Genesis Catalyst: A National AI Platform to Advance Scientific Progress
03 December 2025
On November 24, 2025, the White House issued an Executive Order launching the "Genesis Mission." Anchored at the Department of Energy (DOE) and coordinated through the National Science and Technology Council (NSTC), the Mission directs the build-out of a secure, integrated AI platform to accelerate scientific discovery, strengthen national security, and reinforce US technology leadership.
The plan taps decades of federal investment in data and supercomputing-especially at DOE labs-while setting clear guardrails for cybersecurity, classification, export controls, and IP. It also opens structured pathways for public-private collaboration.
What's being built
At the center is the American Science and Security Platform. This is a secure, integrated infrastructure that brings together high-performance computing (DOE supercomputers and secure cloud), AI modeling frameworks and domain-specific foundation models, and governed access to diverse datasets.
It supports predictive and simulation workloads, automated research workflows, and autonomous or AI-augmented experimentation and manufacturing. The Platform is built to meet classification handling, federal cybersecurity, and supply-chain compliance requirements.
Who runs it
The DOE Secretary is responsible for implementation, with day-to-day leadership designated as needed. The Assistant to the President for Science and Technology (APST) coordinates agencies via the NSTC. DOE oversees a centralized, multi-agency Platform with standardized collaboration and IP mechanisms.
Priority domains and national challenges
Within 60 days, DOE will propose at least 20 national challenges across:
- Advanced manufacturing
- Biotechnology
- Critical materials
- Nuclear fission and fusion
- Quantum information science
- Semiconductors and microelectronics
Within 30 days after that, APST will coordinate an expanded list through the NSTC. Agencies will use the Platform to pursue aligned R&D with annual updates.
Milestones you can plan around
- Within 90 days: Inventory federal and partner computing, storage, and networking resources; identify gaps and partnerships.
- Within 120 days: Identify initial data and model assets; publish a risk-based plan for integrating external datasets.
- Within 240 days: Review robotic labs and production facilities for AI-directed experimentation and standards.
- Within 270 days: Demonstrate initial operating capability for at least one challenge (subject to appropriations).
- Within one year and annually: Report to the President on operations, integration, user engagement and training, research outputs, partnerships, and needed authorities.
Public-private collaboration
The Order directs DOE and APST to standardize user-facility partnerships, data/model-sharing agreements, and IP policies (including for AI-directed experiments). Expect uniform data access and cybersecurity controls that cover classification, privacy, and export-control compliance.
Through the NSTC, the Administration may also launch coordinated funding and prize programs and expand fellowships, internships, and apprenticeships in AI-enabled science, including placements at DOE laboratories.
Data, security, and compliance
Platform participation will require rigorous data management aligned with federal standards, federal-grade cybersecurity spanning cloud and supply-chain assurance with continuous monitoring, and built-in classification handling and export-control screening. Privacy protections are explicit.
If you run data pipelines or lab automation, plan for auditable controls, provenance tracking, and role-based access across classified and unclassified environments.
Implications for labs, universities, and industry
Demand for AI capabilities is set to surge-computing, data engineering, model development, and autonomous experimentation. Near term, expect concrete opportunities around access to high-performance computing and secure AI environments for training and evaluation.
Applied use cases include AI-accelerated design and prototyping in advanced manufacturing and materials; foundation models plus autonomous labs for biotech under strict biosecurity protocols; and AI-driven workflows for semiconductor and microelectronics design, verification, and production.
There is clear momentum for dual-use applications across national security and energy-nuclear, fusion, critical materials, and supply-chain resilience. The policy context points to a strong, government-supported pipeline of translational R&D with clearer federal routes to commercialization.
Set expectations for stringent compliance and export-control sensitivities, especially for dual-use tech and critical infrastructure. Timelines are ambitious and may shift, but the demand signal, program structure, and emphasis on governance and security are unmistakable.
What to do next (practical steps)
- Map assets: Document your compute, storage, networking, and data catalogs. Identify what can federate into federal environments.
- Data readiness: Triage datasets by sensitivity, provenance, licensing, and export-control status. Prepare metadata and access policies.
- Security posture: Align to federal baselines (identity, least-privilege, monitoring, software supply chain). Validate readiness for classified workflows if applicable.
- Model strategy: Prioritize domain-specific foundation models you can contribute or fine-tune; define evaluation protocols.
- Lab automation: Assess robotic labs and pilot autonomous workflows with safety interlocks and audit trails.
- IP and agreements: Pre-draft IP terms for AI-directed experiments, data/model sharing, and joint publications.
- Workforce: Stand up fellowships, internships, and apprenticeships aligned to AI-enabled science; build training plans for PIs and research staff.
- Pick a pilot: Choose one challenge area and scope a 270-day demonstration with measurable outcomes.
Why this matters
The Mission introduces a centrally coordinated, security-hardened AI platform with near-term demonstrations and recurring reporting. Interagency alignment, data governance, cybersecurity, and IP clarity are the levers. Early movers will help set practical standards for AI-enabled science at national scale.
Resources
- National Science and Technology Council (White House)
- DOE Office of Science - Advanced Scientific Computing Research
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