Author: Bill Moore
Published: 1/14/2026
The National Institute of Standards and Technology (NIST) in collaboration with the MITRE Corporation announced late last month that it’s investing $20 million to establish two AI Economic Security Centers.
One will focus on advancing AI solutions for U.S. manufacturing. The other will work to secure critical infrastructure from cyber threats. The centers are part of a broader effort that includes NIST’s planned AI for Resilient Manufacturing Institute, which will receive up to $70 million over five years.
It’s an important moment. Not because of the dollar figure, but because it forces us to confront realities that have long been deferred in favor of operational continuity. It’s also important because of what it represents. We’re now actively introducing AI into environments where a wrong decision can mean physical consequences, operational disruption, or cascading failures across critical systems.
Moving forward, AI systems will not just observe, but recommend, decide, and act at a speed and scale humans can’t match. In industrial environments, that’s both exciting and uncomfortable. Productivity gains are real. So are the risks. And those risks demand we take a hard look at whether we’re actually ready for this shift.
This pressure has emerged now for a reason. Industrial environments are more connected than they have ever been, driven by remote operations, distributed workforces, and the need to operate assets across wider geographic footprints. At the same time, AI capabilities have matured from niche analytics into tools that organizations increasingly expect to operate in real time. Add workforce constraints and growing operational complexity, and we have convergence that makes AI adoption feel less optional and more inevitable.
NIST’s announcement reflects that reality: It’s no longer a discussion on whether AI will get introduced into these environments. The conversation has shifted to whether we will do it deliberately or by necessity, and whether existing operating and security models can handle it.