Washington’s Hidden AI Loss: The Compliance Gap

Spain recently picked a Chinese vendor to run legally authorized wiretap infrastructure—inside the EU, inside NATO. The contract wasn’t huge money by national standards (about €12.3 million), but it exposed a bigger weakness: U.S. AI and security vendors are getting boxed out of allied procurements because they can’t prove compliance fast enough.

Most people think the “AI race” is about who has better models, more GPUs, or flashier demos. In government and national security, that’s only half true. The other half is paperwork—evidence, testing records, risk controls, audit trails, and conformity assessments that prove a system is lawful to deploy. If you can’t produce those artifacts on demand, you don’t just lose market share. You create interoperability gaps with allies that the U.S. then has to patch operationally.

This post is part of our AI in Government & Public Sector series, where we focus on what actually determines adoption: procurement rules, accountability, and real-world deployment constraints. The hard lesson from Europe is simple: AI governance is now a battlefield advantage.

The AI race most people miss: “proof” beats “performance”

The near-term contest in allied AI procurement is not model accuracy—it’s compliance readiness. If an EU agency classifies a system as high-risk, vendors must deliver detailed technical documentation to compete, not after the fact.

That changes how national security technology spreads across alliances. A border screening model, a critical infrastructure anomaly detector, or a surveillance analytics platform can be technically strong and still be non-viable for an EU buyer if it lacks the required documentation package.

Here’s the operational reality I’ve seen trip teams up: procurement officers rarely have the mandate (or appetite) to “take a chance” on a non-compliant system, even if the engineering team loves it. They buy what they can legally defend.

The “documentation gap” is now a security gap

A spring 2025 global survey found a credibility imbalance: across 25 countries, a median of 53% of adults trusted the EU to regulate AI, versus 37% for the U.S. That trust gap matters because it influences how regulators, procurement offices, and oversight bodies interpret risk.

A useful way to think about it:

• Innovation advantage helps you build capabilities.
• Compliance advantage helps you field capabilities—at scale, across borders, and under scrutiny.

If the U.S. loses the compliance contest, American systems don’t get adopted, don’t become defaults, and don’t set standards. That’s strategic loss, even if U.S. labs keep winning benchmarks.

Why U.S. AI policy doesn’t translate into allied procurement wins

America’s AI governance posture is strong in guidance and uneven in market access execution. The U.S. has credible risk management work—especially the widely respected NIST AI Risk Management Framework. The problem is that much of it is voluntary, while key allied markets operate on mandatory compliance.

In practice, U.S. firms show up with a “trust us” story and an internal governance deck. EU buyers increasingly need something different: a documented trail that maps requirements to controls, testing, monitoring, and accountability.

Voluntary frameworks vs. mandatory market access

The EU’s AI Act creates binding obligations for systems categorized as high-risk—often including border control, critical infrastructure, and many public safety applications. That category matters for defense-adjacent vendors because lots of “civilian” systems are dual-use in effect:

• Port and cargo screening
• Passenger risk scoring
• Critical infrastructure threat detection
• Identity verification and biometric matching
• Emergency response resource allocation

A U.S. vendor can have a superior algorithm and still lose because the procurement team can’t legally buy it without the right conformity evidence.

The U.S. is fast on restrictions, slower on alignment

Washington has proven it can move quickly when the goal is restricting technology flows—export rules, outbound investment controls, and chip diffusion limits. But allied competitiveness requires a different muscle: making U.S. systems easy to buy and integrate under allied legal regimes.

That’s the mismatch. U.S. policy often focuses on:

• funding R&D,
• protecting domestic innovation,
• restricting adversary access,
• coordinating statements with allies.

Those steps are useful. But they don’t automatically produce what procurement offices demand: repeatable compliance packages, test evidence, and certification pathways that can be attached to bids.

Homeland security interoperability: where the risk becomes real

Interoperability is the hidden cost center of the compliance gap. When allied agencies adopt different vendors and governance models, the burden shifts to operators who now need to connect systems with incompatible documentation, auditability, and update controls.

One hard number illustrates how quickly this problem scales: the U.S. Department of Homeland Security reported 158 AI use cases in its 2024 inventory, representing a 136% increase from the prior year. More AI systems means more integration points—with allies, with state and local partners, and with private critical infrastructure operators.

If those systems can’t align with EU “high-risk” documentation expectations, it creates three concrete risks:

1. Operational friction at borders and ports

   • If an allied port authority can’t legally integrate an American AI cargo screening module, they’ll buy an alternative that can be certified and audited.

2. Security blind spots in shared threat pictures

   • If data-sharing requires governance artifacts (risk controls, monitoring plans, change logs) and one side can’t produce them, information exchange slows or narrows.

1. Vendor lock-in over 15–20 year procurement cycles
   • Once a country commits to an infrastructure stack—surveillance, analytics, case management—it becomes a long-term dependency.

A line worth remembering: You can’t win a contract you’re not allowed to compete for.

People also ask: “Can’t allies just buy the best tech and document later?”

They usually can’t. Public sector buyers face oversight, courts, data protection authorities, and procurement rules that require upfront diligence. In high-risk AI contexts, retrofitting documentation after deployment can be legally and politically non-viable.

How competitors turn compliance into export power

China is treating compliance as a product feature, not an afterthought. When governance is baked into export strategy, vendors show up with procurement-ready artifacts: checklists, documentation templates, and “here’s our conformity story” packages that match local expectations.

That doesn’t mean the technology is always better. It means the vendor is easier to buy.

For U.S. national security stakeholders, this dynamic is uncomfortable but clarifying: the next decade’s influence battle is fought through standards, certification, and regulatory credibility. If allies normalize on non-U.S. stacks because those stacks are “paperwork complete,” the U.S. inherits a fragmented alliance tech environment.

Strategic lock-in looks boring—until it isn’t

Lock-in is rarely announced with fanfare. It shows up as:

• standardized interfaces built around one vendor’s audit model,
• training pipelines that assume one toolset,
• maintenance contracts that become de facto governance controls,
• data formats and retention rules optimized for one platform.

After a few years, switching costs aren’t just financial. They’re operational and legal.

A practical path: turn AI governance into a deliverable

The fix isn’t more white papers. It’s turning governance into procurement-grade deliverables that travel with the system. If you want allied adoption, compliance can’t be an internal policy memo. It needs to be a standardized package that can survive legal review in Brussels, Madrid, or Warsaw.

Below are actions that actually change outcomes—because they change what shows up in the bid.

1) Build “Regulatory Interoperability Plans” into defense procurement

For defense-adjacent systems expected to integrate with allies, require a Regulatory Interoperability Plan at evaluation time. That plan should answer, in plain language:

• Which AI functions are high-risk in the target jurisdiction?
• What documentation artifacts are delivered at contract award?
• How does the vendor handle updates, model drift, and change control?
• What audit logs exist, and who can access them?
• What’s the incident response path for safety, security, and misuse?

This is boring on purpose. It’s also the difference between a system that deploys and a system that stalls.

2) Stand up a DHS–European AI compliance working group (by mid-2026)

Homeland security is where the alliance friction is most immediate: border operations, cargo, travel security, and critical infrastructure resilience.

A joint working group—staffed by operators and compliance specialists—should produce shared templates for high-risk AI documentation and pilot mutual recognition pathways for specific system categories (for example, cargo screening models or critical infrastructure anomaly detection).

If that sounds bureaucratic, good. Bureaucracy is exactly what procurement runs on.

3) Create an “AI regulatory passport” for exports

U.S. vendors need a repeatable way to prove:

• conformity to U.S. trustworthy AI expectations (e.g., NIST-aligned controls), and
• compatibility with allied documentation requirements.

An AI regulatory passport doesn’t “bless” a model forever. It certifies that the vendor can produce required artifacts, maintain controls through updates, and support audits. Think of it as a procurement accelerator.

4) What vendors should do now (even without new policy)

If you sell into government, you don’t need to wait for Washington to fix this. Start packaging compliance like a product.

A strong baseline set of deliverables includes:

• a model and system card that matches public-sector procurement language
• data lineage and retention documentation
• threat modeling for model abuse (prompt injection, data poisoning, exfiltration)
• red-team test results and mitigation tracking
• drift monitoring plan with measurable thresholds
• human oversight and escalation procedures
• change management logs for model updates

If you can hand this to a procurement team on day one, you’ve already separated from most of the market.

Memorable rule: If your AI system can’t explain how it stays safe after the next update, it’s not procurement-ready.

What this means for AI in government & public sector (and why it drives leads)

This topic sits at the heart of digital government transformation: public sector AI doesn’t scale on innovation alone—it scales on trust, auditability, and interoperability. The U.S. can keep pushing R&D and still lose adoption across alliances if American systems can’t meet mandatory documentation requirements.

For defense and national security leaders, the priority is straightforward: treat compliance as a strategic capability. Fund it, standardize it, measure it, and demand it from suppliers.

If you’re building, buying, or governing AI for defense and homeland security, the practical next step is to map your systems to the documentation that allied partners will require—before the procurement starts. That’s how you stay in the competition.

The open question heading into 2026: Will Washington build an export-grade compliance pipeline, or will allies standardize on whoever can pass audits fastest?