The label of the “first AI war” obscures the reality that Operation EPIC FURY is still a conflict in which human judgment remains central to targeting. Artificial intelligence (AI) has not replaced human operators, but it has redefined how human judgment functions. The contemporary battlefield is now shaped by rate of fire, targeting accuracy, AI-enhanced cognition, and the real transformation that machine learning has introduced into modern warfare. 

One of the most persistent misunderstandings about AI-assisted targeting is the claim that humans have somehow been removed from the loop, decisions are made solely on AI recommendations, or strikes are approved in seconds without meaningful review. The human factor has not disappeared. Humans remain indispensable to targeting. What has evolved is not the elimination of human involvement, but the rapid synthesis of intelligence with target acquisition. That distinction matters because many assume there is little or no review before a strike is done. However, no systems make decisions independently. They supplement human decision-making by sorting and ranking information to generate recommended outcomes that must still meet rigid criteria. Analysts verify intelligence, legal teams conduct reviews, commanders make the final decision, and human beings remain responsible for the outcome. 

Critics often point to ambiguity in strategic-level U.S. directives. The Department of War Directive 3000.09 attempted to regulate certain AI-enabled systems, though the technology at the time was far less sophisticated than it is today. Military doctrine undermines the myth of autonomous targeting as well. The Army’s FM 3-60 frames targeting as an iterative command process and states that commanders remain the final approval authority for targeting activities and acceptable levels of risk. Machines may assist with detection, but they do not inherit command responsibility. The result is that humans remain in the loop because targeting is still a command process, not an autonomous one. Military doctrine frames targeting as a cycle of deciding, detecting, delivering, and assessing, but commanders retain authority over acceptable risks. AI can compress and organize the data, but it cannot make strategic or moral judgments. 

AI models remain central to identity-based targeting and advanced decision support. Open-source reporting indicates that sophisticated models, such as Anthropic’s Claude, integrated into systems such as Palantir designed Maven Smart System, have enabled rapid conversion of vast amounts of intelligence, surveillance, and reconnaissance (ISR), signals intelligence, and behavioral data into target packages. 

Human productivity has also increased. Tasks that once required weeks and a large staff can now be completed in minutes with fewer personnel. However, speed and efficiency do not mean AI independence. It does not change what Clausewitz described as the “grammar of war.”  

The most consequential shift in conflict today is the compression of time within the targeting cycle and its integration into intelligence. In the past, high-value or high-payoff targets were often missed because manual processes relied heavily on human operators and overwhelming amounts of ISR data. Past conflicts reflected these limitations. During Operation Desert Storm, Iraqi mobile Scud launchers exploited delays by firing and relocating before U.S. forces could strike them. Kinetic precision still frequently exceeds intelligence fidelity. A munition could hit its coordinates perfectly while the underlying intelligence remained flawed. The use of intelligence to target enemy combatants predates modern technology. AI did not invent decapitation strategies; it made them more data-driven and less dependent on purely human intelligence sources. The Information Age once overwhelmed operators with data. AI now provides a way to navigate that environment. This is why cyber intelligence and persistent access are essential to modern targeting. Pattern-of-life targeting relies on multiple streams of surveillance and behavioral data. AI’s greatest strength is its ability to combine these streams on a scale that would overwhelm most military units. Yet the central question remains unresolved by algorithms alone: should the target be neutralized? That decision is legal, moral, political, and strategic. 

A clear example of AI-integrated intelligence limits came on the first day of the 2026 Iran War, when a U.S. missile struck an elementary school in Minab, Hormozgan province, killing civilians, including children, in one of the war’s deadliest civilian incidents. The incident underscored a basic truth: AI-enabled targeting is only as dependable as its data. Here, the system likely relied on outdated intelligence that missed the school’s proximity to an Islamic Revolutionary Guard Corps compound.  

AI was not the likely source of failure. More likely, flawed intelligence and the fog of war were to blame. Human operators still validated the strike with satellite imagery and intelligence reviews, even though the target was effectively co-located with the school.  

The episode showed both the limits of AI models and the need for human review. Systems like Maven Smart System’s Target Workbench sort, correlate, and reveal intelligence, but humans still approve of final actions. AI can aid target validation, but legal review and command authorization remain essential. 

CONCLUSION 

The effectiveness of any algorithm depends entirely on the intelligence architecture and data supporting it. AI does not create certainty; it produces probability. If the underlying data is manipulated, incomplete, stale, or inaccurate, the output will reflect those flaws. The greater danger is not the removal of the human in the loop, but the compression of human judgment into groupthink. AI-generated recommendations can create an aura of probabilistic certainty that encourages agreement instead of scrutiny. Human operators may still make the final call, but the risk is that they increasingly validate model logic rather than independently challenge it. 

Humans remain in the loop today, but intelligence is now sorted at machine speed while generative systems provide recommendations to reviewers within the targeting cycle. Doctrine should evolve to ensure that human judgment takes precedence over AI-generated recommendations. The defining feature of this so-called first AI war is therefore not the replacement of human agency, but the intensification of human responsibility to judge, restrain, and decide at machine speed. 

Lieutenant Colonel Matthew J. Fecteau is an information operations officer working with artificial intelligence, and a PhD researcher at King’s College London. The views expressed in this report are those of the author and do not necessarily reflect the official policy or position of the Department of the Army, the Department of War, or the US Government. 

Why the “First AI War” is Still a Human Struggle was originally published on Global Security Review.

Artificial intelligence is quietly redrawing the front lines of national security, and the United States’ Defense Industrial Base (DIB) now sits in the crosshairs of a new style of conflict. What once looked like routine cyber incidents now appears as a persistent campaign that fuses digital intrusion, supply chain manipulation, and targeted information operations into a single pressure system aimed at the factories, laboratories, and logistics networks that keep American forces armed and ready.

When most Americans imagine national defense, they focus on the uniformed force and the platforms that dominate headlines. Behind that visible edge of power stands a sprawling, largely private ecosystem of designers, manufacturers, software firms, logistics providers, depots, and research institutions that convert national intent into fielded combat capability. Federal regulation describes this DIB as the combined government and private sector industrial complex that can research, develop, produce, and sustain weapon systems and their components at the scale required for military operations.

That chain is far more diverse than the marquee names on major defense contracts. It includes niche machine shops, regional logistics firms, university laboratories, software providers, and government facilities that share technical data and workflow information through a constant flow of digital exchanges. Design files, bills of material, maintenance records, and operational telemetry form the nervous system of this industrial organism. When the system is healthy, the nation can surge production and sustain readiness under stress. When it is strained, deterrence becomes much harder to demonstrate in a crisis.

This industrial nervous system is absorbing AI at high speed, often with limited guardrails. Across the DIB, machine learning supports predictive maintenance, defect detection, demand forecasting, scheduling, and supply chain visibility. Corporate leadership often has only a surface-level understanding of how thinking machines can erode corporate identity, trust, and reputation quietly, yet catastrophically.

For the strategist, this adaptation expands the terrain adversaries can probe. Industry surveys in the World Economic Forum’s Global Cybersecurity Outlook 2026 report show that executives see AI as the primary driver of change in cybersecurity and regard AI-related vulnerabilities as the fastest-growing category of cyber risk. Organizations recognize that their attack surface is expanding as AI tools move into sensitive workflows, yet governance practices and security controls often lag deployment.

Hybrid campaigns against the DIB rarely announce themselves through spectacular outages. Security officials describe a patient pattern that begins with access and aims for endurance rather than immediate disruption. Once inside a network or supplier ecosystem, adversary teams map production rhythms, supplier dependencies, identity systems, and critical decision points where even modest delays can ripple across schedules and inventories. AI has become a force multiplier

for this reconnaissance, mining engineering files, and communications at machine speed and surfacing patterns that would take human analysts far longer to identify.

The contest is unfolding below the threshold of open conflict. Strategic competitors apply pressure through cyber intrusion, intellectual property theft, data manipulation, counterfeit insertion, and narrative operations designed to erode confidence in the U.S. capacity to arm itself and its allies. Hybrid pressure often manifests as subtle slowdown, rising cost, and creeping doubt rather than overt sabotage.

The stakes for deterrence are significant. Modern deterrence depends not only on visible platforms and war plans but also on an adversary’s belief that the United States can sustain forces and generate combat power at speed. If competitors conclude that AI-enabled systems in the DIB are brittle or easily manipulated, the credibility of deterrence weakens. The 2026 National Defense Strategy emphasizes strengthening the industrial base as a pillar of national power, tying cyber resilience directly to the ability to deter and wage war.

Pentagon planners increasingly describe cyber activity against the DIB as a persistent campaign environment. Adversaries can pursue national security effects through intrusions into private networks and business processes that support critical programs.

The technical attack surface is broad because the DIB operates as a tightly coupled system. Engineering teams collaborate across companies, moving design data through shared tools and platforms. Components flow through multiple tiers of suppliers before the final assembly. A single compromised vendor can offer adversaries access to multiple programs. Hybrid campaigns exploit these seams.

The effect of these operations extends beyond physical outcomes. Manipulated or stolen data can become material for influence narratives that frame U.S. production as unreliable or compromised. Production delays caused by cyber incidents can be amplified to sow doubt among allies about American capacity.

Adversary teams also benefit from repetition. They have treated the DIB as a learning environment, refining tradecraft through continuous operations. Hybrid coercion in this context is deliberate and calibrated, remaining below the threshold that would trigger a national response while still generating uncertainty and doubt.

Emerging evidence suggests that agentic AI systems are beginning to automate portions of this intrusion lifecycle. Automated chains reduce the cost of probing many suppliers and narrow the window for defenders to respond. For smaller firms with limited security resources, the pressure can quickly become unmanageable.

Security experts argue that defending against such campaigns will require disciplined governance and architecture. Pre-deployment AI security assessment and continuous validation must become standard practice, covering model selection, data provenance, access control, logging, and periodic reevaluation.

Architectural choices will also play a critical role. Zero trust principles and micro segmentation can reduce the impact of intrusions by limiting movement across networks. For DIB operators, this means treating segmentation and strong identity controls as the default architecture.

The industrial context around these cyber efforts is already volatile. The aerospace and defense sector is managing supply chain disruptions and resource constraints while trying to scale production. This environment amplifies the effectiveness of cyber sabotage and influence operations because attacks land in systems that are already stressed.

The strategic logic behind adversary focus on the DIB is clear. By degrading confidence and throughput, competitors can undercut deterrence without open conflict. When intrusions are contained and production continues under pressure, the calculus of hybrid aggression shifts.

Hybrid warfare against the DIB aims to bend trust in the systems that generate combat power. If those trust systems are distorted through advanced technologies and coordinated information operations, the result is slower decisions, higher costs, delayed output, and a quieter form of coercion.

Mr. Greg Sharpe is a Fellow and the director of Communications and Marketing for the National Institute for Deterrence Studies and the Managing Design Editor for the Global Security Review. Greg has over 35 years of military, federal civilian, and defense contractor experience in the fields of database development, digital marketing & analytics, technology use case exploration and assessment, and as a USAF doctrine outreach and engagement analyst. The views of the author are his own.

Quiet Warfare: Bending Data and Perceptions in the Defense Industrial Base was originally published on Global Security Review.

Their low cost, flexibility, and ability to operate without putting human pilots at risk make drones increasingly valuable in conventional military conflicts. Their capabilities already include reconnaissance and surveillance, long-range strike missions, electronic warfare, and precision killing.

With their precision-targeting ability, drones can be integrated into nuclear deterrence strategies. For instance, they could be used to ensure the survivability of a country’s nuclear forces by providing continuous surveillance and early warning against potential nuclear threats. Drones could also support a more viable second-strike capability, potentially increasing the credibility of nuclear deterrence by ensuring that a country retains a means to retaliate even after a nuclear first strike.

The use of drones in situations where nuclear escalation is a possibility could lead to unintended consequences. The increasing autonomy of drones raises the risk of misinterpretation, as drones could be perceived as a precursor to a larger attack, even when they are only conducting reconnaissance. This could trigger a preemptive nuclear strike by an adversary, leading to an inadvertent escalation into full-scale nuclear war. Cold War and subsequent histories show that the danger of inadvertent nuclear escalation is not trivial.

The possibility that expansion of the war in Ukraine from conventional weapons into nuclear first use could occur from Russian views of Ukrainian deep strikes into Russian territory, with NATO ballistic and cruise missiles, provides one example of concerns in this category.  Lewis A. Dunn suggests that President Donald Trump is faced with a world sliding into nuclear anarchy. He writes:

Brinkmanship among major nuclear powers is rising. China is relentlessly expanding its nuclear forces but rejecting serious engagement with the United States on arms control. US–Russia cooperation on nuclear matters, already in a dire state, has deteriorated further with President Vladimir Putin’s repeated nuclear threats in the course of Russia’s war in Ukraine. Recent reports based on information from senior US officials indicate that the United States, too, could modify its posture and expand its arsenal to strengthen deterrence of coordinated Russian, Chinese, and North Korean nuclear adventurism. All these developments have eroded critical pillars of nuclear order and raised the risk of nuclear warfare.

Drones are relatively fast, low-cost, and difficult to detect, which makes them ideal for preemptive strikes against high-value targets. In theory, a nation could deploy a drone strike against an adversary’s nuclear command-and-control infrastructure or missile silos, aiming to disrupt or neutralize a potential nuclear retaliation before it can be launched. In addition, drones equipped with nuclear payloads or advanced conventional weapons could be used as part of a disarming strike. The ability to carry out such strikes could shift the strategic calculations of nations, as adversaries might feel more vulnerable to a preemptive attack, especially if they believe their nuclear retaliation capabilities could be neutralized by fast-moving drone strikes.

As drones become more autonomous, the risk of them making decisions without human oversight increases. In a nuclear context, where the consequences of any action are catastrophic, the delegation of decision-making to machines is highly controversial. The potential for autonomous drones to trigger a nuclear response or make fatal miscalculations due to algorithmic errors presents a possible threat to strategic stability.

Given that drones can operate autonomously, one challenge is ensuring that their actions do not trigger unintended escalation. Moreover, the reliance on technological systems for communication and control in a nuclear context raises concerns about vulnerabilities in these systems, especially if adversaries employ cyberattacks or electronic warfare tactics to disrupt drone operations.

Future generations of drones will interact with artificial intelligence that also supports other elements in the matrix of deterrence and defense. AI will privilege deterrence by denial compared to deterrence by credible threat of unacceptable retaliation. It will do so because states will have to quickly manage the deterrence and/or conduct conflicts in multiple domains: land, sea, air, space, cyberspace, and the information or knowledge domain. The knowledge domain wraps around all the others. It is the “gnostic center” that controls, connects, and prioritizes among the component parts of the various domains in order to provide for the correct response to threats or attacks.

AI-assisted attacks on the gnostic center will require immediate responses by AI-assisted defenses that can defeat or diminish the cost of those attacks. Absorbing the first blow and then retaliating may not be a choice that is available to beleaguered and time-pressed decision-makers. This situation poses an especially concerning challenge for nuclear deterrence. Decisions for or against nuclear war should allow policymakers sufficient time to deliberate alternatives with their advisors and to select the most appropriate option for the exigent circumstances. But the potential speed of AI-boosted attacks against space and cyber assets, together with the rising speed of kinetic strikes from hypersonic weapons, may leave leaders fearful of an enemy nuclear first strike to choose preemption instead of retaliation.

Just as we can conceive of drones as reconnaissance and strike platforms for offenses, it is also possible that drones can be part of any state’s comprehensive antimissile and air defense plan. One illustration is the use of drone swarms to defeat attacking drones tasked with reconnaissance or strike missions. Another example would be the use of drones for electromagnetic “hit to kill” within the atmosphere or, even more ambitiously, in midcourse intercept against attacking ballistic missile forces. Drones based on one or more lunar spaceports could protect American interests in cislunar space.

Futuristic drones with embedded AI and space-to-space weapons could defend orbital satellites against attack (so-called DSATs) or engage another state’s satellites that appear threatening (ASATs). Priority DSATs and ASATs would deter or defend against any threat to the viability of American satellites for warning and assessment; command, control, and communications; geolocation; and other missions.

Comparatively inexpensive drones could thus take over some of the strategic defense burden, otherwise requiring both upgraded terrestrial missile launchers and kill vehicles or, eventually, sophisticated ballistic missile defenses based on space-to-earth weapons such as lasers or particle beams. Future planners should expect a more crowded space domain, including newer generations of orbital satellites with diverse missions, space stations, and additional reconnaissance and strike weapons along with smarter drones and larger swarms.

The preceding discussion about drones and their possible relationship to nuclear deterrence has implications for nuclear arms control. It is important for a peace agreement to terminate the war in Ukraine for many reasons. One reason is so that the United States and Russia can resume negotiations about an arms control regime to succeed the New START agreement, due to expire in 2026.

The “beyond New START” consultations should include discussions about the two states’ arsenals of non-strategic nuclear weapons and protocols for nuclear first use. Vladimir Putin’s repeated warnings about the possibility of Russian nuclear first use in Ukraine is dismissed by some as bluffing for effect, a form of coercive diplomacy. On the other hand, Russia’s doctrinal shifts appear to move toward a more permissive standard as the war continues. In addition to clarifying this matter, the United States and Russia must acknowledge that China is an aspiring nuclear peer and include China in discussions about nuclear policy issues, including transparency about force structures and military doctrines. China is unlikely to be interested in arms reductions per se, but dialogue should be initiated at the expert level to clarify China’s thinking about strategy, arms control, and related issues.

The character of war changes with the advent of new technologies and strategic thinking.  But the nature of war is perennially the environment of competition and conflict, uncertainty, chance, and friction. The relationship between drones and nuclear deterrence represents a mixed blessing for military planners and arms control. Drones have the potential to enhance nuclear deterrence, but they also introduce significant risks in terms of escalation control and first-strike stability. As drone technology advances, it will be critical for policymakers to develop strategies that account for the unique challenges drones pose in nuclear deterrence and, as well, their future roles in space and cyber wars.

Professor Stephen Cimbala, PhD, is a Senior Fellow at the National Institute for Deterrence Studies.

Nuclear Deterrence and Drones: An Unpredictable Mix? was originally published on Global Security Review.

These domains and areas are being weaponized for strategic purposes, as adversaries target cross-domain North Atlantic Treaty Organization (NATO) interests with the intent of weakening the Western security architecture and fragmenting alliance cohesion. The Trump administration must work closely with NATO allies to confront the many challenges that face them.

Strategic challenges, such as the Arctic, deep sea, and space, and the threats they pose require improved joint military readiness, enhanced deterrence by denial capabilities, and improved intelligence, surveillance, and reconnaissance.

“Over the last 15 years,” writes Scott Savits, “the Arctic has become a renewed theatre of military competition…. [T]op Russian officials have referred to the Arctic as Russia’s ‘Mecca,’ and a large fraction of Russia’s economy is based on Arctic fossil fuels and minerals.” Frustrating Russian efforts to gain a strategic advantage in the Arctic is of paramount importance to NATO’s deterrence mission.

Russia gaining an advantage in the Arctic will enhance its ability to establish escalation dominance against NATO in the event of a conflict with the alliance. Deterring Russia from broadening the scope of conflict, by threatening NATO’s vital interests in the Arctic, remains critical in dissuading other adversaries, such as China, from seeking to gain similar advantage.

With China developing and deploying new detection technologies in anti-submarine warfare, American nuclear submarine capabilities are becoming increasingly vulnerable to detection and targeting. China’s “Death Star” satellite claims to possess detection capabilities that renders the ocean transparent for up to 500 meters beneath the surface, putting American submarines at risk.

In the space domain, it is estimated that loss of access to space would come at a cost of roughly One billion pounds per day to the British economy. The reported deployment of Russian anti-satellite weapons systems (ASAT) in space are clearly coercive moves designed to threaten NATO’s space assets.

Russia’s weaponization of space is especially concerning as NATO depends on space to conduct an array of operations across the spectrum of deterrence and defence. Most notably, NATO airpower relies on space-based and space-dependent systems to fulfil a series of critical security functions. Leveraging robust deterrence capabilities in orbit, through targeting Russian and Chinese space-based military and non-military assets, is critical to securing NATO’s vital interests in space.

Beyond seeking strategic advantage, China is also expanding and modernising its nuclear arsenal at an unprecedented rate since the end of the Cold War. The Pentagon forecasts that China will be a nuclear peer of the United States by 2035. The latest figures published by the Federation of American Scientists show that China now possesses at least 500 operationally deployed nuclear weapons—up 43 percent from 2020.

Russian President Vladimir Putin continues to undermine international norms by persisting in threats to use battlefield nuclear weapons in Ukraine. Russia also deploys dual-use satellite technologies in space, capable of carrying nuclear warheads into orbit, in direct contravention of long-standing international treaties such as the Outer Space Treaty (1967), which prohibits the weaponization and nuclearization of space.

Meanwhile, Iran, a latent nuclear state, coerces the West by threatening the weaponization of its nuclear program. Iran also infiltrated the West by creating extremist networks through community centers, laundering money in major European and American cities that is used by criminal gangs to plot and execute terrorist attacks.

Proxies supported by Iran, such as Hamas and Hezbollah, can also launch increasingly devastating attacks. Furthermore, attacks like October 7, 2024, or September 11, 2001, do not warrant nuclear retaliation. A nuclear response to a terrorist attack, depending on the attack, is likely a disproportionate response.

China and Russia also engage in subversive activities within the cyber domain, sowing discord by using disinformation, intellectual property theft, and malign interference to destabilize NATO member states. Cyberattacks on critical national infrastructure can also inflict severe levels of damage. The appropriateness of cross-domain responses is yet to be decided.

The cyber attacks against Estonia in 2007, which lasted for 22 days, did not result in the triggering of NATO’s Article 5 collective defense clause. Yet, it was an attack on a NATO member state. The character of the attack complicated the process by which a viable and appropriate retaliatory response could be devised. In a multidomain threat landscape, hostile state actors conducting their operations in the grey zone can claim plausible deniability.

China, Iran, Russia, and North Korea also hold joint exercises, share intelligence, exchange military capabilities, and share a diplomatic and political kinship. This axis of Western adversaries shares the same geopolitical and economic objectives. They seek to replace the international rules-based order and establish alternative institutional frameworks to global order that undermine concepts such as democracy, human rights, rule of law, and national sovereignty.

Militarily, nowhere is this more apparent than in Russia, where Iranian drones and North Korean soldiers were provided to aid Putin’s war in Ukraine. Politically, emerging international blocs such as the BRICS demonstrate the extent to which countries like China and Russia are gaining traction in driving alternatives to the current order.

“As hybrid threats evolve to encompass the whole of digital and networked societies,” wrote Sean Monaghan, “so too will the capabilities required to deter them. A more complex threat environment will make predicting attacks and vulnerabilities more difficult, so nations may rely more on resilience.”

Hence, for deterrence to be effective today, credibility must incorporate more than hard power capabilities. Red lines must be communicated effectively across different channels. Resolve must be demonstrated through a force posture that includes a willingness to establish escalation dominance in a crisis scenario. The art of deterrence is also about determining and holding at risk what an adversary values.

As the outgoing US Secretary of Defence General (Ret.) Lloyd Austin said in 2022, cross-domain deterrence “is the right mix of technology, operational concepts, and capabilities—all woven together and networked in a way that is credible, flexible and so formidable that it will give any adversary pause…. [It is] multidomain, spans numerous geographic areas of responsibility, is united with allies and partners, and is fortified by all instruments of national power.”

Ultimately, deterrence is about credibly threatening to impose unacceptable costs, by denial or punishment, on a would-be aggressor. Those costs must convince the would-be aggressor that they outweigh any potential gains made.

Therefore, it is imperative for the US and NATO to increase cross-domain capabilities to match those of adversaries. Adopting a combination of different violent and non-violent means, to conduct deterrence credibly across multiple domains and at various levels of intensity, will enhance NATO’s ability to secure its vital interests in an increasingly volatile era of global strategic competition.

Alex Alfirraz Scheers holds a diploma in Politics and History from the Open University, a bachelor’s degree in War Studies and History from King’s College London, and a master’s degree in National Security Studies from King’s College London. He has held research positions at the Henry Jackson Society and the International Centre for the Study of Radicalisation, and his articles have been published in the Diplomat, Times of Israel, RealClearDefense, and the Royal United Services Institute. Views expressed in this article are the author’s own. 

Deterrence and NATO’s Emerging Security Environment was originally published on Global Security Review.

Standoff warfare is characterized by the use of long-range weapon systems, such as cruise missiles, drones, and precision-guided munitions, to engage targets from a safe distance. This approach leverages advanced surveillance, reconnaissance, and targeting technologies to identify and strike enemy assets without direct engagement.

Advantages of Standoff Warfare

One of the primary advantages of standoff warfare is the significant reduction in the risk to military personnel. By operating from a distance, forces are less exposed to direct enemy fire and ambushes, leading to fewer casualties and increased morale. By keeping forces out of the immediate reach of the enemy, standoff warfare helps preserve valuable military assets. This approach ensures that high-value equipment and personnel are available for prolonged engagements and future conflicts.

Modern long-range weapons are highly accurate, allowing for precision strikes on strategic targets. This capability enhances operational efficiency by focusing on high-value targets and minimizing collateral damage, which is crucial in maintaining public support and adhering to international laws of warfare.

The ability to strike from a distance can have a significant psychological impact on the enemy. The constant threat of unexpected precision attack can demoralize opposing forces and disrupt their operational planning and execution.

Standoff warfare allows for rapid deployment and response to emerging threats. With assets positioned at a safe distance, commanders can quickly adapt to changing battlefield conditions and execute strikes without the need for extensive mobilization.

Disadvantages of Standoff Warfare

Standoff warfare relies heavily on advanced technologies for surveillance, targeting, and weapon delivery. This dependence can be a vulnerability if these systems are disrupted by electronic warfare, cyberattacks, or other countermeasures.

The development, procurement, and maintenance of long-range weapon systems and associated technologies are expensive. The financial burden of sustaining a standoff warfare capability can strain defense budgets and divert resources from other critical areas.

Standoff warfare is most effective against concentrated, high-value targets. When facing adversaries employing dispersed, decentralized tactics, the efficiency of long-range strikes diminishes, necessitating alternative approaches.

Accurate intelligence and targeting data are crucial for successful standoff operations. The reliance on real-time, high-fidelity information can be a limitation if there are gaps in intelligence or if adversaries employ deception and concealment strategies.

The use of long-range strikes can be perceived as highly provocative and potentially escalatory in a conflict. Adversaries may respond with retaliatory measures, leading to a cycle of escalation that can spiral out of control.

China

China’s military modernization and expansion pose a significant challenge to American and allied forces in the Indo-Pacific region. China’s development of anti-access/area denial (A2/AD) capabilities, including long-range missiles, sophisticated air defenses, and naval assets, necessitates a robust standoff strategy.

Standoff warfare allows the US and its allies to engage Chinese assets from a distance, mitigating the risk posed by China’s A2/AD systems. The ability to strike from afar can disrupt Chinese operations, degrade critical infrastructure, and maintain freedom of navigation in contested areas.

China’s advancements in electronic warfare, cyber capabilities, and counter-space operations could undermine the effectiveness of standoff warfare. Additionally, the vast expanse of the Indo-Pacific region presents logistical challenges for sustaining long-range operations.

Russia

Russia’s military doctrine emphasizes hybrid warfare, combining conventional and unconventional tactics. Its integrated air defense systems, long-range missile capabilities, and electronic warfare proficiency make it a formidable adversary.

Standoff warfare enables NATO forces to counter Russian aggression by targeting key military installations, command-and-control centers, and logistical hubs from a safe distance. Precision strikes can degrade Russia’s offensive capabilities and hinder its operational tempo.

Russia’s integrated air defenses and advanced electronic warfare capabilities pose significant challenges to standoff operations. The risk of miscalculation and escalation is also high, given the proximity of NATO forces to Russian borders and the potential for rapid conflict escalation.

Iran

Iran’s strategic posture relies on asymmetric tactics, including the use of proxy forces, ballistic missiles, and naval assets in the Persian Gulf. Its ability to disrupt critical waterways and target regional adversaries necessitates a nuanced approach.

Standoff warfare allows the US and its allies to target Iranian missile launch sites, naval assets, and command structures with minimal risk to their forces. This approach can help deter Iranian aggression and protect vital shipping lanes in the region.

Iran’s use of underground facilities, mobile missile launchers, and dispersed assets presents challenges for effective targeting. Additionally, the potential for retaliatory actions against regional allies and American interests necessitates careful consideration of the broader geopolitical implications.

Conclusion

Standoff warfare continues to offer significant advantages in terms of force protection, precision, and operational flexibility. However, its effectiveness is contingent on technological superiority, accurate intelligence, and the ability to adapt to evolving threats. Against adversaries like China, Russia, and Iran, standoff warfare provides a valuable tool for countering their respective military capabilities. Nonetheless, it must be integrated into a comprehensive strategy that addresses the unique challenges posed by each adversary and mitigates the risks of escalation and technological vulnerabilities. As hypersonic, low-observable, and other advancing technologies continue to develop, they will force the need for rapid evolutions of military doctrines which will need to consider the role of standoff warfare as a critical component of modern defense strategies.

Joshua Thibert is a Contributing Senior Analyst at the National Institute for Deterrence Studies (NIDS) with nearly 30 years of comprehensive expertise, his background encompasses roles as a former counterintelligence special agent within the Department of Defense and as a practitioner in compliance, security, and risk management in the private sector. His extensive academic and practitioner experience spans strategic intelligence, multiple domains within defense and strategic studies, and critical infrastructure protection.

Striking from Afar: The Strategic Edge of Standoff Warfare was originally published on Global Security Review.

From counterterrorism efforts to geopolitical forecasting, the applications of AI in strategic intelligence operations span a diverse array of domains, shaping national security strategies and global geopolitics alike. However, alongside these transformative capabilities come complex ethical, legal, and policy considerations that necessitate careful navigation.

            Foremost, AI has the ability to continuously monitor news sources, social media feeds, and other open-source intelligence channels in real time, alerting analysts to relevant developments as they happen. Sifting through massive datasets from diverse sources that include both open-source and classified reporting will allow analysts to quickly dismiss the “noise” and more easily discover relevant information that might otherwise be missed by human-driven analysis. Tedious and repetitive tasks, like report generation or data cleaning, can be automated, increasing efficiency and allowing analysts to focus their time and efforts on critical strategic analysis.

Furthermore, algorithms will unearth subtle trends, correlations, and anomalies that traditional analytical methods often overlook. This enhanced capability will empower proactive decision-making based on insights that would have otherwise remained hidden. Algorithms can help identify and mitigate potential biases in human analysis, promoting more objective decision-making processes. AI tools can act as a “smart assistant,” highlighting relevant information, providing summaries, and offering different perspectives to enhance human analysis. This frees up analysts from mundane information-gathering tasks and allows them to focus on higher-order strategic thinking.

Expanding further, the advanced collection and analytical features of AI will greatly assist with gauging potential instability in regions of interest, analyzing competitor activities, patent filings, and market trends, which can be streamlined with AI to quickly identify threats and opportunities. AI can analyze network traffic to detect anomalies indicative of potential cyberattacks, allowing for a faster response to cybersecurity threat detection.

The capabilities of generating and analyzing various potential scenarios based on historical data and current trends, in a fraction of the time needed for humans, provides analysts with a more comprehensive analysis for decision-makers to assess the likelihood of different outcomes and a higher confidence in predicting and understanding the consequences of their decisions. The AI-powered predictive analytical forecasting potential of geopolitical events, economic shifts, or emerging technologies that might create future strategic risks or opportunities for governments is attractive to all states as they leverage advantages to expand influence and power.

Incorporating AI capabilities into the strategic intelligence realm is not without its challenges or concerns. It will be imperative to ensure meaningful human control over any AI systems associated with strategic intelligence. Other national security assets should be considered a high priority at this critical onset of AI applications focused on the establishment of safeguards against autonomous decisions.

Considering AI relies on the accuracy and completeness of data, ensuring effective measures are in place to maintain data integrity and avoid garbage-in, garbage-out scenarios is critical. It is vital that AI models are interpretable so that analysts can understand the reasoning behind recommendations. This builds trust and facilitates better decision-making. Addressing biases in AI models and ensuring algorithms are used in a transparent and responsible manner that aligns with organizational values is also important.

Advancing AI may process vast amounts of data in times of crisis, and do it far faster than humans, though there is understandable concern about the appropriate level of AI involvement in high-stakes decisions where time is of the essence. For example, should AI have any control over nuclear launch decisions, and if so, how much? Errors in AI analysis or reliance on faulty data could lead to miscalculations and unintended escalation.

As intelligence agencies increasingly rely on advanced technologies like AI, there is a need for robust regulation and oversight to prevent abuse of power, misuse of data, and violations of civil liberties. Policies should establish clear guidelines for the collection, storage, and use of intelligence data, as well as mechanisms for accountability and transparency.

The proliferation of intelligence data and the use of advanced analytics pose challenges related to data security and protection. Policies must address issues such as data encryption, secure storage, access controls, and measures to safeguard against cyber threats and breaches.

Given the global nature of many intelligence threats, there is a need for international cooperation and the development of norms and standards governing the use of AI technologies. Policies should promote collaboration among intelligence agencies from different countries while respecting sovereignty and legal frameworks.

AI algorithms used in intelligence operations may exhibit bias or produce unfair outcomes, particularly if trained on biased data or programmed with flawed assumptions. Policies should address these concerns through measures such as algorithmic transparency, fairness assessments, and diversity in data sources and large language model (LLM) development.

The development and deployment of AI technologies can confer strategic advantages to nations or organizations. Policies may need to balance the pursuit of such advantages with efforts to prevent destabilizing arms races or conflicts arising from the use of intelligence capabilities.

The use of AI capabilities, particularly in areas such as cyber warfare or information operations, can raise the risk of deterrence failures or unintended escalation. Policies should seek to establish clear deterrence strategies, rules of engagement, and mechanisms for de-escalation to mitigate these risks. As AI technologies become more sophisticated, intelligence operations will increasingly involve human-machine collaboration. Policies should address issues such as human oversight, accountability for algorithmic decisions, and the ethical implications of human-AI interaction in intelligence activities.

The future of AI and strategic intelligence operations is poised to be characterized by continued innovation, integration, and adaptation to evolving geopolitical, technological, and societal landscapes. Further breakthroughs in AI technologies, including deep learning, natural language processing, and reinforcement learning, will enable intelligence agencies to extract deeper insights from vast and diverse datasets. This will enhance capabilities for predictive analysis, anomaly detection, and decision support across a wide range of intelligence operations.

The integration of AI into autonomous systems, such as unmanned aerial vehicles (UAVs) and unmanned underwater vehicles (UUVs), will certainly revolutionize intelligence, surveillance, and reconnaissance (ISR) capabilities. These systems will be capable of operating in contested or denied environments with reduced risk to human operators and logistical support assets.

The proliferation of cyber threats and the increasing reliance on information warfare tactics will drive the expansion of cyberintelligence capabilities. Intelligence agencies will focus on detecting, attributing, and mitigating cyberattacks, as well as leveraging information operations to shape narratives and influence adversaries.

The rise of social media platforms and digital communication channels will continue to reshape intelligence gathering and analysis. Open-source intelligence (OSINT) and social media analysis techniques will play an increasingly prominent role in monitoring global events, assessing public sentiment, and identifying emerging threats. Intelligence agencies will increasingly collaborate with other government agencies, international partners, and private-sector entities to leverage complementary expertise and resources. Fusion centers will facilitate the integration of intelligence from multiple sources to produce more comprehensive and timely assessments.

Intelligence agencies will need to enhance their resilience and adaptability to rapidly evolving threats, including emerging technologies, geopolitical shifts, and unconventional adversaries. This will require agile organizational structures, flexible operational frameworks, and continuous investment in training and capabilities development.

Overall, the future of AI and strategic intelligence operations will be characterized by a dynamic interplay between technological innovation, geopolitical dynamics, and societal trends. By embracing these trends and addressing associated challenges, intelligence agencies can enhance their effectiveness in safeguarding national security and advancing strategic objectives in an increasingly complex and interconnected world.

As the United States intelligence community navigates the complexities of an increasingly interconnected and unpredictable world, the future of strategic intelligence operations will be defined by our ability to harness the power of AI technologies while mitigating their risks and ensuring their responsible and ethical use. By embracing innovation, fostering collaboration, and upholding democratic values, intelligence agencies can effectively confront the challenges of the 21st century and advance the interests of peace, security, and prosperity for all.

Joshua Thibert is a Contributing Senior Analyst at the National Institute for Deterrence Studies (NIDS). With over 30 years of comprehensive expertise, his background encompasses roles as a former counterintelligence special agent within the Department of Defense and as a practitioner in compliance, security, and risk management in the private sector. The views expressed in this article are his own.  

Unveiling the Future: The Convergence of AI and Strategic Intelligence Operations was originally published on Global Security Review.