Technology and War

Introduction: Technology as a Strategic Variable

The relationship between technology and warfare has always been constitutive rather than merely instrumental. Nuclear weapons did not simply add a more powerful explosive to the arsenal; they fundamentally restructured the logic of deterrence, the meaning of victory, and the very possibility of great power conflict. Today, a new constellation of technologies—artificial intelligence, advanced semiconductors, and pervasive surveillance systems—is provoking a transformation of similar magnitude. These technologies are reorganizing the conditions under which states project power, compete for advantage, and manage insecurity. For security studies scholars, the pressing question is not whether warfare is becoming "more technological" but rather how these innovations reshape the foundational concepts of the field: deterrence, coercion, escalation, and the political economy of military power.

The stakes are evident in the scale of investment and institutional change now underway. The Australian Defence Force has committed approximately A$425 billion in capability investment through 2035-36, with AI named as a force multiplier across domains from undersea warfare to cyber operations . The United States has channeled $52.7 billion through the CHIPS Act, while Taiwan Semiconductor Manufacturing Company (TSMC) has announced a new $100 billion investment to build five additional chip facilities in the United States . These are not merely procurement decisions; they represent a fundamental bet that technological capability has become coextensive with strategic power itself.

Yet the integration of AI, semiconductors, and surveillance into military systems generates profound risks that security studies must confront. The compression of decision cycles, the opacity of algorithmic systems, the strategic dependencies created by concentrated supply chains, and the potential for inadvertent escalation all demand analytical attention. As one analysis warns, "the most serious long-term risk involves integrating AI into nuclear command, control and communications systems," potentially weakening deterrence by eroding second-strike confidence and increasing the likelihood of false alarms . The challenge for security studies is to examine how military innovation redistributes vulnerability and advantage across states—and to assess whether the governance of these technologies can keep pace with their proliferation.

Technology and State Capacity

Technological advantage enhances state capacity along multiple dimensions: decision speed, operational reach, and industrial resilience. These are not isolated attributes but components of a broader sociotechnical system that links industrial policy, military doctrine, and battlefield effectiveness. The scholars at the Institute for National Strategic Studies observe that "AI accelerates decision cycles, extends operational reach, and enables exercised control of the informational, and cognitive dimensions of engagement" . This capacity to compress time and expand reach represents a qualitative shift in what states can accomplish through military means.

Consider the relationship between AI and decision-making. AI systems can analyze intelligence data and provide commanders with recommendations at speeds that outpace human cognition. As a result, "commanders might rely more on AI recommendations rather than wait for a detailed analysis," potentially creating "an accountability gap—the challenge of assigning responsibility when AI systems cause harm" . The compression of decision time is not merely an operational matter; it has strategic consequences. In crisis environments, accelerated alerts can "build momentum faster than diplomacy can absorb," meaning that "escalation can emerge from speed and uncertainty rather than from deliberate choice" . This dynamic fundamentally challenges traditional models of crisis management that assume human judgment can impose rationality on events.

Semiconductors underpin these capabilities at the hardware level. Every AI system, every surveillance network, every precision-guided weapon depends on microchips at its computational core. As one Indian defense analyst notes, "drones, anti-drone systems, quantum computing and directed-energy weapons will define the future" of warfare—and every one of these systems "depends on a semiconductor at its computational core" . The strategic significance of semiconductors lies not only in their functionality but in the vulnerabilities created by their production geography. Taiwan controls roughly 67% of global foundry capacity, while the United States dominates chip design and certain equipment categories . This concentration creates choke points that can be weaponized by states seeking to deny technological capability to adversaries.

The surveillance dimension of state capacity operates through the collection, fusion, and analysis of vast quantities of data. The TITAN (Tactical Intelligence Targeting Access Node) system, described as the Army's first "AI-defined" vehicle, "uses AI to fuse sensor data and help commanders make faster decisions" . Persistent monitoring, remote sensing, and data fusion improve targeting, border control, and coercive diplomacy. Yet surveillance also makes war more opaque in some respects, because decision-making is distributed across sensors, algorithms, and institutions. The same data streams that support tactical battlefield awareness may simultaneously inform strategic deterrence decisions, blurring the traditional boundaries that separate tactical and strategic actions .

The integration of these technologies suggests that state capacity is increasingly a function of sociotechnical systems rather than isolated capabilities. As one analysis puts it, "data has become a strategic resource; controlling data corridors is now as vital as controlling physical borders in terms of national sovereignty" . The capacity to command data, networks, and tech infrastructure has become a new dimension of state power, one that challenges conventional understandings of what constitutes military strength.

AI and the Changing Character of War

The integration of AI into military systems is transforming the character of war by compressing decision time and intensifying competition over information superiority. This transformation is not simply about replacing human judgment with algorithmic decision-making; it is about changing the tempo and scale at which states can sense, process, and act. As one study observes, "AI enables military forces to process information and coordinate responses quicker than ever before, pushing adversaries to develop similar capabilities to avoid falling behind in the AI military race" . This dynamic has implications for strategic stability that security studies must examine carefully.

The compression of decision cycles has particular significance for crisis management and escalation dynamics. In traditional conflict, escalation was expected to follow a systematic process: detection of a crisis trigger, verification and attribution, political deliberation, and execution of a response. AI-enabled systems "bypass these stages almost entirely," accelerating decision cycles and weakening human oversight . The "Super OODA" architecture enabled by AI shifts battle decision-making from traditional human-led loops to faster, AI-driven processes characterized by "reduced human cognition—or the ability of decisionmakers to interpret, evaluate, and contextualize information—and enhanced goal-centric decision-making, in which algorithms prioritize achieving predefined objectives over exercising situational judgment or restraint" .

The risks of this acceleration are compounded by the unreliability of AI systems in novel contexts. Unlike traditional software that follows explicit rules, AI systems trained on data "can produce unpredictable outputs when they encounter situations outside their training data" . This unreliability creates particular dangers in military applications, where the consequences of algorithmic error can be catastrophic. Moreover, the integration of AI into military decision-making creates an accountability gap: "the challenge of assigning responsibility when AI systems cause harm" . This gap is not merely a legal or ethical problem; it has strategic consequences, as the inability to assign responsibility can undermine deterrence and make escalation more likely.

The risk of misperception is another critical dimension of AI integration. How rivals interpret a capability "matters as much as what it does" . When states deploy AI-enabled systems, adversaries may interpret these capabilities through the lens of their own worst-case assumptions. A Chinese naval commander observing Australian undersea surveillance activity "cannot easily see whether it is oriented towards conventional denial or towards tracking nuclear platforms" . This ambiguity can generate pressure for escalation, as rivals may preemptively act to restore room for maneuver. As one analyst notes, "the mechanism is fear and expectation: when rivals interpret AI-enabled awareness as compressing their options, they may escalate to restore room for manoeuvre" .

The governance of military AI lags significantly behind its integration. While the United Nations Group of Governmental Experts on Lethal Autonomous Weapons Systems has met periodically since 2017, it "has not produced any binding agreements" . The Political Declaration on Responsible Military Use of AI has been endorsed by over 50 states, but it establishes only "voluntary principles without enforcement mechanisms" . This governance deficit means that "the window for effective AI governance in military systems is closing due to increasing integration and institutional entrenchment" . The challenge for security studies is to understand how this governance gap affects strategic stability and what institutional innovations might be necessary to address it.

Semiconductors and Strategic Dependency

Semiconductors are not merely an economic sector; they are strategic infrastructure that shapes the distribution of military power among states. Advanced chip design and fabrication determine who can build modern weapons, run AI systems, and sustain secure communications. As one analysis observes, "microelectronics are essential to all of these AI functions and applications. Algorithms operate only as quickly, securely, and as reliably as the silicon components that subserve them" . The security implications of semiconductor dependency are profound, as concentrated supply chains generate vulnerability, leverage, and the potential for coercion.

The geography of semiconductor production creates strategic dependencies that states cannot easily overcome. The United States dominates chip design and certain equipment categories, representing about 50% of global revenue. Taiwan controls roughly 67% of global foundry capacity through TSMC. Europe's strength lies in ASML's advanced EUV lithography technologies, "the machines everyone needs but only one company currently makes" . This extreme specialization means that the global semiconductor supply chain is a "house of cards," in which "the entire global economy now depends on a supply chain so specialized that losing even one supplier can shut down entire industries" .

The weaponization of semiconductor dependencies has become a central feature of US-China strategic competition. The United States has imposed export controls "prohibiting state-of-the-art technologies such as extreme ultraviolet (EUV) lithography machines and sophisticated AI chips," severely restricting China's access to essential tools and expertise . These restrictions "do not merely impede China's pursuit of technological self-sufficiency; they also pose a real threat of cleaving the global supply chain into two distinct factions—one dominated by the US and its allies, and the other centred around China" . The fragmentation of the semiconductor supply chain has economic costs—semiconductor prices could increase by 35-65% due to suboptimal scale and inefficiencies—but it also has strategic consequences, as the division of the global economy into competing blocs intensifies geopolitical competition .

For states dependent on foreign semiconductors, the risks are multidimensional. One analysis highlights the discovery of "undocumented 'rogue' communication devices in Chinese-manufactured solar power inverters," demonstrating that "foreign-manufactured, mission-relevant microelectronics may serve dual-use functions that are neither transparent nor controllable under peacetime procurement regimes" . The insertion of tainted components into critical infrastructure "effectively constitutes a latent kill switch," which could be activated to "catalyze blackouts, damage grid synchronization, or degrade continuity of operations across critical defense installations" . This vulnerability extends to military AI systems, which "increasingly rely on complex energy management hierarchies—many of which draw from the civilian grid" . As one analysis warns, "the adversary's intent is to disrupt, if not disable key systems preemptively—without warning, detection, attribution, or recourse" .

The response to semiconductor dependency has been a wave of national industrial policies aimed at building domestic capacity. The United States committed $52.7 billion through the CHIPS Act plus additional tax credits. The European Union established a €43 billion Chips Act through 2030. China launched its third "Big Fund" phase in May 2024 with $47.5 billion. South Korea developed a $450 billion K-Semiconductor strategy through 2030 . India has entered the semiconductor competition with its $10 billion Semiconductor Mission . Yet complete self-sufficiency remains "financially prohibitive for any country," and "smart interdependence" may be a more realistic goal than impossible independence . The challenge for states is to manage dependency, not eliminate it—a task that requires strategic discrimination about which capabilities must be secured and which can be sourced from allies or the global market.

The governance of semiconductors has thus become a domain of strategic competition. As one study observes, "the US, in particular, is seeking to leverage its security patronage to align its allies and partners with its technological and economic security strategies" . Technologically advanced democracies respond to US pressures in different ways, ranging from full alignment to selective autonomy, depending on their degree of security commitment to the United States and their relative power in the semiconductor global value chain . This diversity of responses suggests that the governance of semiconductors will remain contested as states balance alliance obligations against technological sovereignty.

Surveillance, Targeting, and Power Projection

Surveillance technologies alter the relationship between information and force in ways that have profound implications for military power and strategic stability. Persistent monitoring, remote sensing, and data fusion improve targeting, border control, and coercive diplomacy—but they also change what states can know, how they justify action, and how they normalize exceptional measures. The integration of AI into surveillance systems accelerates these dynamics, enabling "the scale, tempo, and precision" of intelligence, surveillance, and reconnaissance (ISR) operations to surpass conventional means .

The production of targets is a central concern in the literature on surveillance and warfare. AI-driven surveillance can identify potential targets with unprecedented speed and accuracy, but it also creates risks of misidentification and algorithmic error. As one analysis notes, "bias in training data—such as datasets that over-represent certain regions, demographic groups or conflict types—can lead to distorted predictions" . These distortions have consequences not only for civilian harm but for strategic decision-making, as commanders may rely on algorithmic recommendations that reflect systematic biases rather than operational reality.

The entanglement of surveillance systems across domains has strategic implications that security studies must examine. Satellite surveillance, for instance, "may simultaneously support tactical battlefield awareness and strategic deterrence" . Where tactical and strategic surveillance operated through separate assets and command channels, today's integrated systems fuse both functions, allowing the same data stream to inform real-time targeting and long-term deterrence decisions. This "deep inter-connectivity breaks down the traditional escalation ladder that notionally separates tactical and strategic actions" and "leads to the emergence of a 'strategic state,' in which all systems are entangled across domains, enabling AI-driven and increasingly opaque goal-centric decision-making" . In this context, a limited action—like jamming a radar or disrupting a satellite link—can yield unintended consequences elsewhere in the system, potentially triggering escalation through mechanisms that human decision-makers may not fully understand.

The strategic implications of surveillance integration are particularly acute in regions with existing tensions. The May 2025 conflict between India and Pakistan, in which "major cities and military installations were struck directly using AI targeting," demonstrated how surveillance capabilities can lower the threshold for conflict . Both states are pursuing AI-integrated ISR and autonomous defense systems, with India developing AI-enabled air defense networks "that can detect, track, and respond to multiple threats in real time" and Pakistan establishing a Centre for Artificial Intelligence and Computing focused on "automating threat recognition, data fusion, and cognitive electronic-warfare systems" . These capabilities, intended to enhance situational awareness and decision speed, also compress decision cycles and narrow the space for deliberate command decisions. As one analysis observes, "tactical speed" can become "strategic pressure," creating conditions in which limited actions trigger escalatory responses through mechanisms that human leaders may not anticipate or control .

The normalization of surveillance as a routine dimension of military operations raises questions about the boundaries between war and peace. Persistent monitoring, remote sensing, and data fusion blur the distinction between peacetime intelligence collection and wartime targeting, creating a condition of "always-on" surveillance that may lower the threshold for the use of force. The governance of surveillance technologies lags behind their proliferation, with limited international frameworks to regulate their use or establish accountability for harms. For security studies, this governance gap represents a critical area for research and policy engagement.

Military Innovation and Competition

Military innovation emerges from interaction among states, firms, labs, and defense institutions. The new strategic environment rewards systems integration, rapid experimentation, and dual-use innovation—not just platform acquisition. The integration of AI and semiconductors into military systems is not simply a technical process; it is a social and political one, shaped by procurement systems, civil-military relations, and tolerance for risk. As one analysis of the US defense establishment observes, "the winners will be those who successfully establish technology innovation into the national grand strategy" .

The convergence of civilian and military innovation ecosystems is reshaping how states develop military capabilities. The commissioning of tech executives from OpenAI, Meta, and Palantir as reserve officers in the US Army's Detachment 201 "signals a new chapter in civil-military cooperation, where service to country doesn't only mean deploying overseas with a rifle, but it can also mean deploying code and commercial innovation expertise in service of national defense" . This convergence brings Silicon Valley's "move fast, innovate, iterate" ethos into defense thinking, potentially accelerating the development and deployment of new capabilities . Yet it also raises questions about democratic oversight, as "the ethos of the tech industry" may conflict with the deliberative norms of democratic governance .

The political economy of military innovation is equally significant. The integration of AI into defense systems requires significant investment, but "start-up costs for AI are substantial, requiring significant upfront capital that intensifies an already pressured fiscal environment" . The allocation of resources toward AI "will inevitably necessitate some redirection of funding from existing programs, compelling a transparent assessment of capability prioritization" . These trade-offs have strategic consequences, as "each allocation toward AI carries a counterbalance—potential reductions in legacy systems, emerging capabilities, or critical support functions—with consequences that can, and likely will reverberate throughout operational readiness and strategic architectures and postures" . The challenge for states is to discern "where AI investments yield decisive advantage and where careful reallocation aligns with overarching national defense objectives" .

The path-dependent nature of military innovation means that states differ in their capacity to develop and deploy new technologies. Institutional arrangements for procurement, civil-military relations, and tolerance for risk shape the trajectory of innovation in ways that are not easily changed. The United States, with its vibrant venture capital ecosystem and defense-industrial base, has advantages in dual-use innovation. China, with its state-driven investments and central planning, may have advantages in mobilizing resources at scale but faces challenges in translating research into operational capability. The European Union, with its fragmented defense industrial base and limited integration, faces challenges in achieving the scale necessary for semiconductor self-sufficiency . These differences have consequences for strategic competition, as states with more agile innovation systems may be able to exploit new technologies more rapidly than their rivals.

Implications for Security Studies

The analysis presented above suggests that technology is reorganizing the material basis of security competition while reshaping the epistemic practices through which threats are identified and managed. For security studies, this has several implications that warrant attention.

First, the concepts of deterrence and escalation must be rethought in light of AI-enabled decision-making. Traditional deterrence theory assumes that rational actors can communicate credible threats, establish red lines, and calculate consequences. AI systems that compress decision cycles and generate unpredictable outputs undermine these assumptions. As one analysis warns, "wars might be fought and decided at algorithmic speed, with humans relegated to observers of machine-driven escalation spirals they initiated but cannot control" . The risk of inadvertent escalation through algorithmic misperception or system failure is not merely theoretical; it is a live concern for states integrating AI into command and control systems. Security studies must develop new conceptual frameworks that account for the ways in which AI systems shape escalation dynamics, including the potential for misperception, the opacity of algorithmic decision-making, and the accountability gap that arises when machines generate recommendations that humans cannot adequately scrutinize.

Second, the relationship between technology and state power must be understood in terms of networks and dependencies, not simply capabilities. The semiconductor supply chain reveals how concentrated production creates choke points that can be weaponized by states seeking to deny technological capability to adversaries. The United States' export controls on advanced chips and manufacturing equipment demonstrate how technological dependency can be leveraged for strategic purposes. For security studies, this suggests a renewed attention to the political economy of military power—the ways in which industrial policy, supply chain vulnerabilities, and technological dependencies shape the distribution of power among states. The concept of "silicon sovereignty" captures this shift, as states seek to secure control over the computational infrastructure that underpins military capability .

Third, the integration of surveillance, AI, and semiconductors into military systems raises questions about the governance of strategic technology that security studies must address. The current governance architecture is fragmented, with voluntary principles but no binding agreements, limited coordination across international bodies, and no enforcement mechanisms. As one study observes, "the absence of a shared risk framework leaves states without common standards for assessing and managing the dangers that military AI systems pose" . This governance gap has strategic consequences, as it creates conditions for technological arms racing, misperception, and inadvertent escalation. Security studies can contribute to governance efforts by analyzing the conditions under which international cooperation on military technology is possible, the institutional mechanisms that might facilitate restraint, and the domestic political dynamics that shape states' willingness to accept limits on their technological freedom.

Finally, the transformation of warfare through AI, semiconductors, and surveillance raises fundamental questions about the relationship between technology and human agency in armed conflict. The compression of decision cycles, the opacity of algorithmic systems, and the integration of autonomous capabilities into military operations all suggest that human judgment is becoming increasingly peripheral to conflict dynamics. Yet the legal and ethical frameworks governing warfare assume human agency—the ability to exercise judgment, take responsibility, and comply with international humanitarian law. The gap between technological capability and legal-ethical frameworks is a source of strategic instability, as states deploy capabilities that outpace the norms governing their use. For security studies, this suggests a need to attend to the normative dimensions of technological change, including the conditions under which states develop norms for responsible military innovation and the mechanisms that might facilitate restraint.

The central challenge of the AI era is governing technological competition without amplifying instability. The technologies analyzed here—AI, semiconductors, and surveillance—are not neutral instruments that states can simply add to their arsenals. They are reorganizing the conditions under which states project power, compete for advantage, and manage insecurity. For security studies, understanding this reorganization—and developing frameworks for governing it—is an urgent intellectual and practical task. The outcome of this effort will shape not only the future of warfare but the broader character of international politics in an era of technological transformation.