AI Autonomy Standards the Pentagon Can’t Delay

A swarm of drones doesn’t fail because it “isn’t autonomous enough.” It fails because the pieces can’t coordinate when it counts.

That’s the uncomfortable truth behind the U.S. military’s current autonomy moment: the Department of Defense is buying (and building) more autonomous and AI-enabled systems every year, but it still lacks a shared, enforceable way to describe what autonomy is, what it’s allowed to do, and how it should communicate across platforms and services. When a crisis hits—especially in a contested environment where comms are degraded—ambiguity becomes operational risk.

This post is part of our AI in Defense & National Security series, and it focuses on a foundational requirement that too many autonomy conversations skip: standards. Not “standards” as paperwork, but standards as the difference between coordinated effects and disconnected gadgets.

The real problem isn’t autonomy—it’s ambiguity

If “autonomous” means five different things to five different program offices, the joint force can’t plan, test, or fight coherently. The market will happily sell “autonomy” as a label; warfighters have to live with it as a capability.

The autonomy hype cycle has made this worse. Vendors pitch everything from advanced autopilot to mission-level independence under the same word. Meanwhile, different services pursue different architectures, interfaces, and doctrine for air, maritime, and ground systems—often rational in isolation, but chaotic when stitched together under joint time pressure.

Here’s the practical consequence: the Pentagon can’t compare offerings cleanly. If one program’s “autonomy” is route planning and another’s is target tracking with onboard sensor fusion, acquisition teams aren’t evaluating like-for-like. Worse, training and tactics development becomes fragmented. Operators learn a specific system’s quirks rather than gaining transferable understanding of autonomy behaviors across the force.

A military without a shared autonomy language is building tomorrow’s force the way early PCs were built: custom cables, custom drivers, and constant integration pain.

“Fog of marketing” becomes fog of war

Marketing language is optimized to win contracts, not to reduce battlefield uncertainty. When autonomy is poorly defined, the organization with the clearest incentives—industry—fills the vocabulary vacuum.

That is backwards for national security. The government should define the operational outcomes, the minimum interfaces, and the trust requirements. Otherwise, DoD ends up with a portfolio that looks diverse on slides but behaves like a collection of isolated prototypes when the shooting starts.

Autonomy in combat: what recent operations actually show

Modern autonomy is layered and incremental, not a sci-fi leap. One of the most instructive recent examples is Ukraine’s widely discussed drone operations that used coordinated behaviors: humans set objectives and launched systems, while autonomy handled key functions like navigation, timing, and deconfliction.

The lesson isn’t “fully autonomous warfare is here.” The lesson is simpler: small doses of well-integrated autonomy multiply effect—especially when systems operate in numbers.

Autonomy that matters most is “coordination autonomy”

In contested environments, the hardest part isn’t making one vehicle fly itself. It’s making many vehicles cooperate under:

• intermittent communications
• GPS degradation or denial
• electronic warfare
• dynamic, moving targets
• shifting commander’s intent

This is where standards become decisive. Coordination requires shared assumptions about messages, tasking, status reporting, timing, and handoffs. If every platform speaks a different dialect, the force burns time translating instead of acting.

Why joint interoperability breaks without a standard layer

Interoperability is the enabling condition for military autonomy at scale. Without it, autonomy stays boutique—useful in single-service lanes, but brittle in joint operations.

A Taiwan Strait contingency is the obvious stress test. In a real crisis, the Air Force, Navy, and Marine Corps will need to share tasking, sensor data, and effects across domains. Yet autonomy programs often grow within service-specific ecosystems, each with its own control interfaces and reference architectures.

If those systems can’t exchange mission tasks and interpret each other’s status in real time, the result is the 21st-century equivalent of incompatible radios. It’s not just inconvenient—it’s dangerous.

A standard isn’t “one system to rule them all”

A common misconception is that autonomy standards mean picking a single vendor stack or freezing innovation. The opposite is true.

The right standard defines the interface, not the implementation. It’s how the internet scaled: common transport protocols, endless room for innovation above and below.

For defense autonomy, the goal should be similar: standardize one or two critical layers so that:

• tasking is portable across platforms
• reporting is understandable across services
• autonomy behaviors can be tested against common expectations
• vendors compete on performance and reliability, not proprietary lock-in

What to standardize first: the “minimum viable autonomy interface”

The fastest path is to standardize autonomy messaging and tasking before trying to standardize autonomy algorithms. Algorithms will evolve. Interfaces need to endure.

If you’re building an autonomy standard that can survive real acquisition cycles and coalition operations, start with the pieces that program offices repeatedly rebuild from scratch.

Layer 1: Mission tasking primitives

Define a small, joint set of task types that can apply across domains. Not thousands—start with a tight core.

Examples of cross-domain tasking primitives:

• patrol area with route constraints and time windows
• track entity with sensor preferences and confidence thresholds
• screen corridor with spacing and handoff rules
• relay/bridge comms with prioritization
• hold at waypoint with triggers for re-tasking

The key is that a task should describe the outcome and constraints, not prescribe the internal method. That preserves vendor innovation while enabling joint orchestration.

Layer 2: Status, health, and confidence reporting

Operators and commanders need consistent answers to consistent questions:

• Where are you (and how sure are you)?
• What are you doing now (and why)?
• What can you do next (and what’s limiting you)?
• How degraded are you (EW, sensors, fuel/energy, comms)?

A shared reporting schema enables joint monitoring tools and reduces training friction. It also supports mission planning AI: planners can reason over comparable telemetry instead of bespoke formats.

Layer 3: Safety constraints and human-control handoffs

In defense autonomy, “trust” isn’t a vibe. It’s a set of engineered guarantees.

Standardize how systems express and obey:

• keep-out zones and rules of engagement constraints
• abort criteria and safe modes
• handoff procedures (machine-to-human and human-to-machine)
• audit logs for post-mission accountability

If every platform implements these differently, operators will default to the least risky option: not using autonomy when it matters.

Operator trust is built early—or it isn’t built at all

Autonomy that operators don’t trust becomes shelfware. And when autonomy is introduced late—after requirements are locked and interfaces are fixed—trust gaps show up during exercises or deployments, when it’s expensive and politically painful to fix.

Calibrated trust comes from three things: education, repetition, and transparency.

Education: teach “autonomy behaviors,” not vendor features

I’ve found that autonomy training often fails because it’s delivered like software training: button-by-button, screen-by-screen. That doesn’t scale.

What scales is teaching operators to reason about:

• sensing limits and false positives/negatives
• confidence scores and what they actually mean
• failure modes (GPS denial, spoofing, comms loss)
• autonomy boundaries (what the system will never do)

This is another reason definitions matter. A shared taxonomy lets training units build a common curriculum across platforms.

Diagnostics: give operators the tools to interrogate autonomy

If a system can’t answer “why did you do that?” in a form an operator can use, trust will be fragile.

You don’t need perfect explainability. You need operationally relevant introspection, such as:

• the top 3 factors that drove a maneuver decision
• which sensor inputs were trusted vs rejected
• whether a behavior was policy-constrained or model-driven

When operators can diagnose behavior, they stop treating autonomy like magic—and start treating it like a teammate with known strengths and weaknesses.

Acquisition: standards shape the market (whether DoD admits it or not)

Every interface DoD standardizes becomes a magnet for industry investment. That’s not theory; it’s how technology ecosystems form.

A useful analogy is USB: once device makers could count on a shared connection and data/power expectations, the peripheral market exploded. Users benefited because everything got easier to integrate.

Defense autonomy is stuck in the pre-USB era. Custom integrations dominate timelines. Integration teams become the hidden tax on every “rapid” fielding effort.

What “good” looks like for DoD autonomy procurement

If you’re writing requirements or evaluating proposals, standards should show up as non-negotiables:

1. Conformance testing against the autonomy messaging/tasking layer
2. Interoperability demonstrations in joint exercises (not just lab settings)
3. Data rights and interface openness sufficient to avoid vendor lock-in
4. Upgrade resilience so autonomy improvements don’t break joint coordination

This isn’t anti-industry. It’s pro-market. Clear standards reduce uncertainty and expand the pool of competitors who can plug in.

Practical next steps: a 90-day standardization sprint

DoD doesn’t need a five-year committee process to start. It needs a sprint with teeth. Here’s a realistic sequence that can begin in a single quarter.

Step 1: Publish a joint autonomy taxonomy (Version 1)

Deliver a short, operationally grounded vocabulary that distinguishes:

• operator assistance vs mission autonomy
• navigation autonomy vs coordination autonomy
• target tracking vs target engagement
• degraded-mode behaviors (lost comms, lost GPS, sensor failure)

Make it mandatory in program documentation within the next budget cycle.

Step 2: Select one standard layer and enforce it

Pick autonomy tasking/messaging as the first “must comply” layer. Then:

• define the minimal tasking primitives
• define required status/health messages
• release a reference implementation and test harness

Step 3: Prove it in an exercise, not a slide deck

Run a joint demo where at least three systems from different vendors exchange tasks and status through the standard layer. Score it publicly inside the department: reliability, latency tolerance, degraded-mode performance, and operator workload.

Step 4: Bake it into acquisition language

If compliance is optional, it won’t happen. Make standard conformance a scored requirement, and treat non-conformance like you’d treat a radio that can’t connect to the net.

What this means for AI in defense and mission planning

AI in defense and national security only scales when the underlying autonomy stack is legible. Mission planning AI is increasingly expected to allocate assets, propose courses of action, and manage dynamic retasking. Those capabilities depend on consistent tasking interfaces and consistent reporting.

If every autonomous platform reports state differently, planning tools become bespoke. If every service defines autonomy differently, joint planning becomes guesswork. Standards are the substrate that turns “promising demos” into operational capability.

The Pentagon doesn’t need to predict the perfect future of autonomy. It needs to define the common language that lets future autonomy plug into the force without a custom integration effort every time.

The question worth sitting with is straightforward: When the next crisis hits, will U.S. autonomous systems coordinate like a team—or like a pile of gadgets with great branding?