How generative AI/agents could reduce the cost of classified networks by enabling intelligent declassification

The rising cost of classified communications

Governments across the world spend enormous amounts of money building, operating, and securing classified communications networks. These systems require specialised facilities, accredited hardware, advanced encryption, cleared personnel, and strict compliance processes.

The result is an infrastructure environment that costs billions annually to maintain, even before new systems are developed.

In many countries, classified networks exist because sensitive information must be transmitted securely between ministries, intelligence agencies, embassies, and military units. When information is labelled SECRET or above, it typically must travel across dedicated classified networks rather than commercial communications channels. These networks demand extensive physical protection, controlled access facilities, specialised encryption systems, and highly vetted personnel. Each requirement significantly increases cost.

However, a major structural issue contributes to this expense: a significant share of classified material does not actually need to remain fully classified for operational use. Many intelligence or operational messages contain both sensitive source information and actionable insights. The insight itself may be safe to share broadly if the sensitive details are removed. This creates an opportunity for generative AI (Gen AI) to play a transformative role.

By intelligently transforming highly classified reports into lower-classification or unclassified versions before transmission or storage, Gen AI and AI agents could dramatically reduce the need for expensive classified networks, facilities, and operational processes. This emerging approach has the potential to reshape how governments think about classified communications while maintaining security outcomes.

Why classified networks are so expensive

Classified communications environments are expensive because security requirements extend far beyond encryption alone. Entire ecosystems must be created to protect sensitive information.

Sensitive Compartmented Information Facilities (SCIFs), for example, require reinforced construction, surveillance detection protections, electromagnetic shielding, access control systems, and secure equipment. These facilities often cost significantly more than normal buildings and can take years to accredit. Updated standards requiring advanced RF shielding and TEMPEST protections are further increasing construction and retrofit costs.

Technology infrastructure is also specialised. Classified networks rely on accredited hardware, air-gapped systems, custom encryption devices, and highly controlled software environments. Commercial off-the-shelf technologies often cannot be used without costly certification and modification.

Personnel requirements further increase costs. Staff must undergo lengthy background investigations to obtain security clearances, and the limited pool of cleared specialists drives up labour rates. Ongoing security training, compliance auditing, and operational monitoring add additional recurring expenses.

Administrative processes add another financial burden. Large volumes of classified information must be securely stored, periodically reviewed, and eventually declassified through labour-intensive processes. Overclassification—where information is classified at higher levels than necessary—creates long-term handling costs that can exceed the cost of producing the information itself.

Taken together, these structural factors make classified communications one of the most expensive elements of national security operations.

The overclassification problem and its financial impact

A significant portion of classified information does not need to remain fully classified for operational purposes. Estimates from multiple oversight reviews suggest that a large percentage of classified documents could be safely released or downgraded without harming national security.

The financial impact of overclassification is substantial. Every document classified at a high level triggers long-term costs associated with secure storage, specialised transmission, controlled access, auditing, and eventual declassification review. Governments often spend far more maintaining existing classified information than releasing it.

In operational environments, overclassification also creates inefficiencies. Field personnel, diplomats, and partner agencies may need actionable intelligence but cannot easily access highly classified systems. As a result, critical information may not reach the people who need it quickly enough to act.

This gap between “classified detail” and “actionable insight” represents the opportunity space where generative AI can deliver meaningful value.

Generative AI and intelligent declassification

Generative AI systems are increasingly capable of analysing large volumes of structured and unstructured data, identifying sensitive elements, and rewriting content while preserving meaning. When applied within controlled security environments, these capabilities can enable intelligent declassification workflows.

Instead of transmitting full classified reports across high-security networks, agencies could use Gen AI tools to generate lower-classification versions that remove sensitive sources, methods, identifiers, or operational details while preserving the essential insight required by recipients.

For example, a highly classified intelligence report describing surveillance methods, identities, and technical collection techniques could be automatically converted into an operational advisory that communicates the risk, recommended actions, and confidence level without exposing sensitive sources. The actionable information could then be transmitted through lower-cost secure channels or even unclassified communications systems when appropriate.

This process does not necessarily eliminate the need for classified systems entirely. Highly sensitive source material would still require secure storage and transmission. However, reducing the volume of information that must travel across classified networks could significantly lower infrastructure and operational costs over time.

Reducing infrastructure costs through selective transmission

One of the largest cost drivers in classified environments is the requirement to maintain secure transmission capabilities across many locations worldwide. Embassies, forward operating bases, intelligence liaison offices, and government facilities must maintain specialised communications equipment, cleared personnel, and secure facilities to handle classified transmissions.

If only the most sensitive source information required transmission via top-tier classified networks, and operational summaries could travel through lower-classification systems, the number of facilities requiring full classified infrastructure could decrease. Smaller diplomatic posts, temporary field operations, and partner-nation environments might rely primarily on lower-cost secure communications systems supported by automated declassification tools.

Over time, this selective transmission approach could reduce the number of high-security facilities required globally, lowering construction, accreditation, staffing, and maintenance costs. Even incremental reductions in classified infrastructure can produce significant financial savings given the high cost per site.

Improving usability and operational effectiveness

Beyond cost savings, Gen AI-enabled declassification could improve the usability of intelligence reporting. Many intelligence customers struggle to use classified reports effectively because they are too technical, too detailed, or accessible only through specialised systems. When actionable insights are translated into operational language suitable for broader distribution, the likelihood that the information will be used increases significantly.

Generative AI can also support structured reporting protocols that allow agencies to signal the confidence level, urgency, and priority of intelligence without exposing sensitive details. This helps recipients understand how to act on the information quickly while protecting the underlying sources.

In crisis situations, where rapid communication is essential, the ability to generate safe-to-share advisories automatically could improve response times and operational coordination across agencies and partner organisations.

Cost savings across the classified information lifecycle

The financial benefits of intelligent declassification extend beyond transmission networks. Costs can be reduced across the entire classified information lifecycle.

Storage requirements decrease when fewer documents must be maintained at the highest classification levels. Personnel clearance requirements may decline if fewer roles require access to top-tier classified systems. Training and compliance costs may also fall as fewer staff need specialised classified handling certifications.

Administrative workloads associated with long-term declassification reviews could also decline. If reports are automatically produced in both classified and downgraded formats at the time of creation, future review processes become simpler, reducing long-term administrative costs.

Even cybersecurity spending can be optimised. While classified networks will always require strong protection, reducing the amount of data stored within the highest-risk environments lowers the potential impact of insider threats or breaches.

Strategic implications for national security architectures

Adopting Gen AI-assisted declassification does not mean weakening security standards. Instead, it represents a shift toward more targeted protection of truly sensitive information while enabling broader operational use of intelligence insights.

Future classified communications architectures may operate as layered systems. At the highest layer, highly sensitive source material remains protected within traditional classified networks. At intermediate layers, automatically sanitised operational intelligence is transmitted through lower-classification secure systems. At the lowest layer, publicly releasable insights can be distributed widely to partners and stakeholders.

This layered model allows governments to focus their most expensive security controls where they are most needed while maintaining information advantage across the broader operational environment.

Implementation considerations for governments

Successfully deploying Gen AI-enabled declassification capabilities requires careful governance, oversight, and technical design. AI systems must operate within secure environments, use accredited models and datasets, and include human review processes for sensitive decisions.

Agencies will also need clear policy frameworks defining what types of information can be automatically downgraded and under what conditions.

Pilot programs focused on high-volume reporting environments—such as operational intelligence summaries or diplomatic situation reports—may offer early opportunities to demonstrate value. Over time, lessons learned can inform broader adoption across defence, intelligence, and civilian agencies.

Investment in this capability should be viewed not only as an AI initiative but as a long-term infrastructure optimisation strategy capable of delivering recurring cost savings.

Balancing security and efficiency in the AI era

Classified communications systems are essential to national security, but they are also among the most expensive government infrastructure environments. Much of this cost is driven by the requirement to protect large volumes of information at the highest classification levels, even when only a portion of the information requires that level of protection.

Generative AI offers a practical pathway to reduce these costs by enabling intelligent declassification before transmission and storage. By automatically transforming highly classified reports into lower-classification operational products, governments can reduce reliance on expensive classified networks, optimise infrastructure investments, and improve the usability of intelligence reporting.

The key insight is not that classified systems should disappear, but that they should be used more selectively. Protect the sources, methods, and truly sensitive details at the highest levels, while allowing actionable insights to move more freely across operational environments. Over time, this approach can deliver substantial cost savings while strengthening mission effectiveness.

Governments that begin experimenting with AI-driven declassification workflows today will be better positioned to manage the rising costs of secure communications in the decade ahead. Strategic pilots, strong governance, and phased adoption can unlock both financial and operational benefits without compromising security.

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