AI for Grid Resilience and Security Challenge

Due: February 10, 2026

The intersection of AI, critical infrastructure, and energy grids are a symbiotic necessity, where AI serves as both the primary driver of new electricity demand and the essential tool for managing a complex and secure critical infrastructure. Inspired by the Department of Energy’s emerging Genesis Mission, this Challenge invites innovators to explore how advanced AI models and tools can support national critical infrastructure.

Areas of Interest:

Operational Intelligence & Automation
  • Agentic AI for Grid Reliability
  • Self-Healing Infrastructure
  • Simulation/Digital Twins
Distributed Energy Integration
  • Hyper-local Forecasting
  • Dynamic Line Rating (DLR)
  • Virtual Power Plants (VPPs)
Managing the AI-Driven Demand Shock
  • Data Center Load Flexibility
  • On-site Generation & SMRs
  • Transmission Optimization
Security and Resilience
  • AI-Enhanced Cybersecurity
  • AI for air-gapped or restricted networks
  • Sovereign AI Clouds
AI for Transportation & Traffic Management
  • Fleet and logistics optimization
  • Energy-aware routing and congestion management
  • Resilient operations during disruptions or emergencies
AI for Video & Sensor Data Management
  • Intelligent triage of video or imagery streams
  • Event detection and anomaly identification
  • Reducing cognitive load for human operators
Other AI Applications for Grid Resilience

Who Should Participate

  • Businesses of all sizes developing advanced AI models, platforms, or tools that can be adapted for secure and classified environments
  • National laboratories, manufacturers, utilities, and site operators seeking to co-develop AI capabilities for critical infrastructure
  • Providers of secure, accredited cloud environments and AI development platforms capable of handling sensitive and classified data

Scope & Innovation Guardrails

  • Mission Alignment – Solutions must clearly connect to grid resilience, urban infrastructure, or critical infrastructure security-adjacent operational environments.
  • Security by Design – Proposals must demonstrate awareness of classified or high-sensitivity constraints and incorporate defense-in-depth thinking.
  • Operational Realism – Solutions should reflect real deployment pathways within national labs, secure sites, or regulated infrastructure.
  • Trust & Transparency – AI outputs must be interpretable and governable by human operators.
  • Measurable Impact – Teams should define concrete performance metrics and anticipated operational benefits.
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