AI Warfare Explained: How India Can Keep Pace in the Age of Algorithmic Combat

Modern warfare shift: The report argues that war is moving from platform-centred combat to software-centred, sensor-rich and algorithm-driven combat. Earlier, military power was mainly measured through tanks, aircraft, ships, artillery and troops. Now, the ability to collect data, process it quickly and connect sensors with shooters is becoming equally important.

Indian concern: India faces two technologically capable adversaries and a complex security environment across land borders, the Indian Ocean, airspace, cyberspace and space. Therefore, India cannot treat AI warfare as a distant future issue.

UPSC relevance: This topic is important for GS3 under defence technology, cyber security, internal security, military modernisation, indigenisation, drones, space technology and ethical use of emerging technologies.

Basic meaning: AI warfare means the use of artificial intelligence for military functions such as surveillance, target recognition, decision support, logistics, cyber defence, autonomous navigation, electronic warfare and battlefield planning.

Not only robots: AI warfare does not only mean killer robots. It can include AI tools that detect enemy drones, classify satellite images, predict equipment failure, plan routes, analyse intercepted signals, identify cyberattacks or support commanders.

Decision-cycle advantage: The main military value of AI is speed. A force that can observe, understand, decide and act faster than the adversary can gain battlefield advantage.

Meaning: Algorithmic warfare means the use of algorithms to process battlefield data and support military decisions.

Simple explanation: An algorithm is a set of instructions used by a computer to solve a problem. In war, algorithms can help identify patterns, detect targets, prioritise threats and recommend actions.

Example: If thousands of drone images arrive every hour, humans cannot manually examine all of them quickly. AI algorithms can flag possible tanks, artillery positions, supply trucks or troop movement.

UPSC trigger: The term connects science and technology with national security, cyber warfare, data governance, ethics and accountability.

Meaning: Military autonomy refers to systems that can perform tasks with limited human intervention after being activated.

Different levels: Autonomy can be low-level, such as auto-pilot navigation, or high-level, such as target selection and engagement. The higher the autonomy in lethal decisions, the greater the legal and ethical concern.

Human control: The most important debate is whether humans must remain meaningfully involved in decisions involving use of lethal force.

International law angle: The International Committee of the Red Cross has warned that autonomous weapon systems raise humanitarian, legal and ethical questions and that clearer rules are needed to protect International Humanitarian Law.

Battlefield laboratory: The Russia-Ukraine war has shown how drones, sensors, artillery, cyber tools, commercial satellites and battlefield software can be integrated in real time.

Delta system: Ukraine’s Ministry of Defence says battlefield datasets are being used to train AI models for unmanned systems and that data is used to automatically identify ground and aerial targets in the DELTA system.

Kill web logic: The newspaper report describes how systems such as Delta fuse multiple inputs and connect them with drones and other shooters, reducing the time between detection and strike.

Lesson for India: Future conflicts may reward militaries that can rapidly combine drones, data, command networks and precision weapons.

Kill chain: A kill chain is the sequence of detecting, identifying, tracking, targeting, engaging and assessing an enemy target.

Kill web: A kill web is more flexible than a chain. It connects multiple sensors, commanders and weapons in a network. If one sensor finds a target, another system can track it and a third system can strike it.

Why it matters: Kill webs reduce dependence on a single platform. They make the battlefield faster, more distributed and harder for the enemy to disrupt.

Example: A satellite, drone, radar, electronic sensor and artillery unit can be linked through software so that targets are engaged quickly.

Low cost, high impact: Drones are cheaper than many traditional aircraft and can be used in large numbers for surveillance, strike, deception and logistics.

Risk reduction: Drones reduce risk to pilots and soldiers because they can enter dangerous zones before humans.

Mass use: Small drones, loitering munitions and kamikaze drones can overwhelm conventional defences if used in swarms.

India link: India’s recent DAC approval includes anti-UAV electronic warfare systems, jet-based kamikaze drones and naval shipborne unmanned aerial systems, indicating that drone and counter-drone capability is now central to military planning.

Autonomous combat aviation: The YFQ-44A Fury is an AI-enabled autonomous aircraft being developed by Anduril for the US Collaborative Combat Aircraft programme.

Collaborative airpower: Such aircraft are meant to operate with crewed fighters, performing tasks such as surveillance, electronic warfare, decoy missions or strike support.

Defence industry shift: The report uses this example to show that agile defence-tech start-ups are increasingly challenging traditional defence primes.

Lesson for India: India needs both public-sector defence capacity and a stronger start-up ecosystem for autonomous systems, AI software, sensors and secure military platforms.

Data sovereignty: Military AI depends on sensitive battlefield data. India cannot depend on foreign-controlled datasets or platforms for critical defence decision-making.

Software sovereignty: Imported AI systems may create security, backdoor, update-dependence and doctrinal risks.

Operational secrecy: Defence algorithms trained on Indian terrain, languages, signals, platforms and adversary patterns must remain under Indian control.

Strategic autonomy: Sovereign AI capacity supports India’s larger goal of Aatmanirbhar Bharat in defence.

Defence AI institutions: The government has set up the Defence Artificial Intelligence Council under the Raksha Mantri and the Defence AI Project Agency under the Department of Defence Production for enabling AI-based processes in defence organisations.

AI products: The Ministry of Defence launched 75 AI products and technologies during the first AI in Defence symposium, covering multiple defence domains.

Innovation ecosystem: ADITI 2.0 and DISC 12 include challenges in artificial intelligence, quantum technology, military communication, anti-drone systems, UAVs, networking and communication.

IndiaAI link: IndiaAI Mission supports national compute, indigenous foundation models, datasets and safe AI tools, which can indirectly strengthen India’s broader AI ecosystem.

Battlefield data platform: India needs an indigenous, secure and scalable battlefield management and data-fusion platform that can combine inputs from satellites, drones, radars, sensors, soldiers, naval platforms and cyber systems.

Drone ecosystem: India should develop a wide inventory of micro-drones, loitering munitions, high-altitude pseudo satellites, unmanned surface vessels, unmanned underwater vehicles and counter-drone systems.

Space layer: Low Earth Orbit satellites can improve real-time intelligence, surveillance and reconnaissance.

Cyber and electronic warfare layer: AI systems must be protected from hacking, spoofing, jamming, data poisoning and adversarial manipulation.

Speed advantage: Start-ups can design, test and upgrade software faster than traditional procurement-heavy structures.

Dual-use innovation: Many AI, drone, robotics and sensor technologies are dual-use, meaning they have both civilian and military applications.

Indian schemes: iDEX aims to foster innovation in defence and aerospace by engaging MSMEs, start-ups, innovators, R&D institutions and academia.

Challenge: Defence start-ups need assured testing ranges, procurement pathways, cybersecurity vetting, patient capital and faster acceptance procedures.

Human responsibility: If an AI-enabled weapon causes wrongful harm, responsibility must be traceable to human commanders, developers or operators.

Civilian harm: AI systems may misclassify civilians, hospitals, schools or civilian vehicles as targets if data is poor or the battlefield is unclear.

Bias and uncertainty: AI systems can fail in fog, dust, electronic interference, camouflage or unfamiliar terrain.

Escalation risk: Autonomous systems operating at machine speed may trigger escalation before human decision-makers can intervene.

UPSC point: The military advantage of AI must be balanced with International Humanitarian Law, proportionality, distinction and accountability.

Meaning: International Humanitarian Law is the law that regulates conduct during armed conflict.

Core principles: It requires distinction between combatants and civilians, proportionality in attack, military necessity and precaution to minimise civilian harm.

AI challenge: AI systems may make targeting faster, but faster decisions are not automatically lawful decisions.

Global debate: Lethal autonomous weapon systems are being discussed under the Convention on Certain Conventional Weapons framework and related UN processes.

Security risk: Foreign AI systems may be vulnerable to external control, supply disruption or hidden vulnerabilities.

Data leakage: Sensitive military data may be exposed if processed on foreign platforms.

Doctrine mismatch: Foreign models may not understand India’s geography, tactical doctrine, languages, operating conditions or rules of engagement.

Strategic dependency: Dependence on foreign AI can reduce India’s freedom of action during crisis.

Land borders: AI-enabled drones, sensors and analytics can improve surveillance across the Line of Actual Control and Line of Control.

Air defence: AI can support detection of drones, cruise missiles, loitering munitions and swarm attacks.

Maritime domain: AI can analyse ship movement, submarine signatures, satellite imagery and undersea sensor data in the Indian Ocean Region.

Internal security: AI can support counter-terrorism, cyber defence and critical infrastructure protection, but it must be governed with safeguards.

Main idea: War is becoming software-defined, data-driven and increasingly autonomous.

Indian challenge: India must avoid both extremes: ignoring AI warfare or rushing into unsafe automation without doctrine, law and accountability.

Balanced answer: A good UPSC answer should combine capability building, indigenisation, ethical safeguards, human oversight, start-up innovation and international law.

Build a sovereign battlefield AI platform: India should create an indigenous, secure and tri-service data-fusion system connecting satellites, drones, radars, sensors, commanders and weapons.

Adopt human-in-the-loop doctrine: Use AI for speed and decision support, but keep meaningful human control over lethal decisions.

Accelerate drone and counter-drone ecosystems: India needs mass production of drones, loitering munitions, anti-drone EW systems, directed-energy options and trained drone-hunting teams.

Crowd the ISR layer: Low Earth Orbit satellites, high-altitude pseudo satellites, unmanned aerial systems and naval unmanned platforms should be integrated for persistent surveillance.

Reform defence procurement: Fast software upgrades, spiral development, battlefield trials and start-up procurement pathways are needed because software cycles are faster than conventional procurement cycles.

Protect AI systems from adversaries: Military AI must be hardened against cyberattacks, GPS spoofing, jamming, data poisoning and adversarial images.

Create military AI testing ranges: India needs secure testbeds for autonomous swarms, EW-contested environments, drone-on-drone combat, sensor fusion and AI-enabled command systems.

Link civil and defence AI: IndiaAI Mission, iDEX, DRDO, DPSUs, private industry, academia and start-ups must work together without compromising military secrecy.

Develop legal and ethical rules: India should frame national guidelines for military AI use, weapons review, auditability, responsibility and compliance with International Humanitarian Law.

Shape global norms: India should actively participate in UN and CCW discussions on autonomous weapons while protecting its national security interests.