Unleashing AI across the US government: The data security challenge holding back decision advantage
Unleashing AI across the US government: The data security challenge holding back decision advantage
Publish Date: 2026-05-08 14:41:00
Source Domain: www.nextgov.com
During my years leading IT strategy at the Department of Defense and the Navy, I witnessed firsthand the frustrating paradox that continues to plague government artificial intelligence initiatives: we’re sitting on mountains of valuable data that could revolutionize mission outcomes, yet we can’t actually use most of it with AI systems.
The problem isn’t technology adoption, since federal agencies are rapidly deploying AI and machine learning capabilities. The challenge is that our most sensitive data — the information that could provide genuine decision advantage — remains locked away because our current security architectures can’t protect it at scale once AI systems begin processing it.
The promise of augmented intelligence
Let’s be clear about what’s at stake. When properly implemented, AI — or what I prefer to call “augmented intelligence” — represents a crucial advancement in how government operates. From predictive maintenance on weapons systems to accelerated threat detection in cybersecurity, from streamlined acquisition processes to improved resource allocation, AI has the potential to enhance every aspect of federal operations.
The Pentagon’s emphasis on responsible AI — built on principles of equitable, traceable, reliable, governable and transparent usage — provides the right ethical framework. We understand that humans must remain in the loop for critical decisions, particularly those involving national security or individual rights. We’ve established governance structures and invested in quality, auditable data pipelines.
But here’s what keeps CIOs and CISOs awake at night: all these careful preparations become meaningless if we can’t secure the data during AI processing.
The decrypt-to-use vulnerability
Today’s AI systems, including the increasingly popular Retrieval-Augmented Generation (RAG) models that federal agencies are deploying, have a fundamental security limitation. To analyze data, they must decrypt it first. This creates…
