Strategic Knowledge Infrastructure

Artificial intelligence is eroding one of the foundational assumptions of modern technological superiority: that knowledge can be reliably traced to its source.

To preserve its technological and military advantage, the United States must build a Strategic Knowledge Infrastructure (SKI)—a foundational verification layer embedded across the nation's digital infrastructure that treats data provenance not as an administrative compliance exercise, but as an essential component of national defense.

Artificial intelligence challenges these assumptions. Information is no longer simply transferred between secure entities in discrete transactions. Instead, machine-learning systems continuously merge, transform, and regenerate data through complex computational processes that often leave no auditable record. As these models grow more sophisticated, assigning ownership, liability, or responsibility becomes increasingly difficult.

This provenance gap introduces significant operational risks across the Pentagon's digital ecosystem, particularly for the U.S. Navy's globally deployed forces. Naval modernization depends on decades-long engineering programs, highly integrated supply chains, digital twins, and distributed command-and-control networks. As AI becomes embedded in fleet readiness, ship design, autonomous systems, logistics, and weapons development, confidence in the underlying data becomes mission critical.

The Navy cannot afford uncertainty over whether an engineering file for a critical propulsion valve, an autonomous drone component, or a radar-array simulation was generated from trusted data or synthesized through an opaque AI process. If the lineage of a software update or a machine-generated blueprint cannot be verified, confidence in operational performance, maintenance decisions, and combat readiness begins to erode. Likewise, partnerships with defense contractors, commercial technology firms, and allied nations depend upon proprietary designs and classified research remaining distinct, attributable, and verifiable throughout their lifecycle.

The operational costs of fragmented data architectures are already visible across the Indo-Pacific. Despite important initiatives such as the Quad's Indo-Pacific Maritime Domain Awareness (IPMDA) partnership, the region continues to experience friction in integrating maritime information from multiple national systems.

Platforms such as India's Information Fusion Centre–Indian Ocean Region and U.S. maritime awareness systems like SeaVision often operate under different technical standards, classification rules, and data-sharing protocols. The challenge today is interoperability. Tomorrow it will be provenance.

When commercial satellite imagery, unclassified vessel tracking, and military sensor data cannot be fused under common verification standards, the operational picture becomes fragmented, and response times suffer. As AI increasingly analyzes these same data streams to predict adversary movements and support operational decisions, the consequences of uncertain data lineage will only grow. Tactical success will depend not simply on sharing information, but on ensuring that every participant can trust where that information originated and how it has been transformed.

The costs of this architectural gap extend well beyond the battlefield. Across the defense industrial base, uncertainty over AI-generated intellectual property is slowing technology transfers, complicating acquisitions, and increasing legal risk. Licensing negotiations have become more complex. Compliance costs rise. Intellectual property disputes multiply. In a strategic competition where speed itself is an advantage, uncertainty becomes a self-imposed tax on innovation.

When foundational institutions can no longer verify knowledge lineage, innovation becomes slower, more expensive, and less predictable.

Beijing understands that long-term technological leadership depends not only on developing advanced AI systems but also on shaping the infrastructure through which knowledge flows. China has invested aggressively in standards-setting, digital infrastructure, industrial policy, and data governance because it recognizes that tomorrow's competitive advantage will be determined by trusted ecosystems as much as technological breakthroughs.

Washington, by contrast, has concentrated on protecting the perimeter through export controls, investment screening, and supply-chain security. Those tools remain indispensable, but they address only part of the challenge. Guarding a technology is of limited value if we cannot reliably prove who owns it or where it originated within our own innovation ecosystem.

Existing legal and security frameworks leave a significant gap. Intellectual property law resolves disputes after infringement occurs. Export controls govern technology crossing borders. Cybersecurity protects systems against intrusion. None were designed to preserve continuous knowledge lineage as AI creates, transforms, and recombines information at machine speed.

This missing verification layer represents a strategic vulnerability. America possesses increasingly sophisticated hardware, software, sensors, and AI models, but it lacks a common architectural capability for verifying the provenance of the information driving them.

The potential solution to this vulnerability lies in introducing a secure, centralized architecture layer designed to natively enforce standardized data governance protocols. By doing so, defense organizations can establish a permanent and unalterable baseline for algorithmic trust.

Strategic Knowledge Infrastructure fills that gap by embedding interoperable, machine-readable provenance standards throughout defense digital infrastructure. Rather than centralizing information, SKI creates a federated verification architecture that enables organizations to establish trusted records of how data enters systems, how it is transformed, and how AI-generated outputs are produced.

The technical foundations already exist. Open standards such as the W3C PROV data model demonstrate that relationships among original data, computational processes, and generated outputs can be recorded in structured, interoperable formats. The challenge is no longer technical feasibility. It is institutional adoption.

Implementing this infrastructure would strengthen America's resilience against foreign manipulation. In an era of gray-zone competition, Beijing routinely employs commercial proxies, state-sponsored maritime militias, cyber actors, and information operations to obscure attribution. As deepfakes, AI-generated software, and autonomous systems become increasingly sophisticated, adversaries will seek not only to penetrate networks but also to corrupt the information flowing through them.

An adversary no longer needs to breach a secure network if it can subtly contaminate the data feeding it.

Without verifiable provenance, commanders cannot confidently determine whether an automated logistics request, engineering specification, or AI-generated threat assessment has been manipulated before reaching the decision-maker. Authenticating knowledge will become as fundamental to military operations as authenticating identities.

The race for AI superiority will not be won solely by the nation that develops the largest models or the fastest processors. It will favor the nation that builds the most secure, trusted, and legally resilient innovation ecosystem.

For the defense enterprise, the central challenge of AI governance is no longer controlling what machines are permitted to create. It is ensuring that what they create remains transparent enough to protect intellectual property, sustain defense collaboration, secure maritime supply chains, and preserve operational confidence.

Just as previous generations built strategic advantage on GPS, secure communications, and cyber resilience, the next generation will depend on trusted knowledge infrastructure. Provenance is becoming a strategic capability in its own right.

Building a Strategic Knowledge Infrastructure should become a national priority—not to constrain artificial intelligence, but to ensure that the fleet, weapons, and alliances America builds tomorrow rest on knowledge it can verify today.

Sue Ghosh Stricklett is an attorney specializing in technology transfer, export controls, and national security law. She is a founder of Digital Archives Pro, a company specializing in secure data infrastructure and verifiable knowledge lineage. Previously nominated by President Trump to serve as Assistant Administrator for the Asia Bureau at USAID, she has served as an Indo-Pacific strategic advisor, counseling senior policymakers on regional security, supply-chain resilience, and technology defense.

image: U.S. Navy Operations Specialist Seaman, Jonathan Felix, from Texas, stands watch on the bridgewing aboard Arleigh Burke-class guided-missile destroyer USS Mustin (DDG 89) while underway in the Indian Ocean, July 18, 2026. Mustin is forward-deployed and assigned to Destroyer Squadron (DESRON) 15, the Navy’s largest DESRON and U.S. 7th Fleet’s principal surface force. (U.S. Navy photo by Mass Communication Specialist 2nd Class Timothy Dimal)