The Intelligent Grid: Mission Autonomy and Resilient Systems with Quantum-Safe, Critical Infrastructure

As quantum computing advances, many critical infrastructure systems worldwide face increased risks. These include internet infrastructure, electrical grids, water management, energy production and distribution, as well as financial, healthcare, and transportation systems. What is needed is a system that can automatically detect and fix problems, make independent decisions, and employ next-generation encryption to stay fully secure from future cyberattacks. This year's Energy, Infrastructure, and Environment (EIE) Summit will address these urgent issues by exploring how to deploy self-healing architectures and strengthen them with quantum-safe cryptography to ensure long-term, unbreakable infrastructure resilience. As environmental instability and cyber threats grow, critical infrastructure requires more than just predictive software: it needs autonomous adaptability. Agentic AI networks capable of real-time decision-making and decentralized operation are essential. By leveraging multi-agent AI systems, automated load balancing, and secure edge-computing operational technology (OT), federal and defense leaders are creating self-healing microgrids that can quickly reroute power during crises. To that end, the Department of Energy (DOE), Department of War (DoW), and commercial innovators are expanding these agentic systems to safeguard domestic energy grids and strengthen forward-operating bases. Public sector thought leaders will share how federal agencies respond to and deliver innovative solutions that modernize, secure, scale, and solve energy demands and threats. Topics to be explored will cover: Moving beyond predictive software to autonomous AI agents that dynamically reroute power during cyberattacks or extreme weather events. Practical timelines and deployment strategies for integrating Post-Quantum Cryptography (PQC) into legacy federal SCADA networks. Designing intelligent, self-regulating infrastructure capable of managing the enormous energy demands of federal AI data centers. Describe impactful AI use cases that agencies are implementing, including how they prepare their workforce for responsible AI adoption with governance and reporting tools, data analysis platforms, secure enterprise integrations, and context-aware digital assistants to automate and personalize workflows.