Europe’s Strategic Autonomy: AI as the Deciding Factor

Europe’s problem isn’t that it lacks power. It’s that it can’t reliably use it.

In a multipolar world—where the U.S., China, and Russia set the tempo—Europe still carries enormous economic weight, sophisticated technology, and deep alliances. Yet when decisions need to happen fast (missile defense, cyber response, sanctions enforcement, intelligence sharing, battlefield resupply), the continent too often defaults to dependence, delay, or disagreement.

Here’s my take: Europe’s debate about “strategic autonomy” won’t be settled by speeches or new acronyms. It’ll be settled by operational capability—and increasingly, that capability is shaped by AI in defense and national security. Not because AI is magic, but because modern conflict is a race to understand, decide, and act faster than the other side.

Multipolar reality: Europe is squeezed on three fronts

Europe is being compressed between three competing systems of power. That squeeze isn’t theoretical; it shows up in procurement lead times, supply chain risk, cyber incidents, and alliance politics.

The direct point: In a multipolar order, Europe’s safety and prosperity depend on how well it can manage three simultaneous pressures.

The U.S.: indispensable, but no longer endlessly patient

Europe still relies heavily on U.S. enabling capabilities—intelligence, strategic lift, command-and-control, missile defense, and key munitions. Even when European forces are competent, the “back office” of modern warfare often runs on U.S. systems and U.S. inventory.

But Washington’s strategic attention is stretched across multiple theaters, with rising political friction over burden sharing and industrial capacity. That creates a risk Europe can’t ignore: a capability gap that can’t be closed on short notice if U.S. priorities shift.

AI fits here in a very practical way. If you assume the U.S. can’t always be the default provider of awareness and coordination, Europe needs its own decision advantage—built from shared data, shared models, and shared command workflows.

China: economic gravity plus technology competition

Europe’s industries need Chinese inputs and markets, while also confronting a reality that China is competing for influence through technology standards, investment, and information operations.

The immediate defense implication is less about a single battlefield and more about industrial resilience:

• Critical minerals and components
• Semiconductor supply chains
• Battery and energy-tech dependencies
• Dual-use technologies that blur civilian and military boundaries

This is where AI becomes a national security tool beyond the battlefield: forecasting supply chain disruptions, detecting IP theft patterns, and identifying strategic dependencies before they become crises.

Russia: a structural security threat, not a “temporary crisis”

Russia’s war in Ukraine forced Europe to face a hard truth: high-intensity conflict in and around Europe is not a historical anomaly. It’s a planning baseline.

That pushes Europe into an uncomfortable, expensive lane:

• sustained defense spending
• scaled munitions production
• integrated air and missile defense
• counter-sabotage and counterintelligence

AI doesn’t replace mass, ammo, or mobilization. What it does is compress the time from sensor-to-shooter, improve targeting quality, and strengthen force protection through faster anomaly detection (cyber, ISR, infrastructure).

Europe’s core weakness: “power without agency” is a losing model

Europe’s strategic challenge is not just military spending. It’s the ability to coordinate, decide, and execute.

Answer first: Europe has plenty of assets, but it lacks the operating system to turn them into coherent power.

The RSS article calls out four structural issues—fragmented decision-making, military insufficiency, economic vulnerability, and demographic decline. I’d translate that into a single operational sentence:

If you can’t share data, align decisions, and scale production quickly, you don’t have strategic autonomy—you have strategic anxiety.

Fragmented decision-making is now a battlefield vulnerability

When foreign policy requires unanimity and defense procurement is nationally siloed, adversaries gain a simple advantage: they can act at machine speed while Europe debates at committee speed.

AI can’t fix politics, but it can reduce the friction of coordination by enabling:

• shared situational awareness across agencies and borders
• consistent risk scoring for threats (cyber, disinformation, sabotage)
• common operating pictures for air/maritime security

That matters because the first days of a crisis are rarely about perfect strategy. They’re about preventing surprise and avoiding paralysis.

Military insufficiency isn’t just spending—it’s integration

Europe’s defense industrial base remains fragmented across many national systems and standards. The cost isn’t only financial; it’s operational.

If allies can’t exchange data easily, if logistics software can’t talk to each other, and if targeting workflows aren’t compatible, you don’t get “combined arms.” You get parallel national forces.

AI-enabled interoperability—shared data schemas, federated model approaches, compatible mission planning tools—can reduce that fragmentation without requiring every country to buy identical platforms.

Where AI actually strengthens European security (and where it doesn’t)

AI in defense tends to attract big promises and vague claims. Most organizations get this wrong by treating AI as a gadget instead of infrastructure.

Answer first: Europe should focus AI investment on three mission outcomes—decision advantage, resilience, and scalable deterrence.

1) Intelligence fusion and warning that works across borders

The first strategic payoff for Europe is speed and coherence in intelligence.

AI can help fuse:

• satellite imagery and radar
• maritime AIS anomalies
• cyber telemetry and malware indicators
• open-source reporting and disinformation narratives

The goal is not “AI does intel.” The goal is AI-assisted triage so analysts spend time on what matters.

A practical model for Europe is a federated approach: data stays national when it must, but insights can be shared as alerts, patterns, and confidence-scored assessments.

2) Cyber defense as continuous operations, not incident response

In a multipolar world, Europe will face persistent cyber pressure—against defense primes, ports, energy infrastructure, logistics networks, and elections.

AI helps when it’s used for:

• behavioral anomaly detection (not just signature matching)
• automated containment playbooks for known attack paths
• rapid correlation across endpoints, identity systems, and networks

It doesn’t help if you treat it as a dashboard. The difference is whether AI is integrated into SOC workflows, with authority boundaries, audit trails, and human override.

3) Autonomous and semi-autonomous systems for mass and persistence

Europe is already under pressure to expand surveillance and deterrence capacity without unlimited manpower. Autonomous systems—air, sea, and ground—address that by providing persistence.

The best use cases are boring in a good way:

• border and maritime monitoring
• depot and base perimeter defense
• route reconnaissance for logistics
• counter-UAS detection and tracking

This is where Europe can build strategic autonomy faster than with exquisite manned platforms—if procurement and safety certification keep pace.

Where AI won’t save Europe

A few realities are non-negotiable:

• AI can’t substitute for ammunition stockpiles.
• AI can’t manufacture air defenses faster unless industrial capacity exists.
• AI can’t overcome political vetoes in the middle of a crisis.

AI is an accelerator. If the underlying system is fragmented, AI accelerates fragmentation.

A European AI defense playbook that’s realistic in 12–24 months

The gap between “strategy” and “capability” is where most initiatives die. Here’s what I’ve found works: choose a few outcomes, standardize the boring parts, and ship improvements in cycles.

Answer first: Europe can make real progress quickly by standardizing data, securing model lifecycles, and fielding AI where it reduces operational friction today.

1) Standardize coalition data pathways (before the next crisis)

Europe doesn’t need one giant database. It needs shared data contracts and cross-domain sharing patterns.

Priorities:

• common metadata standards for ISR and cyber indicators
• identity, access, and auditing across organizations
• “releaseability by design” tagging for intelligence products

2) Build defense-ready AI governance (so operators trust outputs)

Defense AI must be auditable, testable, and resistant to manipulation. That means:

• model evaluation tied to mission tasks (not generic accuracy)
• red-teaming for adversarial inputs and data poisoning
• clear human-in-the-loop decision boundaries
• retraining rules and provenance tracking

Trust isn’t a slogan. It’s engineering plus policy.

3) Field AI in three places that pay back immediately

If you’re choosing where to start, pick areas with high data availability and clear operational metrics:

1. ISR triage for border/maritime and critical infrastructure monitoring
2. Cyber defense automation for major government and defense supplier networks
3. Logistics forecasting (spares, fuel, maintenance) to reduce readiness dips

Logistics is underrated here. Readiness collapses faster from supply bottlenecks than from lack of strategy.

4) Treat procurement as a software problem, not only a platform problem

Europe’s traditional procurement cadence is mismatched to AI iteration. A workable model is:

• shorter contracting cycles
• modular accreditation for updates
• continuous testing environments
• clear IP and data rights so governments aren’t locked out

Strategic autonomy includes autonomy from vendor lock-in.

People also ask: what does “strategic autonomy” mean in AI terms?

Strategic autonomy in AI terms means you can sense, decide, and act without relying on another power’s data, compute, or permission.

That doesn’t require isolation. It requires control points:

• sovereign access to training and operational data
• secure compute environments for defense workloads
• an industrial base that can sustain models and systems over time
• coalition interoperability that doesn’t collapse under classification barriers

If those control points sit outside Europe, autonomy is a talking point—not a capability.

Europe’s choice: comfort, dependence, or a real operating advantage

The RSS piece frames three futures: real strategic autonomy, renewed Atlantic dependence, or fragmentation and decline. I’d add a blunt observation: Europe doesn’t get to choose the timeline. Adversaries choose it for you.

Strategic autonomy isn’t anti-NATO. It’s pro-credibility. A Europe that can generate its own intelligence picture, defend its networks, and coordinate multi-domain operations is a stronger ally—and a harder target.

If you’re building or buying AI for defense and national security, the question to ask in 2026 planning is simple: are we creating a capability Europe can run under stress, with partial allies, contested networks, and political disagreement? Or are we buying another demo?

Europe can survive the new multipolar world. But it won’t be because the world got nicer. It’ll be because Europe decided that speed of decision, resilience of systems, and scale of deterrence are worth funding—and worth integrating.