Defense has always evolved alongside technology. Every few decades, a new class of tools arrives that changes how nations detect threats, coordinate responses, and protect their people. The Chain Home radar network gave operators crucial time to react to aerial threats during the Battle of Britain. GPS satellites, born from Cold War tracking programs, allowed forces to coordinate with precision across vast distances. Code-breaking machines at Bletchley Park unlocked the ability to understand an adversary's plans before they were carried out. Each of these shifted what was possible, and reshaped how nations think about security and defense.

AI follows this same pattern, though what sets it apart from earlier technologies is the scale at which it operates.

The advantage AI has over technologies like radar is the scale that it operates on. Rather than monitoring a single domain, AI can simultaneously process feeds from hundreds of satellites, drones, radar arrays, and signals intelligence sources, compressing what used to take hours of human analysis into seconds. Where GPS pinpointed a location, AI compresses entire decision cycles from hours down to seconds. And unlike static technologies, AI systems learn and adapt over time. That combination of breadth, speed, and adaptability has driven global defense spending on AI from an estimated $9.3 billion in 2024 toward projections of $19 to $35 billion by 2030 to 2031 [1]. The investment reflects a structural shift in how defense capability is built and maintained.

Integrated Command and Control

Modern defense operations increasingly depend on the ability to process and act on information rapidly across multiple domains. AI addresses this directly, replacing isolated, disconnected systems with integrated architectures that give a comprehensive view of operations in real time.

One of the most significant developments in this space is Joint All-Domain Command and Control, or JADC2. It connects sensor data from across all military branches, meaning the army, navy, air force, and space and cyber commands, into a single network, giving a full picture of what is happening rather than dealing with separate, disconnected feeds. AI processes data from multiple sensors at once, makes intelligence summaries easier to access across different command levels, and flags unusual activity before it turns into a larger problem. For example, instead of an analyst manually cross-referencing a radar contact with satellite imagery and communications intercepts, an AI system can correlate all of that data instantly and alert the relevant decision maker before the situation develops further.

Nations and alliances across the world are developing integrated command architectures, each through their own programs but working toward the same goal. The United States is advancing through the Air Force's Advanced Battle Management System, the Army's Project Convergence, and the Navy's Project Overmatch. NATO's Allied Command Transformation has its own AI-assisted decision-making system that processes data continuously from legacy infrastructure across member states. The EU's Permanent Structured Cooperation framework has funded over 75 joint defense projects, including EUMILCOM, a prototype European command platform designed to be interoperable with NATO systems. The UK's Digital Targeting Web, backed by over £1 billion from the 2025 Strategic Defence Review [2], connects sensors, decision-makers, and response systems across domains. Japan's SAMURAI initiative develops runtime assurance frameworks, which are systems that monitor and enforce the safety and performance of AI software during live operation, for AI-powered unmanned systems alongside next-generation aircraft programs. India is advancing Integrated Theatre Commands with AI-assisted coordination at its center.

Deterrence works when the ability to detect and respond to threats is clear and credible. AI strengthens both, giving defense systems the speed and awareness needed to respond before situations escalate.

Satellite Intelligence and Counter-Drone Defense

Knowing what is happening on the ground, before it becomes a crisis, has always been a core function of defense. AI has meaningfully upgraded this capability by automating the analysis of satellite imagery and sensor data at a scale that human analysts simply cannot match alone.

Planet Labs operates a constellation of more than 600 satellites that image every point on Earth daily. Their AI analytics can reduce raw data volume by 80% through edge computing which processes data closer to the source rather than in a centralized cloud, and deliver automated change-detection alerts in under an hour [3]. Their Aircraft Detection Analytic Feed automatically identifies military aircraft across global airfields without requiring an analyst to manually review each image. Maxar Technologies, whose 30cm-resolution imagery supplies foundational geospatial intelligence for much of the Western defense community, provided the satellite data that documented troop buildups near Ukraine with enough detail to enable early diplomatic responses.

At a multilateral level, NATO's Alliance Persistent Surveillance from Space program, a $1 billion five-year initiative involving 17 member nations [4], integrates government and commercial satellite resources into a shared intelligence picture. The EU has invested in the AI4COPSEC project, which applies self-supervised deep learning, a method where a model learns patterns from automatically labeled data rather than manually annotated datasets, to maritime monitoring through the Copernicus satellite program.

Computer vision which is a field of artificial intelligence that enables computers to "see" and interpret digital images or videos, is also being applied to counter-drone defense, one of the most pressing situational challenges of the current decade. The scale of drone attacks has grown considerably, with incidents involving hundreds or even thousands of units at once now on record across multiple regions. Responding to these with conventional interceptor missiles, which cost tens of thousands per shot, is not economically viable at that volume. AI-powered systems address this by classifying drone threats automatically and recommending the appropriate response quickly enough, without human analysts having to review each track manually.

France's Thales unveiled its SkyDefender system in early 2026, an integrated air and missile defense platform that combines geostationary early-warning satellites, infrared sensors capable of detecting launches before ground radar range, and 360-degree radar coverage up to 350km. The system uses AI to correlate data across all these sensors and recommend layered responses. The UK awarded MBDA a £316 million contract for DragonFire [5], a directed-energy laser weapon for Royal Navy destroyers operational from 2027, which intercepts drones at roughly £10 per shot compared to tens of thousands for conventional missiles. Italy's Leonardo developed ORCUS, an AI-powered counter-drone system deployed at UK airports and for events including the G7 summits and the Paris Olympics. In India, Grene Robotics' Indrajaal system provides autonomous wide-area coverage across 4,000 square kilometers, designed specifically to protect critical national infrastructure including nuclear facilities and power grids. NATO has formalized this as a collective priority through its Layered Counter-UAS Initiative, a flagship program for 2026, with annual multinational exercises now involving more than 20 nations and 50 industry partners.

In each of these cases, AI is a tool for improving human awareness and response time, not for replacing the judgment of the people using it.

AI in Cyber Defense, Autonomous Systems and Supply Chain Security

Defense resilience is not only about physical threats. It is about ensuring that defense systems can withstand shocks, whether cyberattacks, supply chain disruptions, or large-scale drone incidents, and continue to function effectively.

Cyberattacks on defense infrastructure have grown sharply in both frequency and sophistication. In 2025 alone, the UK's National Cyber Security Centre logged 204 nationally significant cyber incidents, more than double the prior year's figure [6]. With over 159 actively exploited vulnerabilities recorded in just the first quarter of 2025, and most being actively used against systems within a day of discovery [7], traditional defenses that rely on fixed rules are too slow to respond effectively.

AI-driven cyber defense addresses this by moving away from static signatures toward behavioral pattern recognition. UK-founded Darktrace, developed with roots in the signals intelligence community, which involves gathering and analyzing electronic signals for intelligence purposes, takes a different approach to cyber defense. Rather than relying on a fixed set of rules about what an attack looks like, its system continuously learns what normal activity looks like across a network and flags anything that deviates from that baseline. This means it can detect threats that have never been seen before, not just the ones that security teams have already anticipated. Its AI triage capability reduces the time analysts spend reviewing and responding to alerts by over 90% [8], allowing security teams to focus on the incidents that actually require human attention. Leonardo has operated NATO's cyber defense infrastructure since 2012, with a team of around 200 specialists protecting 75 sites across 29 countries around the clock [9]. Australia's REDSPICE program, the Australian Signals Directorate's largest-ever investment, is designed to significantly expand the country's ability to detect and respond to cyber threats across its defense networks, with AI playing a central role in identifying intrusions faster than human analysts could manage alone.

Beyond cyberspace, AI is also strengthening resilience through autonomous systems that extend reach into environments too hazardous for human crews. Australia's Ghost Shark autonomous underwater vehicle, developed in partnership with Anduril, is designed for persistent maritime surveillance with a multi-thousand-mile range. First deliveries began in January 2026. The system uses Anduril's Lattice AI platform to process sensor data onboard and make navigation decisions without constant human input. The UK Royal Navy took delivery of an end-to-end autonomous mine-hunting system developed by Thales under a Franco-British program, using AI-powered automatic target recognition. The Royal Navy is also converting vessels into motherships for autonomous underwater drones, supported by contracts for remote command centers capable of controlling these systems globally.

Supply chain security has become an equally important dimension of defense resilience. AI systems that analyze vendor relationships, ownership structures, and material sourcing can flag dependency risks that manual audits would miss entirely. The U.S. Defense Logistics Agency used an AI-powered supplier risk assessment system to identify 19,000 high-risk vendors from a pool of 43,000, and found that more than 90% of materials in shortfall had zero or one domestic supplier, a vulnerability that is difficult to see without AI-powered analysis across the full supplier base [10].

Building Trustworthy and Responsible AI

As AI adoption in defense has accelerated, the work of building governance frameworks around it has followed closely behind. Across multiple institutions and regions, there is an ongoing effort to establish clear principles for how AI should be developed, tested, and used in security contexts.

NATO revised its AI strategy in July 2024 around six principles: lawfulness, responsibility, explainability, reliability, governability, and bias mitigation. The alliance also established a testing and validation landscape to help member nations assess AI systems before operational deployment. The EU's European Defence Agency published a 107-page framework in May 2025 [11] on trustworthy AI for defense, introducing mandatory impact analysis requirements and human-centric design standards specific to defense applications. Australia published its policy settings for responsible military AI in March 2026. The UK's Joint Service Publication 936 sets out the Ministry of Defence's requirements for AI systems across the armed forces.

At the UN level, General Assembly Resolution 79/62 passed in December 2024 with 166 votes in favor [12], endorsing a framework for regulating lethal autonomous weapons that emphasizes predictability, traceability, and human accountability. The REAIM summit process, now spanning three events across The Hague, Seoul, and A Coruña, has brought 96 countries into a common conversation about responsible military AI, with 61 endorsing a Blueprint for Action [13].

What is emerging across all of these frameworks is a consistent set of priorities. AI must remain auditable. Human operators must retain meaningful control over consequential decisions. Systems must be testable and correctable. The technical and ethical challenges of AI in defense are intrinsically linked.

Where This Is Headed

Defense has always been shaped by technologies that allow nations and alliances to protect people, deter threats, and respond to crises more effectively. Radar, GPS, and satellite imaging each expanded the boundaries of what was possible in defense, and AI continues that progression, not by replacing human judgment but by giving the people behind those decisions greater awareness and faster access to the information they need.

The technical work happening today across command networks, counter-drone systems, maritime autonomy, and cyber defense is shaping what AI-enabled defense will look like for years to come. Getting that right means addressing not just the engineering challenges but also the governance questions that come with deploying AI in high-stakes environments.

At Rootcode, we help organizations and governments navigate complex technology challenges, including the integration of AI into defense and high-stakes systems. If you are looking to explore what AI can do for your operations, our engineering and AI teams are ready to help. Get in touch with us today.