Nuclear Energy as a Strategic Power Solution for AI-Driven Data Centers

The exponential growth of artificial intelligence (AI) has redefined global energy demands, with data centers projected to consume over 8% of global electricity by 2030, according to Goldman Sachs Research. As AI infrastructure scales, the need for reliable, low-carbon power sources has become urgent. Nuclear energy, long debated for its role in decarbonization, is emerging as a strategic solution for AI-driven data centers. This article evaluates the investment potential of revitalized nuclear assets in an energy landscape increasingly shaped by AI's insatiable appetite for power.

The Energy Imperative: AI's Growing Appetite

AI training and inference operations require continuous, high-capacity power. Goldman Sachs Research estimates that up to 85–90 gigawatts (GW) of new nuclear capacity may be needed globally by 2030 to meet AI data centers' projected 160% surge in power demand. Unlike intermittent renewables, nuclear power provides baseload electricity, ensuring 24/7 operations without carbon emissions. This makes it an ideal partner for AI infrastructure, where reliability and sustainability are non-negotiable.

Nuclear Capacity Expansion: A Decade of Growth

Global nuclear energy capacity is set to grow from 395 GW in 2024 to 494 GW by 2035, driven by advancements in small modular reactors (SMRs) and decarbonization goals, according to GlobalData. The International Energy Agency (IEA) forecasts a 50% increase in nuclear capacity by 2050 under its STEPS scenario, while IAEA projections in the IAEA's high-case anticipate a 2.6-fold rise to 992 GW by mid-century. SMRs, accounting for 24% of new capacity in the IAEA's high-case scenario, are particularly well-suited for AI applications due to their scalability and reduced costs, GlobalData notes.

Investment Trends: Institutional Confidence in Nuclear Energy

The nuclear energy sector has attracted significant institutional investment, particularly in companies like Centrus Energy Corp. (NYSE: LEU), a key player in nuclear fuel supply. In Q3 2024, Kovitz Investment Group Partners LLC acquired a $1.64 million stake in Centrus, while Stifel Financial Corp increased its holdings by 48.2%, according to a MarketBeat alert. The MarketBeat alert also observed that institutional investors own nearly 50% of Centrus' stock, reflecting growing confidence in nuclear energy's role in the AI era.

Case Studies: Tech Giants Partner with Nuclear Providers

Microsoft's partnership with Constellation Energy to restart the Three Mile Island Unit 1 reactor in Pennsylvania exemplifies the tech-nuclear convergence. The 20-year agreement aims to deliver carbon-free energy for Microsoft's data centers, according to Georgia Tech. Similarly, Google and Amazon have invested in SMR developers Kairos and X-Energy, respectively, as detailed in a Georgetown analysis. These partnerships highlight the urgency of securing stable power sources for AI operations, even as SMR deployment faces delays due to regulatory and technical hurdles, the Georgetown analysis notes.

Government Subsidies and Policy Tailwinds

Recent policy developments have accelerated nuclear-AI integration. In May 2025, President Donald J. Trump signed an executive order mandating the deployment of advanced nuclear technologies to power AI infrastructure and military installations, as outlined in a White House fact sheet. The U.S. Department of Energy (DOE) has also fast-tracked permits for nuclear projects at 16 federal sites, positioning them as hubs for AI data centers, per a DOE announcement. These initiatives underscore nuclear energy's strategic value in national security and energy independence.

Financial Metrics: ROI and Risks

The financial performance of companies integrating AI with nuclear assets reveals a mixed landscape. Palantir Technologies secured a $100 million contract to develop an AI nuclear operating system, leveraging its platforms to optimize energy operations, according to a TS2 report. Meanwhile, BigBear.ai's stock surged 314% in 12 months due to defense AI contracts but reported an $18.6 million Q2 2025 loss, as noted in a TS2 analysis. These cases highlight the high-risk, high-reward nature of investing in nuclear-AI ventures, where technological promise often outpaces profitability.

Challenges and Mitigation Strategies

Despite its potential, nuclear energy faces challenges:
- Regulatory Hurdles: SMR licensing remains complex and time-consuming, according to an SMR study.
- Public Perception: Safety concerns and nuclear waste management persist, as Georgia Tech observes.
- Economic Barriers: High upfront costs and long construction timelines deter short-term ROI, the Georgetown analysis warns.

To address these, experts recommend policy reforms, R&D funding, and public-private partnerships; the SMR study specifically highlights these measures. A diversified energy strategy-combining nuclear with renewables and storage-may also mitigate risks while meeting AI's immediate demands, as Goldman Sachs Research suggests.

Conclusion: A High-Stakes Opportunity

Nuclear energy's role in powering AI infrastructure is no longer speculative but strategically imperative. With global capacity set to double by 2050 and tech giants forging critical partnerships, the sector offers compelling long-term investment potential. However, success hinges on overcoming regulatory, technical, and financial barriers. For investors, the key lies in balancing optimism with caution, targeting companies and projects with clear policy support and scalable technologies.