Europe’s challenge is not inventing AI—it is governing its transition from civilian promise to military reality without losing trust, openness, or sovereignty. Handled well, the EU can build...

AI, Dual-Use Technology, and Europe’s Strategic Crossroads

An essay on innovation, security, and unintended consequences

by ChatGPT-5.2

1. What this report is about — in simple terms

The report The role of AI in the EU’s dual-use technology field explains how artificial intelligence (AI) is becoming a core enabling technology for tools that can be used both for civilian purposes and for military or security purposes. These are known as dual-use technologies.

In the past, dual-use technologies were things like GPS, radar, or jet engines—first developed for defence, later adapted for civilian life. Today, the direction has reversed: most cutting-edge innovation now happens in the civilian tech sector, and defence organisations increasingly adapt those civilian tools for military use. AI is the clearest example of this shift.

The report’s central claim is simple but far-reaching:

AI supports:

• Autonomous drones and robotics

• Cybersecurity and network resilience

• Surveillance and sensing

• Logistics and decision-support systems

• Simulation, training, and predictive maintenance

The European Union believes that how well it integrates AI across civilian and defence ecosystems will determine its future competitiveness, security, and strategic autonomy.

2. Europe’s position: strong foundations, weak connections

The report describes Europe as being well-resourced but structurally fragmented.

On the positive side:

• The EU funds large AI programmes through Horizon Europe, Digital Europe, and EuroHPC

• Defence innovation is supported via the European Defence Fund (EDF), EUDIS, and NATO initiatives like DIANA

• Venture capital investment in European defence-AI startups has grown rapidly since 2022

• Europe now leads globally in the number of dual-use AI investment deals

  AI-enabled Dual-Use Tech and th…

However, the report repeatedly stresses a core weakness:

This leads to:

• Promising AI tools getting stuck at prototype stage

• Startups unable to access defence-grade testing environments

• Long delays between research results and real-world deployment

• A “valley of death” where funding dries up just as technologies need to scale

3. The most surprising statements and findings

1. AI is treated as a capability, not a product
Rather than regulating or funding “AI systems,” the report focuses on capabilities such as autonomy, sensing, or decision-support. This reframing is powerful—and unusual—because it acknowledges that the same model, data pipeline, or algorithm can slide between civilian and military use with minimal change.

2. Europe leads in deal count—but not in speed or scale
While Europe has many dual-use AI startups, the report quietly concedes that the US still outpaces the EU in speed of deployment and capital depth, and China outpaces both in state-directed coordination.

3. AI export controls are already implicit—even if policymakers pretend otherwise
Although AI is not listed explicitly in EU dual-use export controls, the report acknowledges that model weights, source code, technical documentation, and even integration know-how may already constitute controlled exports. This has major implications for startups and universities that may not realise they are operating in a regulated space.

4. The most controversial elements

1. The normalisation of defence as a growth sector
The report openly frames defence and security as long-term economic stabilisers for Europe’s tech ecosystem. This marks a significant cultural shift for the EU, which historically separated civilian innovation from military objectives.

2. Civilian AI safety rules do not apply to military AI
Under the EU AI Act, systems used “exclusively for military or national security purposes” are excluded. The report presents this as pragmatic—but it raises uncomfortable questions about ethics, accountability, and democratic oversightwhen civilian-developed AI migrates into defence contexts.

3. Research security versus academic openness
The push for “safe research” and research-security frameworks is presented as benign and necessary. Yet the implications are profound: universities are increasingly asked to perform geopolitical risk assessments, potentially chilling international collaboration in sensitive AI fields.

5. The most valuable insights

1. Europe’s strength lies in trust and interoperability
Unlike the US (market-led) or China (state-directed), Europe’s model emphasises:

• Common standards

• Cross-border collaboration

• Interoperability between allies

• Ethics and accountability by design

This may slow deployment—but it produces systems that are deployable across 27 countries and NATO allies, which is strategically valuable.

2. Startups are now strategic infrastructure
The report clearly positions AI startups and scale-ups as critical security assets, not just commercial actors. This reframes industrial policy, procurement, and even immigration policy around talent attraction.

3. The biggest bottleneck is not money—it’s coordination
Funding exists. Testbeds exist. Talent exists. What is missing is a repeatable, predictable path from civil AI research to defence adoption.

6. Undesirable consequences if current trends continue

If left unaddressed, the report implies several risks:

• AI startups relocate to the US for faster defence contracts

• European IP is commercialised abroad, then re-imported at higher cost

• Civilian AI safety norms erode through defence carve-outs

• Democratic oversight weakens as military AI expands outside civilian law

• Universities face increasing pressure to act as security gatekeepers

7. Recommendations to address these risks

1. Create a clear, operational definition of “dual-use AI”
Not just for export control—but for funding, procurement, and compliance—so startups and researchers know where they stand.

2. Build mandatory civil-to-defence transition pathways
Ensure that EU-funded civilian AI projects with dual-use potential automatically gain access to:

• Defence-grade test environments

• Security review support

• Procurement pilots

3. Apply baseline AI safety principles even in defence contexts
Military exemption should not mean ethical exemption. Core principles—human oversight, robustness, auditability—should carry over.

4. Use public procurement as a first-customer tool
Expand Pre-Commercial Procurement (PCP) and Public Procurement of Innovative Solutions (PPI) so European buyers help startups scale at home.

5. Protect academic openness while enforcing proportionate research security
Avoid blanket restrictions. Focus on risk-based, transparent safeguards that preserve international scientific collaboration.

6. Treat AI infrastructure as strategic public goods
Secure compute, data spaces, and testing facilities should be accessible to European innovators—otherwise dependency on non-EU platforms will deepen.

Conclusion

This report is ultimately about power, not just technology.

AI-enabled dual-use technologies sit at the intersection of innovation, security, economics, and democratic governance. Europe’s challenge is not inventing AI—it is governing its transition from civilian promise to military reality without losing trust, openness, or sovereignty.

Handled well, the EU can build a uniquely European model of AI power: competitive, ethical, interoperable, and resilient. Handled poorly, it risks becoming a slow-moving incubator for technologies scaled elsewhere—on other countries’ terms.