Volume 6: AI Weaponry

War has always been humanity's cruelest laboratory for innovation. Gunpowder rewrote the rules of siege warfare. Railroads made mass mobilization possible. Aircraft turned battlefields three-dimensional. Nuclear weapons made total war potentially suicidal. Each wave of military technology has redefined what armies can do, how they organize, and which nations can project power.

Artificial intelligence represents the latest turn in this cycle, but with characteristics that make it fundamentally different. Unlike nuclear weapons, which only a handful of nations could develop, AI weaponry is spreading rapidly across state militaries, nonstate armed groups, and criminal organizations. Unlike mechanization, which still required substantial industrial capacity, AI systems can be built from commercially available drones and open-source software. The barrier to entry keeps dropping, and the pace of innovation keeps accelerating.

For the Americas, this transformation arrives at a moment when the hemisphere faces multiple security challenges simultaneously: great power competition, internal conflicts driven by organized crime, and persistent threats from terrorism and insurgency. AI weaponry doesn't simply provide new tools for these conflicts, it changes the fundamental calculus of who can fight, how they fight, and what victory requires.

Why Weaponry Shapes Geopolitical Power

Military organizations convert national resources into coercive power, the ability to deter adversaries, protect territory, and project influence beyond borders. The weapons a military possesses determine what it can threaten, what it can defend, and how credible its commitments appear to allies and rivals.

When AI enters that toolkit, several dynamics shift simultaneously. It changes lethality, the capacity to find, engage, and destroy targets with greater speed and precision. It alters the speed of operations, compressing decision cycles in ways that can overwhelm adversaries operating at human cognitive speeds. It redistributes power, potentially allowing smaller forces to challenge larger ones through coordination, persistence, and willingness to accept losses that would be politically unacceptable for crewed platforms.

For the Americas, U.S. decisions about sharing or restricting AI military technology will shape the capabilities available to Canada, Mexico, and Latin American partners. Nations that can develop or access advanced AI weapons gain deterrence credibility. Those that cannot become dependent on external suppliers and vulnerable to having access restricted when interests diverge.

The Three Layers of AI in Military Affairs

Discussions of AI weaponry often default to images of autonomous killer robots, but that framing misses how AI is actually being integrated into military operations.

The first layer consists of AI embedded directly in weapons platforms: guidance systems that recognize and engage targets, loitering munitions that search for specific vehicle types, and missiles that adapt their flight paths based on defensive countermeasures. This layer generates the most public concern and faces the strongest constraints from international norms and export controls.

The second layer, command, control, intelligence, surveillance, and reconnaissance, may ultimately matter more for how wars are fought. AI systems that fuse data from satellites, drones, ground sensors, and intercepted communications can identify targets and recommend courses of action far faster than human analysts. These systems don't pull triggers, but they shape what gets targeted, when, and by what means.

The third layer encompasses enabling functions: logistics optimization, predictive maintenance, translation systems that allow real-time communication with partner forces, and cyber and electronic warfare tools that disrupt adversary networks. This layer attracts less attention but represents where AI is being deployed at the largest scale right now.

For the Americas, all three layers matter differently for different nations. The United States pursues capabilities across all three. Smaller nations often focus on the second and third layers where they can achieve meaningful improvements without requiring the massive industrial base needed for cutting-edge autonomous weapons.

The United States: Setting the Pace

The Pentagon serves as the central driver of AI military development in the Americas. The DoD budgeted $25.2 billion for programs incorporating artificial intelligence and autonomous systems in Fiscal Year 2025, about 3% of the DoD's total $850 billion budget. This represents a dramatic scaling up from $1.8 billion in fiscal year 2024.

The department maintains more than 685 active AI projects, mostly focused on decision-support, autonomy, and process optimization. These range from AI-enabled translation for Spanish-language officer courses serving Latin American partners to sophisticated battle management systems that coordinate sensors and shooters across domains.

The Replicator initiative, announced in August 2023, exemplifies the Pentagon's strategic direction. The goal is to field autonomous systems at scale of multiple thousands in multiple domains within 18 to 24 months. The Pentagon recently awarded up to $200 million each to four U.S.-based AI companies developing frontier models: Anthropic, Google, OpenAI, and xAI, signaling intent to leverage commercial AI breakthroughs for military applications.

This investment reflects clear strategic calculus: the United States sees AI as essential to offsetting China's numerical advantages in ships, missiles, and conventional platforms. The concept is to field large numbers of networked, intelligent systems that coordinate at machine speeds, creating effects that overwhelm traditional defenses.

For Latin American partners, this trajectory creates both opportunities and dependencies. Washington is integrating AI across security cooperation programs, but access to advanced capabilities will be conditioned on alignment, interoperability with U.S. systems, and willingness to adopt American standards rather than Chinese alternatives.

Canada: Alliance Obligations Meet Ethical Concerns

Canada is not a first-tier AI weapons developer, but it occupies a distinctive position as both a close U.S. military ally and a global leader in AI research, particularly in machine learning that underpins military applications.

Canadian defense policy increasingly frames AI as part of both economic security and alliance obligations. Ottawa faces pressure to contribute meaningfully to North American and NATO defense while maintaining its emphasis on responsible AI development and meaningful human control over autonomous systems. This creates tension between military effectiveness and ethical frameworks.

Canada's practical contributions focus on areas where its research strengths translate into capability: AI for data analysis, autonomous surveillance systems, and decision-support tools that augment rather than replace human commanders. But Canada depends on integration with U.S. military systems and cannot independently develop cutting-edge AI weapons programs at Pentagon scale.

Mexico: Internal Security, Not Interstate Warfare

Mexico's military AI trajectory looks fundamentally different because Mexico faces fundamentally different security challenges. The Mexican armed forces aren't preparing for interstate conflict with peer competitors. They're engaged in internal security operations against powerful criminal organizations that increasingly employ their own technology, including drones.

Mexican security forces are integrating commercially available drones and counter-drone systems into counternarcotics operations. The operational focus is surveillance, intelligence gathering, and defending bases from drone attacks, not developing autonomous weapons for conventional warfare.

Mexico's limited indigenous defense technology capacity means the country will primarily consume U.S. or commercial AI systems rather than develop cutting-edge autonomous weapons domestically. But technology vendor choices carry geopolitical implications. Chinese telecommunications infrastructure in Mexico creates potential complications for integrating U.S. military AI systems that depend on secure data flows. Washington increasingly views technology stack alignment as a prerequisite for deep security cooperation.

Latin America: The Drone Arms Race

Across the rest of Latin America, AI weaponry is advancing unevenly, driven primarily by internal security concerns rather than conventional interstate war preparation.

Colombia provides perhaps the most dramatic example. Between 2024 and 2025, Colombian authorities recorded 264 attacks from drones loaded with explosives, primarily in coca-growing regions where the National Liberation Army and dissident FARC factions maintain strongholds. These attacks killed 15 soldiers and wounded 153 others, demonstrating how commercially available drones adapted with improvised explosives can impose meaningful costs on conventional forces.

Colombia's response illustrates the broader dynamic reshaping Latin American defense procurement. Colombia has officially launched the National Anti-Drone Shield Project, a multi-phase defense program valued at approximately 6.3 trillion Colombian pesos (US$1.68-1.7 billion). The project's first phase is budgeted at 1 trillion pesos (approximately US$260 million).

This represents a massive investment for a country whose defense budget historically focused on personnel and basic counterinsurgency equipment. The drone threat has forced Colombia to leap directly into sophisticated counter-UAS technology without gradual progression through earlier air defense generations.

Other nations face similar dynamics. Peru, Brazil, and others are investing in drones for ISR and counter-drone systems to protect bases and critical infrastructure. But the threat isn't purely military. Criminal organizations across the region are experimenting with drone-borne explosives and surveillance, pushing states into an arms race where nonstate actors set the pace of innovation.

This creates a market that has become a geopolitical competition space. U.S., European, Turkish, Israeli, and Chinese vendors are all positioning to supply Latin American militaries with drone and counter-drone systems. Procurement decisions are alignment decisions, shaping not just immediate capability but long-term dependence on specific vendors.

Coordination at Scale: Swarms and Networks

Individual autonomous weapons represent one level of development. But the real transformation comes from coordinating large numbers of intelligent platforms simultaneously, creating effects that human operators cannot match.

Swarming represents the conceptual breakthrough. Algorithms can coordinate dozens or hundreds of cheap drones that adapt in real time to defensive measures, shifting targets, and battlefield changes. Unlike traditionally commanded units where losing the leader disrupts the force, swarms maintain coherence because control is distributed.

The Pentagon's vision of fielding thousands of autonomous systems across domains explicitly targets this capability. The goal is masses of coordinated effects that overwhelm defenses designed to intercept smaller numbers of threats.

Battle networks extend this logic beyond individual missions to entire force structures. Sensors, shooters, and command nodes link together with AI suggesting or automating engagement chains. A satellite detects a target, an airborne sensor refines its location, AI calculates the optimal weapon and firing platform, and the engagement executes with minimal human intervention.

The Asymmetries AI Creates

For all the sophistication of networked autonomous systems, military AI creates strategic holes that smaller actors can exploit. Three asymmetries deserve particular attention.

Cost Asymmetry

States invest billions in expensive, integrated AI systems. Nonstate actors can impose disproportionate costs with cheap semi-autonomous drones, electronic jamming, or cyber tools that exploit vulnerabilities.

The ELN in Colombia doesn't need cutting-edge AI to threaten Colombian military bases. Commercial drones modified with simple guidance systems and improvised explosives create casualties and force massive investments in countermeasures. The cost exchange favors the insurgents: a $2,000 modified drone can force deployment of $100,000 counter-drone systems.

Disrupting power grids or data networks degrades both commercial and military AI capabilities. The infrastructure dependencies discussed in Volume 4 become strategic vulnerabilities that adversaries don't need sophisticated AI to exploit.

Data and Dependency Asymmetry

Many Latin American militaries will rely on foreign AI models, cloud infrastructure, and commercial vendors. This creates dependencies where access to updates, data, or capabilities can be throttled by external powers.

In a crisis, what happens when a Latin American military dependent on U.S. cloud services for AI-enabled intelligence finds its access degraded because Washington objects to how that country intends to employ the capability?

Meanwhile, nonstate actors increasingly rely on open-source tools and commercial platforms harder to "turn off" politically. They don't depend on government vendors or classified data feeds, giving them operational freedom that state militaries constrained by formal procurement processes cannot match.

Governance and Legitimacy Asymmetry

States face legal and political constraints when deploying AI for targeting, surveillance, and internal security. Mistakes delegitimize governments and fuel backlash. A drone strike that kills civilians or an AI surveillance system that targets political opponents carries political costs that can outweigh tactical gains.

Nonstate actors don't care about attribution, collateral damage, or international law. They operate in gray zones where legal accountability is difficult and public opinion doesn't constrain their actions.

This asymmetry is particularly dangerous in fragile democracies where AI-enhanced repression can erode institutional trust. If governments deploy AI surveillance and targeting systems against domestic populations without safeguards, they risk the legitimacy that sustains democratic governance.

What Comes Next

We have now examined five dimensions of AI's geopolitical impact on the Americas: its emergence as a strategic industry, its employment implications, the supply chains and infrastructure it requires, the natural resources that sustain it, and the military applications that make it a tool of coercive power.

Each dimension reveals the same underlying dynamic: AI is concentrating in ways that create dependencies, but those dependencies are being contested by states and nonstate actors who seek autonomy, leverage, or simply the ability to disrupt systems they cannot control.

Next week, we turn to the governance and standards battles that will determine whether AI develops within frameworks that preserve hemispheric stability or whether competing regulatory models fragment the hemisphere into incompatible technology ecosystems. Military AI weaponry exists within legal and normative frameworks that shape what's permissible and what triggers international censure. But those frameworks are being negotiated right now, and the outcome is far from predetermined.

The question isn't whether AI weaponry will spread across the Americas. It already has. The question is whether governance mechanisms can channel that spread in directions that preserve security without sacrificing the democratic values and human rights protections that should distinguish the hemisphere from authoritarian alternatives.

This is Part 6 of a 10-part series on The Geopolitics of Artificial Intelligence in the Americas by Core Geopolitical Insights LLC. Follow along each week as we explore how this transformative technology is reshaping power, prosperity, and security across the Western Hemisphere. | Next week: Governance and Standards