2025-08-05 –, Copa
This talk explores how energy infrastructure forms the backbone of resilient and robust AI ecosystems and challenges like transformer shortages and foreign dependencies threaten AI ecosystems and national security. We'll examine how disruptions in the energy sector can cascade across AI development, national security, and global competitiveness. By focusing on the often-overlooked role of power infrastructure, including the critical shortage of domestic sourced electrical equipment such as transformers, we'll reveal how energy resilience is the true key to AI dominance beyond algorithms and computing power.
The United States faces a multifaceted challenge in maintaining its technological edge, particularly in AI. While much attention is given to semiconductor production and algorithm development, the foundation of AI supremacy lies in a stable, resilient, flexible, and abundant energy infrastructure. Private capital flows into chips and frontier models; government agencies and labs can only chase and shape the attention of resources. Disruptions in one sector can profoundly impact another: recent challenges, such as the extreme shortage of voltage step-down transformers and heavy reliance on non-domestic equipment, significantly hinder the growth and expansion of AI data centers.
Moreover, U.S. utilities and energy projects remain heavily reliant on non domestic equipment - for large and distribution power transformers, battery energy storage systems, and communications equipment - introducing potential cybersecurity risks that could destabilize power grids and erode energy resilience. China's control over critical mineral processing further compounds U.S. supply chain fragility, threatening to disrupt key industries essential for AI infrastructure. This interconnectedness demonstrates that dominance in AI is not just about computational performance but about securing and optimizing the power that fuels it.
Dr. Emma M. Stewart, is a respected power systems specialist with expertise in power
distribution, clean energy, modeling, and simulation, as well as operational cybersecurity. She
holds a Ph.D. in Electrical Engineering and an M.Eng. degree in Electrical and Mechanical
Engineering. Emma is Chief Scientist, Power Grid at INL currently and leads activities in supply
chain consequence analysis for digital assurance in particular for clean energy cybersecurity
related programs. Throughout her career, Dr. Stewart has made significant contributions to the
field of power systems, receiving patents for innovations in power distribution systems and
consequence analysis for cyber and physical events. Her responsibilities have also included
providing electric cooperatives with education, training, information sharing, incident support,
technology integration, and R&D services in clean energy integration, resilience and grid
planning and microgrid technologies.
Munish Walther-Puri is a seasoned risk advisor and security strategist with two decades of experience translating complex cybersecurity and geopolitical realities into actionable frameworks. His expertise lies in identifying critical blind spots for decision-makers and developing innovative risk assessment methodologies. Currently, he serves as Interim Deputy CISO for a major manufacturer, building enterprise IT GRC programs and uplifting cybersecurity maturity. Munish's career spans diverse roles, including VP of Cyber Risk at Exiger, first Director of Cyber Risk at NYC Cyber Command, and Chief Research Officer at a dark web monitoring startup. His academic engagements include adjunct faculty positions at NYU, Columbia, and IANS Research, as well as a focus on the nexus of cyber, tech, national security, and industrial policy. He is a Life Member of the Council on Foreign Relations and a Senior Fellow at the Institute for Security and Technology. With a keen interest in the intersection of cyber, geopolitical, and supply chain risks, Munish is committed to bridging theory and practice, contributing to academic discourse, and advancing cutting-edge research in interconnected risk.