages, while electrification and manufacturing add more demand to the grid.
A recent Inside Climate News examination of small modular reactors highlights one of the most intriguing possibilities emerging from this power challenge. Small modular nuclear reactors, commonly known as SMRs, are being positioned as a potential source of firm, low-carbon electricity that can operate close to major data center loads. The U.S. Energy Information Administration describes SMRs as reactors generally designed to produce approximately 70 MW to 350 MW, while Inside Climate News reports that 22 SMR designs are under development in the United States and two NuScale designs have received Nuclear Regulatory Commission approval for deployment in the U.S. market. The critical limitation, however, is equally important: as of August 2026, no fully deployed commercial SMR is operating in the United States.
That gap between technological promise and commercial availability is what makes the SMR conversation so important. Data center developers are searching for enormous amounts of electricity today, while advanced nuclear developers are building technologies intended to address electricity needs that may not reach commercial scale for years. Whether those timelines can converge could determine whether SMRs become a niche generation resource or a foundational technology supporting the next generation of AI infrastructure.
Why SMRs and AI Data Centers Appear Almost Made for Each Other
The data center industry's fundamental attraction to nuclear power begins with reliability. AI inference, cloud computing, financial transactions, communications networks and other digital services operate continuously, creating electricity demand that does not disappear when renewable generation declines. Servers do not care whether the sun is shining or whether wind conditions are favorable; they require electricity every second of every day. This makes firm generation extraordinarily valuable to an industry increasingly concerned about both grid reliability and time-to-power.
SMRs aim to combine the operating characteristics of conventional nuclear generation with a smaller, potentially more flexible development model. Traditional nuclear reactors can exceed 1,000 MW, which represents an enormous infrastructure commitment for a single project. A 300 MW reactor may be relatively small within the nuclear industry, but 300 MW represents a substantial block of generation for a hyperscale facility -- enough, according to Inside Climate News, to power hundreds of thousands of average American homes. Multiple modules could theoretically be deployed as computing capacity expands, allowing the energy infrastructure to scale alongside the data center rather than requiring developers to commit immediately to a massive conventional reactor.
Nuclear's extraordinary energy density creates another significant advantage. Wind and solar can produce highly competitive electricity and will remain essential components of the energy transition, but generating hundreds of megawatts from variable renewable resources requires substantial land and supporting infrastructure. Nuclear generation concentrates enormous amounts of energy into a comparatively small footprint while producing electricity continuously. Brad Tietz, Midwest director of government affairs at the Data Center Coalition, told Inside Climate News that SMRs' smaller sizes allow many reactors to fit within just a couple of buildings, leaving room for the data center itself to keep growing alongside its power source.
Reliability, scalability and energy density therefore create an unusually strong technical fit between SMRs and AI data centers. The challenge is that those advantages only become meaningful once reactors can actually be manufactured, licensed, financed, constructed and operated on a commercial scale. Inside Climate News captures that tension clearly: industry advocates see significant potential, while nuclear experts emphasize that commercial deployment remains a multi-year process involving regulatory approvals, manufacturing scale-up and continued technological development.
Co-Locating Nuclear Power with Compute Could Change the Data Center Development Model
One of the most important ideas around SMRs is the possibility of co-locating generation near data center campuses. Instead of selecting a site and depending almost entirely on the transmission system to deliver hundreds of megawatts from distant generating resources, developers could theoretically integrate dedicated nuclear generation into the broader energy infrastructure supporting the campus. Inside Climate News reports that the Data Center Coalition's preferred model would place SMRs close to data centers while still allowing electricity to interact with the grid, potentially reducing the need for additional transmission and distribution infrastructure.
This concept aligns directly with the broader movement toward energy-first data center development. Developers increasingly cannot assume that a location with fiber, land and attractive tax incentives automatically represents a viable data center site. A site capable of accommodating a 500 MW campus is valuable only if developers can realistically deliver 500 MW within the development schedule. As grid capacity becomes constrained, developers are evaluating locations based on available generation, transmission access, substations, natural gas infrastructure, renewable resources and the ability to build additional energy infrastructure directly alongside computing facilities.
An SMR-powered campus could take that concept substantially further. Several reactor modules could provide continuous generation while battery energy storage systems manage short-duration load fluctuations, provide power-quality services and support transitions between generation resources. Solar and wind could contribute additional low-cost electricity when available, while the utility grid could remain connected for redundancy, market participation and operational flexibility. Instead of treating the data center and power plant as separate infrastructure projects, developers could begin designing integrated energy campuses in which computing capacity, generation, storage, substations and cooling infrastructure are developed together.
That model would fundamentally change the relationship between data centers and utilities, but it would also introduce significant regulatory and safety complexities. Nuclear reactors cannot simply be installed behind the meter like conventional backup generators. Licensing, security, emergency planning, waste management, fuel supply, grid interconnection, and operational responsibility would all need to be addressed. Inside Climate News also highlights criticism from nuclear safety experts who question whether co-location should proceed before proposed reactor designs accumulate substantially more operating evidence. The potential infrastructure advantages are substantial but realizing them will require far more than placing a reactor beside a server building.
Time-to-Power May Be the Biggest Obstacle Facing SMRs
For the AI industry, one of the most important metrics in energy development is becoming time-to-power. Electricity cost still matters enormously, but a low-cost resource that cannot be delivered until years after a data center is scheduled to begin operations may have limited commercial value. Billions of dollars of GPUs and computing infrastructure cannot generate revenue while waiting for a power plant, substation or transmission line to be completed.
That tension played out publicly just weeks before Inside Climate News published its reporting. In early August 2026, Texas Governor Greg Abbott ordered a pause on new data center approvals in the state, citing insufficient energy and water resources. The following day, on NuScale's second-quarter earnings call, CEO John Hopkins pointed to the company's SMRs as an answer to exactly that kind of concern, saying NuScale had deepened partnerships with large-scale data centers -- though he offered no specifics about the agreements. "We're positioning ourselves to move forward as quickly [as possible], so it's really the timing of the customer and when they need their energy," Hopkins said. Some nuclear experts, however, remain skeptical that NuScale's design can be made commercially viable at the pace the moment seems to demand.
That episode illustrates the SMR opportunity's most immediate limitation. No fully deployed commercial SMRs are currently operating in the United States, and industry representatives acknowledge that the technologies are not yet widely available or deployable. Regulatory approvals take years, manufacturing capacity must expand, and developers still need to show that standardized reactor designs can move efficiently from approval to repeatable construction.
That timeline means SMRs should not be treated as the primary solution to the immediate data center electricity shortage. AI campuses being developed during the next several years will continue relying heavily on utility power, existing nuclear generation, natural gas, renewable generation, battery storage, and major investments in transmission and substations. Developers may sign agreements with advanced nuclear companies today, but those agreements largely serve as positioning strategies for a future energy portfolio rather than a substitute for the generation required to energize near-term projects.
The strategic value of SMRs instead lies in what could happen during the next phase of AI infrastructure expansion. If first-of-a-kind projects establish viable licensing pathways, manufacturing processes and construction economics, the technology could become increasingly relevant during the 2030s. The difference between today's power solution and tomorrow's power architecture is therefore critical. SMRs may arrive too late to solve the current interconnection crisis, but early enough to reshape how the next generation of gigawatt-scale AI campuses is developed.
Natural Gas Is Creating an Opening for Advanced Nuclear
Natural gas has emerged as one of the most practical near-term responses to the data center power shortage because it provides something developers urgently need: dispatchable electricity from commercially mature technology. The United States has abundant natural gas resources, turbines can provide continuous generation, and generation can potentially be developed close to large loads where sufficient pipeline infrastructure exists. As utility interconnection timelines lengthen, behind-the-meter and co-located gas generation is receiving substantially more attention from hyperscalers and infrastructure developers.
The challenge is that natural gas creates a different set of environmental and regulatory problems. Inside Climate News points to controversy surrounding gas turbines associated with xAI facilities in Tennessee and Mississippi, where environmental organizations have challenged turbine operations and alleged Clean Air Act violations. The article argues that growing resistance to off-grid gas generation could strengthen the case for continuously available low-carbon alternatives such as SMRs.
This dynamic illustrates why the data center energy challenge cannot be reduced to a simple competition between technologies. Developers increasingly need electricity that satisfies four difficult requirements simultaneously: reliability, speed, affordability, and lower emissions. Natural gas performs well on reliability and can potentially perform well on development speed, but emissions and permitting can become significant obstacles. Wind and solar provide scalable low-carbon electricity but cannot independently provide continuous firm generation. Batteries offer exceptional flexibility and rapid response but store electricity rather than create primary energy. Conventional nuclear provides firm low-carbon electricity but has historically involved very large projects, high capital requirements, and long construction schedules.
SMRs are attempting to occupy a unique position within that portfolio by combining nuclear reliability and emissions performance with smaller project sizes and potentially repeatable construction. If standardized manufacturing eventually reduces both cost and development time, advanced nuclear could provide data center developers with an alternative to building increasingly large fleets of natural gas generation. The market opportunity would be substantial because the demand is real; hyperscale developers are already searching for technologies that can deliver hundreds of megawatts of dependable electricity.
The Economics Still Have to Work
Technical compatibility does not automatically make an energy project viable. SMRs ultimately have to compete for capital, and data center developers will evaluate them against every other realistic source of electricity available at a particular location. The relevant comparison will involve much more than the reactor's theoretical generating cost because financing, construction risk, licensing schedules, fuel supply, operating expenses, transmission requirements, and the financial consequences of project delays all influence the delivered cost of electricity.
Inside Climate News highlights Ontario's Darlington New Nuclear Project as one of the most useful current benchmarks. The article cites estimates of approximately $140/MWh for the first BWRX-300 reactor, with the following three units projected around $80/MWh. It contrasts those figures with Lazard estimates for wind and solar generation ranging from below $40/MWh to approximately $86/MWh. The comparison is not perfect because variable renewable generation and firm nuclear generation provide different grid services, but the numbers demonstrate the central economic challenge confronting first-generation SMRs.
The projected decline between the first and subsequent Darlington units also illustrates the economic argument behind modular nuclear development. Traditional nuclear plants have often been enormous custom infrastructure projects, making it difficult to achieve the manufacturing repetition common in industries such as automotive, aerospace or semiconductor production. SMR developers hope standardized designs and factory-produced components will allow later reactors to benefit from accumulated manufacturing experience, reducing costs as deployment volume increases.
Investors and data center developers should nevertheless be cautious about assuming those reductions before they are demonstrated. NuScale's cancelled Utah Associated Municipal Power Systems project remains an important example. Inside Climate News notes that the project, which contemplated 12 modules totaling 600 MW, was terminated in 2023 after costs increased. Critics continue to cite the cancellation as evidence that commercial SMR economics remain unproven despite years of technological and regulatory progress.
For hyperscalers, the correct economic calculation must therefore include time as well as dollars. A resource promising inexpensive electricity but arriving several years after the computing infrastructure is ready could create enormous opportunity costs. Conversely, a more expensive power source that lets a multi-billion-dollar AI campus begin operating years earlier may ultimately create greater economic value. SMRs will have to demonstrate competitive lifetime economics while also proving that their construction schedules can meet the increasingly aggressive timelines of the data center industry.
Manufacturing May Determine Whether SMRs Ever Reach Scale
The word "modular" is central to the SMR value proposition because the long-term economic vision depends on reactors becoming repeatable industrial products rather than one-off megaprojects. Achieving that objective requires far more than a successful reactor design. Manufacturers need factories, specialized components, qualified suppliers, nuclear fuel, skilled labor and an industrial supply chain capable of producing multiple units consistently and safely.
Inside Climate News highlights this issue through comments from the Clean Air Task Force, which argues that nuclear power will require substantial investment in manufacturing capacity if it is going to make a meaningful contribution to U.S. load growth. Current supply-chain limitations create challenges for both commercialization and companies trying to build profitable advanced-nuclear businesses.
Manufacturing economics also create a classic infrastructure problem. Manufacturers need substantial order volumes before investing billions of dollars in factories and supply chains, while customers may hesitate to place large orders until manufacturing has demonstrated predictable costs and schedules. That circular problem has constrained many emerging energy technologies, but the AI boom could create a customer base that can break the cycle.
Technology companies, utilities and data center developers represent unusually well-capitalized electricity buyers with enormous long-term power requirements. If hyperscalers commit to standardized reactor fleets rather than isolated demonstration projects, they could provide the demand certainty manufacturers need to invest in production capacity. Large multi-reactor orders could allow suppliers to standardize components, train specialized workforces, and create the repetition required for genuine learning-curve cost reductions.
The relationship between AI and advanced nuclear could therefore become much deeper than simply one industry purchasing electricity from another. Data center demand could provide the commercial foundation needed to build an American SMR manufacturing ecosystem, while SMR manufacturing could eventually provide the scalable firm electricity needed to support continued AI expansion. Whether that mutually reinforcing relationship actually develops will depend on the success of the first commercial projects.
Nuclear Development Cannot Follow Silicon Valley's "Fail Fast" Model
The technology industry and nuclear industry approach innovation from fundamentally different starting points. Software companies routinely develop products quickly, deploy them to customers, identify problems, and release updated versions. That approach has produced extraordinary technological progress, but it cannot simply be transferred to nuclear energy, where design failures can have consequences far beyond an unsuccessful software release.
Inside Climate News emphasizes this cultural difference through nuclear experts who note that advanced reactor companies cannot approach product development like conventional technology startups. Nuclear projects require extensive engineering validation, regulatory review, security planning and safety analysis before commercial operation. Critics quoted in the article also warn that financial pressure to accelerate deployment or reduce costs should not weaken safety and security standards.
The collision between these two development cultures will become increasingly important as technology companies invest more aggressively in energy infrastructure. AI developers operate in an environment where computing hardware evolves rapidly, and competitive advantage can shift within months. Nuclear developers operate within an industry where projects can require many years of engineering, licensing, and construction. Successful collaboration will require technology companies to recognize that some regulatory and engineering processes cannot simply be compressed to match software development cycles.
At the same time, the nuclear industry will need to demonstrate that rigorous safety requirements do not necessarily require every project to become an entirely new engineering exercise. Standardized reactor designs, repeatable licensing processes, factory manufacturing and accumulated operational experience could eventually shorten deployment schedules without compromising safety. The long-term objective should not be to make nuclear development resemble software development, but to make advanced nuclear resemble a mature industrial manufacturing process in which standardized products are produced repeatedly under rigorous quality controls.
SMRs Should Complement Renewables and BESS Rather Than Compete With Them
Energy discussions frequently frame nuclear, renewable generation, natural gas and battery storage as competing solutions, but the enormous electricity requirements of AI infrastructure make that framework increasingly unrealistic. A 500 MW or 1 GW data center campus needs dependable electricity under a wide range of operating conditions, and no single generation technology perfectly optimizes reliability, cost, development speed, emissions and flexibility.
A future SMR could provide a large block of continuous generation that serves as the foundation of a campus energy system. Solar could supply inexpensive electricity during productive daylight hours, while wind could contribute substantial energy when resource conditions are favorable. Battery storage could respond almost instantaneously to changes in load or generation, provide power-quality services, manage short-duration peaks and shift renewable electricity across several hours. The utility grid could provide redundancy, access to broader generation resources and opportunities for market participation.
This type of hybrid architecture allows each technology to perform the function for which it is best suited. Nuclear does not need to replace renewable energy to create value; its role could be providing firm generation underneath a portfolio containing substantial wind and solar. Likewise, battery storage does not need to replace nuclear because batteries perform an entirely different set of functions. Storage provides flexibility and extremely fast response, while nuclear provides sustained energy production.
For AI infrastructure, this portfolio approach may ultimately be more valuable than pursuing a single "winning" generation technology. The scale of future electricity demand will likely require virtually every viable resource available, particularly in regions experiencing rapid data center development. The most successful campuses may therefore be those capable of combining firm generation, renewable energy, storage and grid connectivity into integrated systems designed around reliability and economics rather than technology preferences.
SMRs Could Eventually Reshape Data Center Geography
Power availability is already changing where data centers can be developed. A location with inexpensive land, excellent fiber and attractive incentives may still be commercially useless if the utility cannot provide several hundred megawatts within the required timeline. This constraint is pushing developers toward markets with available generation, strong transmission infrastructure, existing substations or opportunities to develop dedicated power resources.
Commercial SMRs could eventually alter that equation by allowing generation to become a more direct component of site development. A hyperscale developer capable of pairing a large campus with several hundred megawatts of dedicated nuclear generation would evaluate potential locations differently from a developer completely dependent on existing utility capacity. Transmission connectivity would remain important, but the project could potentially create a substantial portion of its own generation rather than waiting for distant power plants and major transmission upgrades.
This could lead to the development of entirely new AI energy campuses where generation, storage, computing, cooling and grid infrastructure are planned together from the beginning. Regions with suitable land, strong transmission connections, supportive regulatory environments and access to nuclear supply chains could potentially compete for hyperscale development even if they are not currently major data center markets. Existing nuclear communities could also become particularly interesting because they may already possess transmission infrastructure, experienced workforces and public familiarity with nuclear operations.
The geographic implications could become significant during the 2030s if SMRs achieve commercial scale. Today's data center industry is heavily concentrated in established markets such as Northern Virginia, Texas, Phoenix and Chicago, but severe power constraints -- like Texas's own recent pause on new data center approvals -- are already encouraging developers to evaluate new regions. Advanced nuclear would not eliminate the importance of fiber, workforce, water, permitting and transmission, but it could reduce one of the largest barriers to developing major computing campuses outside traditional data center corridors.
The Commercialization Gap Will Determine the Outcome
The advanced nuclear industry currently has no shortage of announcements, proposed partnerships and ambitious deployment plans. Technology companies, reactor developers, utilities, states and infrastructure investors increasingly view SMRs as a potential component of America's future electricity system. The harder challenge is converting announcements into operating power plants that consistently deliver electricity at predictable costs.
Inside Climate News appropriately presents both sides of that debate. Supporters emphasize nuclear's firm generation, low operational emissions, small footprint and potential manufacturing advantages, while critics point to years of development without commercial deployment, uncertain economics and canceled projects such as NuScale's UAMPS initiative. The article also notes that NuScale announced a partnership with the Tennessee Valley Authority in 2025 involving a proposed 6 GW deployment program, although additional project details remain limited.
The current electricity environment nevertheless creates conditions that are substantially different from those advanced nuclear companies faced a decade ago. AI is introducing enormous new loads, transmission constraints are becoming more visible, utilities need additional firm generation, and hyperscalers have both substantial capital resources and ambitious emissions objectives. At the same time, communities and regulators are increasingly scrutinizing whether rapid data center expansion will increase electricity costs, strain water resources, or require large amounts of new fossil generation.
Those conditions create something advanced nuclear has historically struggled to secure: a large group of financially strong customers with enormous long-term demand for exactly the type of electricity nuclear reactors are designed to produce. Data center developers need continuous power, technology companies have the financial capacity to support long-duration infrastructure investments, and the potential electricity demand is large enough to justify manufacturing entire fleets of reactors if the technology becomes commercially viable.
The next several years will therefore be less about proving that an SMR can theoretically generate electricity and more about proving that the entire commercial ecosystem works. Reactor companies must demonstrate licensing, manufacturing, construction, financing, fuel supply, operations and competitive delivered electricity costs. If those elements come together, AI could provide the demand necessary to push SMRs across the commercialization gap. If they do not, data center developers will keep deploying other technologies that can deliver electricity sooner.
Conclusion
Small modular reactors may eventually become one of the most important technologies supporting the AI infrastructure economy, but the distinction between potential and commercial availability is critical. SMRs offer a combination few generation technologies can provide simultaneously: firm electricity, low operational carbon emissions, high energy density, a relatively small physical footprint and the possibility of modular deployment close to large electricity loads. Those characteristics align exceptionally well with the requirements of hyperscale AI data centers.
The obstacles are equally significant. The United States still does not have a fully deployed commercial SMR, first-of-a-kind economics remain challenging, regulatory approvals require time, manufacturing capacity must expand, supply chains must mature and reactor developers must prove that modular construction can actually deliver the cost reductions and schedule improvements being promised. Safety and security standards also cannot become secondary simply because technology companies urgently need electricity.
For those reasons, SMRs should not be presented as the technology that will solve the immediate data center power shortage. Near-term AI development will continue relying on utility generation, natural gas, renewable energy, battery storage, existing nuclear facilities and enormous investments in transmission and substations. The more important question is what happens after the first generation of commercial SMRs establishes -- or fails to establish -- a repeatable development model.
If advanced nuclear companies can move from regulatory approval into standardized manufacturing and predictable commercial deployment, the relationship between computing and electricity could change substantially. Data centers could become anchor customers for fleets of modular reactors, nuclear generation could become more closely integrated with industrial electricity loads, and entirely new AI energy campuses could emerge around combinations of nuclear, renewables, BESS and grid infrastructure.
Artificial intelligence is forcing technology companies to become energy companies and data center developers to think increasingly like power developers. That transformation creates an enormous opportunity for any technology that can deliver reliable electricity at scale. SMRs may not solve the AI power challenge today, but if the technology successfully crosses the commercialization gap, advanced nuclear could become one of the foundational building blocks of the AI energy infrastructure of the 2030s and beyond.
Chris Kalowes, founder of WattThe?! — 15+ years in utility-scale battery energy storage (BESS), renewable energy, and AI infrastructure, across utilities, IPPs, EPCs, developers, and technology providers.
Source: Inside Climate News, "Trying to Get Away From Gas Turbines, Data Centers Place Their Hopes on Small Modular Nuclear Reactors," August 30, 2026.