Gray Zone AI: The Rules We Need Before It’s Too Late

A missile doesn’t have to launch for a country to be under attack. By late 2025, the most consequential uses of AI in national security are often non-kinetic: shaping what populations believe, pressuring what markets do, and nudging what leaders decide. This is the gray zone—the space between routine competition and open conflict—and it’s where AI’s speed and scale create real strategic risk.

Most public debate still treats military AI as a “battlefield problem”: autonomy in weapons, targeting, command and control. That matters, but it’s not the center of gravity. The center is pre-conflict competition—influence operations, cyber campaigns, sanctions enforcement, coercive signaling, and political warfare—where the lines are already blurry and the incentives to push them are constant.

Here’s the uncomfortable truth: AI’s biggest danger in the gray zone isn’t power. It’s portability. The same models that can help defend critical infrastructure can also manufacture believable lies at industrial scale. If the U.S. doesn’t draw boundaries early—operational, legal, and ethical—others will. And they won’t draw them in ways that protect democratic stability.

Snippet-worthy: The gray zone isn’t a moral vacuum. It’s where norms either harden into restraint—or decay into permission.

Why gray zone AI policy is now a defense priority

Answer first: Gray zone AI policy is urgent because AI compresses decision timelines, expands the reach of influence operations, and increases the odds of escalation without anyone intending it.

The AI in Defense & National Security conversation often starts with platforms: drones, sensors, kill chains. In the gray zone, the platform is the population, the market, or the diplomatic process. AI changes three fundamentals:

1. Scale: One operator can run thousands of synthetic personas across languages and regions.
2. Precision: Targeting can shift from demographics to individuals, exploiting specific fears, biases, or grievances.
3. Pace: AI-generated content and automated responses can outstrip the ability of governments and platforms to attribute, respond, or de-escalate.

If you’ve worked in cyber, this will feel familiar. Early cyber operations expanded faster than governance. The world is still paying for that “ship first, norm later” era with normalized intrusion, denial, and escalation. The gray zone AI problem is cyber’s cousin—with deeper reach into perception and legitimacy.

The hidden operational risk: accidental escalation

Answer first: AI increases escalation risk by making actions easier to launch, harder to interpret, and faster to misread.

Gray zone competition relies on ambiguity. That’s the point. But ambiguity plus automation is combustible. A few examples of how escalation can happen without anyone “choosing war”:

• An AI-enabled influence campaign is mistaken for election interference by a rival, triggering retaliation.
• Automated financial pressure (sanctions detection, enforcement, compliance flags) creates cascading market impacts, read as economic warfare.
• AI-enhanced cyber defenses deploy countermeasures that look like offensive preparation.

The operational question isn’t “Can we do it?” It’s “Can we control how it’s interpreted—and can we stop it quickly?”

A practical way to draw lines: keep AI in its lane

Answer first: The most workable governance approach is to set different moral and operational rules for different spheres—diplomatic, informational, military, and economic—so tools built for one sphere can’t be casually repurposed for another.

Political theorist Michael Walzer argued that societies stay just when distinct “spheres” of life keep their own rules. When one sphere invades another—money buying political power, for instance—things rot fast.

Applied to AI-enabled statecraft, the idea is simple: don’t let battlefield-grade capabilities migrate into civic life, markets, or diplomacy. Gray zone operations tempt that migration because they’re pre-conflict and plausibly deniable. That’s exactly why boundaries matter.

Here’s how I translate this into something policymakers, operators, and acquisition teams can actually use: define sphere-specific guardrails the same way we define rules of engagement—clear constraints, auditable compliance, and consequences for violations.

Diplomacy: persuasion isn’t manipulation

Answer first: Diplomatic AI is legitimate when it strengthens understanding and negotiation; it crosses the line when it targets psychological vulnerabilities or fabricates actors.

Permissible diplomatic uses look like:

• Translation, summarization, and negotiation support tools
• Scenario modeling for bargaining positions
• Structured analysis that reduces misperception

Prohibited or tightly constrained uses should include:

• Deepfake simulations of foreign leaders or negotiators
• Automated coercive diplomacy (mass personalized threats, blackmail-style messaging)
• Psychological targeting of individual diplomats using private data

A clean test: Is AI helping you make a better argument—or helping you remove the other side’s agency? If it’s the second, you’re no longer doing diplomacy.

Information and intelligence: defend truth, don’t industrialize deception

Answer first: AI in the information sphere should be built to detect interference and clarify reality, not to automate covert influence or distort democratic processes.

This is the sphere most vulnerable to “portability.” The same generative tools that support intelligence analysis can also mass-produce disinformation. And once large-scale deception becomes routine, every crisis becomes harder to resolve because no one trusts what they see.

Permissible uses:

• Detecting coordinated inauthentic behavior
• Prioritizing cyber and foreign influence alerts
• Accelerating triage in intelligence workflows (with human accountability)

Prohibited uses (the U.S. should draw a bright line here):

• Large-scale deepfake propaganda campaigns
• Synthetic persona armies used to manipulate foreign or domestic audiences
• AI-enabled interference in democratic processes

This isn’t “being nice.” It’s strategic self-interest. Democracies run on shared reality. If you help destroy shared reality abroad, you import the same instability home.

Military AI: necessity and proportionality still apply

Answer first: Military AI is justified when it protects forces and reduces harm under clear rules; it becomes illegitimate when it’s repurposed for domestic control or indiscriminate expansion.

Within armed conflict, necessity and proportionality provide a framework people understand. The gray zone risk is spillover: tools built for contested battle networks get turned inward—surveillance, predictive control, social monitoring—because the technology works.

Permissible uses (with meaningful human accountability):

• Force protection and early warning
• Targeting support that reduces collateral damage
• Decision support for battle management under defined ROE

Red-line uses:

• Domestic population control using military AI systems
• Broadening a conflict’s scope through automated “find and fix” logic

If you’re building for defense programs, this is a design requirement, not a philosophy seminar: build technical constraints that prevent re-tasking without authorization.

Economic statecraft: enforce rules, don’t rig markets

Answer first: Economic AI is legitimate when it enforces transparent rules like sanctions and export controls; it becomes coercive when it manipulates markets or pressures firms through opaque algorithms.

AI can help identify illicit financial networks, flag evasion patterns, and support compliance. That’s valuable, especially as sanctions regimes grow more complex.

Where it gets dangerous:

• Algorithmic pressure campaigns that quietly starve sectors of capital
• Coercion that forces foreign firms into policy compliance without due process
• Market manipulation tactics that create “mystery volatility” rivals can’t attribute

The stability test here is straightforward: Would you accept the same tactic used against U.S. markets as legitimate competition? If not, it probably belongs on the prohibited list.

A three-tier gray zone AI framework: prohibited, restricted, permissive

Answer first: A usable policy framework separates AI capabilities into (1) prohibited uses that damage legitimacy, (2) restricted uses that require oversight and auditability, and (3) permissive uses that strengthen resilience and deterrence.

This is the part many organizations skip. They write principles, then never translate them into procurement requirements, operational approvals, and oversight triggers. A three-tier framework forces decisions.

Prohibited: actions that corrode legitimacy and invite blowback

These are uses that may offer short-term advantage but create long-term strategic loss.

• AI-amplified deepfake propaganda at scale
• Synthetic personas used for mass political manipulation
• AI-enabled interference in elections or democratic processes
• Persistent surveillance of civilians outside conflict zones

If the U.S. normalizes these tools, it hands every competitor an excuse to do the same—and makes de-escalation harder because retaliation becomes politically irresistible.

Restricted: dual-use capabilities that need tight controls

Restricted doesn’t mean “never.” It means audited, limited, and accountable.

• Predictive modeling of adversary decision-making
• Automated detection and attribution support for disinformation
• AI-enabled sanctions enforcement and financial network detection
• Certain cyber defense automations that could be misread as offensive

What “restricted” should require in practice:

1. Named human owner (one accountable leader, not a committee)
2. Audit logs (inputs, outputs, prompt history where relevant)
3. Scope limits (geography, time, targets, and data types)
4. Reciprocity review (what happens if used against us?)
5. Kill switch and rollback (fast shutdown, containment plan)

Permissive: defensive uses that strengthen resilience

Permissive uses should be encouraged because they reduce surprise and raise the cost of aggression without undermining norms.

• Early threat warning and anomaly detection
• Critical infrastructure defense (cyber and physical)
• Identifying foreign interference and coordinated inauthentic behavior
• Defensive counter-disinformation tooling focused on detection and disclosure

This is gray zone deterrence done right: fortify, attribute, expose—don’t fabricate.

Turning principles into execution: what leaders should do in 90 days

Answer first: The fastest path to responsible gray zone AI is to codify boundaries, operationalize oversight, and force auditability into acquisition and deployment.

I’ve found that governance fails when it’s treated as a policy memo instead of a system. If you want boundaries to hold under crisis pressure, they must show up in budgets, authorities, and tooling.

Here’s a practical 90-day starter plan for defense leaders, national security policymakers, and program managers:

1) Publish a “gray zone AI” directive with bright lines

Write down what’s prohibited, restricted, and permissive—using plain language. Then attach approval authorities.

• Prohibited: no waivers except at the highest level, with written justification
• Restricted: requires legal review, ethics review, and an operational risk assessment
• Permissive: fast-track procurement and deployment

2) Treat auditability as a mission requirement

If a system influences diplomatic messaging, information ops, sanctions enforcement, or cyber response, it should generate records that answer:

• What data did it use?
• Who authorized it?
• What did it produce?
• Who saw it and acted on it?

No audit trail means no accountability. No accountability means no legitimacy.

3) Build “portability controls” into the tech stack

Portability is the problem, so address it technically:

• Separate models, weights, or toolchains by mission category
• Require re-authorization for cross-domain reuse
• Red-team for repurposing risk (how could this be turned into manipulation?)

4) Run gray zone exercises, not just war games

Most exercises simulate kinetic escalation. Run scenarios that simulate:

• AI-driven rumor cascades during a crisis
• Deepfake “leader statements” released at key diplomatic moments
• Market shocks triggered by automated enforcement actions

Measure time-to-attribution, time-to-public-communication, and time-to-de-escalation. Those are the real performance metrics in the gray zone.

What this means for the AI in Defense & National Security series

Answer first: Gray zone AI governance is the connective tissue between intelligence, cyber defense, mission planning, and deterrence—because it determines how AI shapes the environment before conflict.

If you’re tracking this series for practical insight, here’s the thread: AI isn’t just a tool inside the Pentagon. It’s a tool that acts on societies. That’s why governance has to cover non-kinetic warfare, not only weapons.

The U.S. still has a window to define credible restraint—rules that competitors may not share, but must at least plan around. That’s strategic advantage. The alternative is a world where everyone runs automated manipulation campaigns, nobody trusts crisis communications, and escalation becomes the default.

The next step is blunt: write the rules, fund the oversight, and engineer the constraints. If your organization works in defense AI—models, data pipelines, cyber tooling, ISR analytics—this is also a product and compliance question. Your customers will need systems that can prove they stayed inside the lines.

Where would you draw the first bright line: deepfakes, synthetic personas, or AI-driven economic coercion?