When the National Institute of Standards and Technology announced a $20 million investment to strengthen artificial intelligence and cybersecurity, it didn’t sound flashy. No moonshots. No big promises about “revolutionizing everything overnight.” But beneath the surface, the move says a lot about where U.S. manufacturing and national security are headed.
The funding, announced by the National Institute of Standards and Technology, will support two new AI-focused research centers run in partnership with MITRE. One center will concentrate on applying AI to real-world manufacturing problems. The other will focus on protecting critical infrastructure, including industrial systems, from cyber threats that are becoming more sophisticated and more automated.
In simple terms, NIST is trying to solve two problems at once: how to help manufacturers actually use AI in practical, scalable ways, and how to make sure those AI-driven systems don’t become easy targets for hackers.
Manufacturing has quietly become one of the most attractive targets for cybercriminals. Factories are more connected than ever, using sensors, robotics, cloud platforms, and AI-driven analytics to manage production. That connectivity boosts efficiency, but it also creates more entry points for attackers.
According to IBM’s annual Cost of a Data Breach report, manufacturing was the most attacked industry globally in 2023, accounting for more than 25% of all cyber incidents. The average cost of a breach across industries reached $4.45 million, a record high. For manufacturers, the damage often goes beyond stolen data. Downtime, safety risks, and disrupted supply chains can ripple for weeks.
AI complicates things further. On one hand, it can help companies detect anomalies faster, predict equipment failures, and automate security monitoring. On the other hand, attackers are now using AI to scale phishing campaigns, generate malware, and probe systems more efficiently. The World Economic Forum has warned that AI-enabled cybercrime could significantly widen the gap between attackers and defenders if organizations don’t adapt quickly.
At first glance, $20 million may not sound like much in an AI world where large tech companies spend billions each year. But NIST’s role isn’t to outspend the private sector. It’s to create standards, shared tools, and trusted research that companies across the economy can build on.
Craig Burkhardt, NIST’s acting director, framed the investment as a way to “lower barriers” to adopting AI safely and responsibly. In other words, many manufacturers want to use AI but don’t have the expertise or confidence to deploy it without introducing new risks. Government-backed research can help fill that gap.
This approach aligns with NIST’s broader mission. The agency already plays a central role in cybersecurity through its widely adopted Cybersecurity Framework, which many organizations use as a baseline for managing cyber risk. Extending that influence into AI-driven systems is a logical next step.
Security experts often describe AI as a double-edged sword. Used defensively, it can dramatically improve how organizations respond to threats. IBM research suggests that companies using AI and automation in cybersecurity reduce breach response times by more than 100 days on average.
But attackers are moving fast. A 2024 report from Europol warned that generative AI is lowering the technical skill required to launch sophisticated attacks. Deepfake audio and video scams, for example, are already being used to impersonate executives and trick employees into transferring money or sharing credentials.
A survey by Accenture found that 36% of executives believe AI is advancing faster than their organization’s ability to secure it. Even more concerning, nearly 90% said they lack clear standards or governance for AI-related security risks. That disconnect is exactly the kind of problem NIST is trying to address with shared research and guidance.
Private companies often focus on immediate business needs, not long-term infrastructure resilience. That’s where federal agencies step in. By funding neutral research centers, NIST can help ensure that AI tools used in manufacturing and infrastructure are interoperable, transparent, and secure by design.
MITRE’s involvement is also significant. The nonprofit is known for its deep ties to federal agencies and for developing widely used frameworks such as MITRE ATT&CK, which helps organizations understand how cyber adversaries operate. Applying that kind of structured thinking to AI systems in manufacturing could help companies anticipate threats before they cause real damage.
Industry groups have welcomed the move. Analysts at Boston Consulting Group have noted that while more than half of executives rank AI-enabled cyber threats among their top concerns, only a minority are investing seriously in AI-driven defenses. Public-private partnerships can help close that gap, especially for mid-sized manufacturers that don’t have large security teams.
NIST hasn’t yet released details about where the new centers will be located or exactly how the funding will be allocated. What’s clear is that this is not meant to be a one-off effort. The investment fits into a broader federal push to strengthen U.S. leadership in AI, semiconductors, and advanced manufacturing while protecting critical systems from disruption.
As Manufacturing Dive reported, the goal is to move beyond theory and into applied solutions that companies can actually use. That means testbeds, pilot projects, and guidance that reflect real factory conditions, not just lab environments.
Cybercrime is expected to cost the global economy more than $10 trillion annually by the middle of this decade, according to Cybersecurity Ventures. Manufacturing sits right at the intersection of digital innovation and physical impact, making it both a driver of growth and a high-stakes target.
NIST’s $20 million investment won’t solve the AI cybersecurity problem on its own. But it sends a clear signal: AI is now part of the nation’s critical infrastructure and securing it is no longer optional. For manufacturers weighing how far and how fast to adopt AI, that kind of leadership could make all the difference.
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