Introduction

Despite the over 10,000 data centers already existing around the world, global data center demand is predicted to triple by 2030, with nearly 70 percent of the demand being driven by artificial intelligence (AI) workloads.¹ This surge in AI data center demand is fueled by the exponentially increasing use of AI at work and integration into daily lives as well as the AI race prompted by the recognition that AI technology can influence geopolitics, reorder the global economy, drive scientific discovery, and transform human lives and society.²

Beyond the predictions, 2025 started with announcements of investments into AI data centers: Project Stargate—supported by the Trump administration—pledged a $500 billion investment for AI infrastructure; and Meta announced a $60–65 billion pledge to AI and an AI data center.³ Globally, France announced that MGX, Bpifrance, Mistral AI, and Nvidia are collaborating on building Europe’s largest data center campus; EDGNEX Data Centres by DAMAC announced a $2.3 billion investment into a 144-megawatt AI data center in Indonesia; and Chinese tech firms plan to build more than 30 AI data centers with 115,000 Nvidia chips in the Xinjiang region.⁴

Two barriers to supporting this increased demand for AI data centers are the required energy and security.⁵ Yet while the energy concern has been highlighted and publicized, the security gaps have been relatively neglected.

Data centers already make up 1 to 2 percent of global energy demand, and data center energy demand is projected to increase to 21 percent by 2030 due to AI.⁶ The International Energy Agency reported that in 2024 AI servers drove 15 percent of electricity demand from data centers, and it projected that data center electricity consumption will more than double by 2030, with AI as the most influential factor.⁷ Recognizing the energy demand, President Biden issued the Executive Order on Advancing United States Leadership in Artificial Intelligence Infrastructure in January 2025, which heavily focused on federal support for AI data center energy needs and clean energy.⁸ Unfortunately, President Trump revoked this executive order six months later.

On the security front, though, AI data centers have mostly been considered as a part of traditional data centers and critical infrastructure with no separate or focused effort for AI data center cybersecurity requirements. For example, the Biden administration issued its National Security Memorandum on Critical Infrastructure Security and Resilience (NSM-22), which designated data centers as a critical part of U.S. infrastructure, indicating the importance of defending the critical infrastructure sectors from cyber activity led by nation-states.⁹ Beyond the United States, China’s 2016 Cybersecurity Law required data centers to have cybersecurity measures against domestic and foreign threats.¹⁰

However, AI data centers face an expanded set of threats. A successful cyberattack on an AI data center could enable threat actors to extract information about the AI model and weights, risking loss of sensitive training data as well as the integrity and confidentiality of the AI model.¹¹ When AI models are exfiltrated (stolen), hackers can create vulnerabilities in AI models, biased outputs, and similar AI models with fewer resources.¹²

Thus, this report recommends a comprehensive framework that identifies requirements for implementing sufficient cybersecurity measures in AI data centers. This report will first provide the methodology, followed by a brief history of traditional data centers and AI data centers. This background will help build a necessary foundation for the discussions of cyber threats to AI data centers. Finally, the report concludes with a framework and recommendations for a comprehensive cybersecurity approach.