National‑security concerns yield three contrasting AI regimes: the EU enforces rights‑forward, risk‑based rules; Algeria pursues capacity and independence; Pakistan prioritizes economic governance while leaving military AI largely opaque. These regulatory gaps threaten market fragmentation, complicate export controls and procurement transparency, and heighten dual‑use risks.

Main Finding

The paper compares how the EU, Algeria, and Pakistan regulate AI in national-security contexts and finds a clear divergence: the EU has a mature, risk‑based legal framework (the AI Act) combined with export‑control tools and institutional oversight; Algeria prioritizes technological sovereignty and capacity building via nascent national strategy documents but lacks binding operational regulation; Pakistan prioritizes economic adoption and digital governance with weak, under‑specified military AI oversight. Common problems across the three are dual‑use risks, limited transparency in defence uses, and gaps in multilateral norms for military AI.

Key Points

• Comparative orientations

  • EU: rights‑centric, risk‑based regulation (AI Act), export controls, parliamentary/judicial oversight; military carve‑out exists, creating a grey area for defence‑specific uses.
  • Algeria: strategy emphasizes technological sovereignty, local capacity building, and state‑directed modernization; operational regulatory bodies and transparency mechanisms are limited.
  • Pakistan: policy focuses on economic growth, skills and innovation hubs; defence governance, procurement transparency, and export controls for sensitive items are weak or underdeveloped.

• Shared governance challenges

  • Dual‑use nature of AI creates regulatory friction: civilian systems and research can be repurposed for security/military use.
  • Transparency vs secrecy trade‑offs: necessary secrecy in defence conflicts with democratic oversight and accountability.
  • International norm gap: no consolidated binding regime for military AI; risks of arms races and destabilizing deployments remain.

• Institutional capacity matters

  • High‑capacity jurisdictions (EU) can implement binding compliance regimes and export controls.
  • Middle‑income states (Algeria, Pakistan) emphasize capacity building and sovereignty but need long‑term investments in regulators, standards, and accredited testing labs.

• Export controls and supply‑chain resilience

  • Controls on processors, sensors, and software are strategic policy levers; EU’s dual‑use regime offers a model but requires cooperative implementation.

Data & Methods

• Methodology: qualitative comparative synthesis and document analysis.
• Sources: primary policy and legislative texts (EU AI Act; Algeria national AI strategy; Pakistan draft AI policy), government communiqués, think‑tank reports, peer‑reviewed literature.
• Analytical steps:
• Coding legal and policy documents by regulatory tools, scope (civilian/dual‑use/defence), oversight and disclosure mechanisms.
• Comparing institutional arrangements (civil‑military interface, procurement oversight, export controls).
• Identifying governance lapses and international security risk vectors.
• Limitations: interpretive, non‑quantitative approach; no empirical tracking of policy-to‑procurement outcomes or battlefield behavior; limited primary data on classified defence practices.

Implications for AI Economics

• Innovation incentives and regulatory trade‑offs

  • EU’s detailed regulation raises compliance costs but can create predictable markets and exportable standards (first‑mover normative advantage).
  • Algeria and Pakistan’s state‑led capacity building may subsidize domestic AI industries, altering competitive dynamics and potentially crowding out foreign suppliers or attracting targeted foreign investment.
  • Defence carve‑outs and fragmented rules increase uncertainty for firms developing dual‑use technologies, affecting investment timing and R&D allocation.

• Trade, export controls, and supply‑chains

  • Export controls on processors, specialised sensors, and critical software reshape global supply chains and can raise input costs for civilian AI producers in constrained markets.
  • Divergent national regimes risk trade frictions and market segmentation (compliance regimes, certification requirements).

• Industrial policy and procurement as demand shaping

  • Government procurement for defence/civil uses becomes an important demand‑pull instrument to develop local capabilities; lack of transparency reduces efficiency and crowding‑in effects for private R&D.
  • State procurement strategies in Algeria/Pakistan could be used strategically to build domestic ecosystems but require institutions to ensure effective technology transfer.

• Labour, human capital, and reallocation

  • Capacity‑building priorities imply increased public investment in STEM training and R&D infrastructure; long run effects include shifts in labor demand toward AI skills and higher returns to technical training.

• Risk externalities and public goods

  • Dual‑use and militarized AI generate negative externalities (escalation risks, destabilization) that private markets will under‑internalize—justifying public regulation, export controls and international coordination.
  • International coordination (standards, confidence‑building) reduces market uncertainty and lowers the social cost of proliferation risk.

• Policy design recommendations relevant for economics

  • Align domestic regulation with emerging international norms to reduce transaction costs for international trade and investment.
  • Enhance transparency in defence procurement (safeguarded disclosures, independent review) to improve market signals for firms and reduce informational asymmetries.
  • Invest in testing, standards bodies and accredited labs to lower compliance costs and enable local firms to compete in regulated markets.
  • Use export controls strategically but transparently to avoid unnecessary trade disruptions and to target real security risks.

Overall, the paper implies that differences in regulatory maturity and orientation will materially affect the economics of AI: market structure, trade flows, R&D investment decisions, and the returns to public industrial policy. For economists modeling AI adoption and policy, the dual‑use dimension, export‑control frictions, and procurement‑driven demand should be explicitly represented as determinants of private incentives and international diffusion.