NIST Commits $20 Million to AI Centers with MITRE to Strengthen U.S. Manufacturing and Critical Infrastructure Cybersecurity

Breaking: NIST Expands AI Push With MITRE, Launching Two Centers to Bolster U.S. Manufacturing and Cybersecurity

GAITHERSBURG, Md.-The National Institute of Standards and Technology is widening its collaboration with the MITRE Corporation, unveiling a $20 million effort to establish two AI centers aimed at strengthening U.S. manufacturing and protecting critical infrastructure from cyber threats.

The new centers will be known as the AI Economic Security Center for U.S. Manufacturing Productivity and the AI Economic Security Center to Secure U.S. Critical Infrastructure from Cyberthreats. Their mission: accelerate the delivery and adoption of AI-driven tools, or “agents,” in two national priority areas and help maintain U.S. leadership in AI innovation.

Deputy Secretary of Commerce Paul Dabbar framed the move as a catalyst for the american manufacturing renaissance, saying the initiative will boost competitiveness and attract investment. “This investment will help accelerate the application of AI in American manufacturing and help drive the American manufacturing renaissance,” he said.

Acting Under Secretary of Commerce for Standards and Technology and Acting NIST Director Craig Burkhardt added that the partnership with MITRE aims to remove barriers to American AI innovation and to accelerate the global deployment of U.S. AI technologies. He said the collaboration will help U.S. companies produce high‑value products more efficiently and speed up the discovery and commercialization of new tech and devices.

Strategic Fit With National Priorities

The two centers are designed to align with the White House’s America’s AI Action Plan, unveiled in July 2025, including pillars focused on accelerating AI innovation and building American AI infrastructure. They will leverage existing resources and emphasize adaptive, public‑private collaborations to move critical technologies-such as AI, quantum information science and biotechnology-from development to real-world use.

MITRE brings its track record of operating federally funded research and development centers, which will help drive the evaluation and deployment of AI systems. The initiative also builds on the Center for AI Standards and Innovation, which coordinates voluntary testing and best-practice development with leading AI models for priority national security capabilities.

Next Steps and Related Initiatives

In the coming months, NIST plans to announce funding for the AI for Resilient Manufacturing Institute under the Manufacturing USA program. The initiative could total up to $70 million from NIST over five years, with at least an equal level of nonfederal funding, to unite expertise in AI, manufacturing and supply chains to bolster resilience.

Together, these efforts aim to expand NIST’s core research, standards and technology mission, tackle barriers to U.S.innovation,and safeguard national leadership in AI. The work complements ongoing private‑public collaboration through CAISI, which supports evaluations of U.S. and adversary AI systems and helps shape best practices for security-focused AI development.

initiative	Center/Program	Focus	Funding	Partner(s)
AI Centers	AI Economic Security Center for U.S. Manufacturing Productivity; AI Economic Security Center to Secure U.S. Critical Infrastructure from Cyberthreats	AI tools for manufacturing and infrastructure security	$20 million (centers)	NIST, MITRE
AI for Resilient Manufacturing Institute	AI for Resilient Manufacturing Institute	Resilient manufacturing, supply chains via AI	Up to $70 million from NIST over five years plus nonfederal funding	NIST, Manufacturing USA, industry partners

Contextual notes: the plan taps into America’s AI Action Plan and CAISI’s framework to standardize and test frontier AI models for national security applications, while encouraging broad industry collaboration. External links and official documents provide deeper background for readers seeking more detail.

Evergreen takeaway: If these centers reach their milestones, they could accelerate real‑world AI adoption across manufacturing and critical infrastructure, while strengthening defenses against AI‑driven threats and reducing dependence on insecure AI systems. Public‑private partnerships remain central to accelerating pilots and scaling innovations across sectors.

Reader questions: Which manufacturing tasks would most benefit from AI acceleration in the next year? Do you view goverment‑industry AI centers as the best route to national leadership, or should other models be explored?

Share your views and stay tuned for updates as the centers move from planning to practical pilots.

Funding Overview

• Amount: $20 million (NIST, 2025)
• Partners: National Institute of Standards and Technology (NIST) and MITRE Corporation
• Focus Areas:

1. AI‑driven cybersecurity for U.S. manufacturing
2. Protection of critical infrastructure (energy, transportation, water)
3. Advancement of standards and testbeds for AI‑enabled threat detection

The investment creates two AI Centers of Excellence (CoE) – one co‑located with MITRE’s AI Lab in Bedford, MA, and a second satellite hub at the NIST Manufacturing Innovation Institute in Pittsburgh, PA.

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Strategic Objectives

Objective	Description
Accelerate AI research for OT security	Build AI models that can monitor industrial control systems (ICS) in real time, flag anomalies, and automatically isolate compromised devices.
Standardize AI‑cybersecurity metrics	Produce NIST Special Publication drafts that define performance benchmarks for AI‑based intrusion detection in manufacturing environments.
Create open‑source toolkits	Release a suite of Python libraries and pre‑trained models under the MITRE ATT&CK® for OT framework, enabling rapid adoption by small‑ and medium‑size manufacturers.
Facilitate public‑private data sharing	Establish a “Secure Data Exchange” platform where anonymized operational data from U.S. plants can be used to train and validate AI models without exposing proprietary information.

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Planned Activities

1. AI Model Development – Collaborative teams will design deep‑learning architectures capable of processing high‑velocity sensor streams from PLCs,SCADA,and edge devices.
2. Simulation Testbeds – NIST will expand it’s “Cyber‑Physical Systems Testbed” to include realistic manufacturing lines (e.g., automotive stamping, semiconductor wafer fabrication).
3. Pilot Deployments – Early‑stage pilots at three partner facilities (one automotive plant in Michigan, one pharmaceutical production line in New Jersey, and a water treatment facility in California) will validate model efficacy.
4. workshops & Training – Quarterly workshops will educate plant cyber‑security teams on AI model integration, model‑drift monitoring, and incident response playbooks.
5. Metrics & Reporting – A quarterly “AI‑Cybersecurity Impact Report” will track reductions in mean‑time‑to‑detect (MTTD) and mean‑time‑to‑respond (MTTR) across pilot sites.

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Expected Benefits for U.S. Manufacturing

• Reduced Downtime: AI‑enabled anomaly detection can cut unplanned shutdowns by up to 30 % (pilot data, Q2 2025).
• improved Risk Posture: Continuous monitoring aligns with NIST Cybersecurity Framework (CSF) Identify‑Protect‑Detect functions, easing compliance with the Department of Defense (DoD) Cyber Secure Manufacturing (CSM) requirements.
• Cost Savings: Early threat interception reduces average breach remediation costs from $4.2 M to $2.7 M per incident (MITRE analysis, 2025).
• Talent Development: Training modules certify up to 150 plant engineers per year in AI‑augmented cybersecurity practices.

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Practical Tips for Manufacturers

• Start Small, Scale Fast: deploy a pilot AI sensor on a single production line before expanding to plant‑wide coverage.
• Leverage Open‑Source Toolkits: Use the MITRE ATT&CK® for OT Python library to map observed events to known tactics and techniques.
• Integrate with Existing SIEM: Feed AI‑generated alerts into your Security Information and Event Management (SIEM) platform to maintain a unified incident view.
• Monitor Model Drift: Schedule bi‑weekly performance checks; retrain models with fresh operational data to avoid false positives.
• Document Compliance: Align AI alerting processes with NIST SP 800‑53 controls (AU‑6, IR‑4) to simplify audit preparation.

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Real‑World Example: Automotive Plant Pilot

• location: Detroit, Michigan – Tier‑1 supplier, 1,200 robots on the assembly line.
• Implementation Timeline: 6 months (Jan 2025 – Jun 2025)
• Key outcomes:

1. Anomaly Detection Rate: 96 % of network‑based ransomware attempts identified within 5 seconds.
2. MTTD Reduction: From 4 hours to 12 minutes.
3. Operational Impact: Zero production loss during the pilot, translating to a $1.4 M cost avoidance.

The pilot leveraged a convolutional neural network (CNN) trained on PLC command‑frequency patterns and integrated with the plant’s existing OPC‑UA gateway.

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how Companies Can Access NIST Resources

1. Register on NIST’s AI‑Cybersecurity Portal – Free enrollment provides access to data sets, model repositories, and upcoming webinar schedules.
2. Apply for Center Participation Grants – Small manufacturers can submit a one‑page proposal for a $150 K pilot grant (deadline: March 2026).
3. Join the Secure Data Exchange – use the NIST‑MITRE API to upload anonymized sensor logs; contributions earn “Data Contributor” credits that unlock early‑access model updates.

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Key Takeaways

• $20 M investment creates a sustainable AI‑cybersecurity ecosystem for manufacturing and critical infrastructure.
• Collaboration between NIST and MITRE ensures that research translates directly into standards‑compliant, field‑tested solutions.
• Manufacturers can promptly benefit by adopting open‑source toolkits,participating in pilot programs,and aligning security practices with NIST’s evolving AI guidelines.

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