Introduction
War has evolved rapidly with technology. In the twenty-first century, we are seeing a change in the velocity of war not merely by automating military tasks but by compressing the decision-making process, data analysis, and intelligence gathering, and enabling lethal action at machine speed. Recent conflicts such as the Russia-Ukraine war demonstrated operational deployment through drone swarms and predictive targeting and reduced the sensor-to-shooter cycle by moving from detection to engagement in minimal time. It showed that AI has now become a decisive force multiplier across five major domains; intelligence and surveillance, autonomous systems, logistics, cyber defence, and command and control systems.
Countries such as the US and China are also investing heavily in AI integration in military, ISR systems and strategic decision support systems. For India, AI showcases both opportunity and strategic necessity as it is surrounded by a complex security environment involving an active northern border, maritime competition in the Indo-Pacific region, and increasing hybrid and grey zone threats. Over the past decade, India has accepted the reality and begun establishing institutional frameworks, defence innovation ecosystems, and indigenous defence capabilities aimed at integrating AI into military planning and operations.
India’s AI development ecosystem
Operation Sindoor provided a significant validation for the concepts and operational plans of the army’s AI adoption. Lt. Gen. Rajiv Kumar Sahni, DG EME, said in a briefing that “AI was extensively used for the multi-sensor data fusion and multi-source data fusion in real time during Operation Sindoor. Overall, 23 apps with specific tasks were used to deal with data and inputs.” These included the Electronic Intelligence Coalition and Analysis System (ECAS) to identify and prioritise threats, weather forecasting tools, and predictive modelling. The Trinetra system with Project Sanjay offered a unified operational picture, improving coordination and situational awareness.
India’s formal engagement with defence AI traces back to February 2018, when the Department of Defence Production constituted a task force for “Strategic Implementation of AI for National Security and Defence” under the chairmanship of Shri N. Chandrasekaran, Chairman, TATA Sons. Based on recommendations, in 2019, the government established the Defence AI Council (DAIC) and the Defence AI Project Agency (DAIPA) to guide policy and accelerate the execution across the armed forces. The institutional architecture reflects that AI adoption requires coordination amongst government, military, industry, and academia.
The Defence Research and Development Organisation (DRDO) is a technical core, specifically its Centre for Artificial Intelligence and Robotics (CAIR), which works on missions involving applications of robotics, command and control systems, autonomous navigation, and secure battlefield communications. It, alongside the DRDO Young Scientists Laboratory (DYSL)-AI, has developed over 75 AI-based defence products ranging from AI automation platforms to cybersecurity and surveillance systems. In 2022, the Ministry of Defence showcased C4ISR solutions, unmanned robotic systems, AI-based intrusion detection, and voice analysis systems at the AI in Defence (AIdef) Symposium and Exhibition. In October 2024, Chief of Defence Staff General Anil Chauhan and DRDO Chairman Dr. Samir V. Kamat launched the Evaluating Trustworthy AI (ETAI) Framework and Guidelines for the Armed Forces. It highlighted that AI applications must be reliable, safe, secure, transparent, and fair, which makes it notably ahead of equivalent governance structures in the US and China. Simultaneously, India has promoted defence innovation through the Innovations for Defence Excellence (iDEX) framework, which connects start-ups, MSMEs, academic institutions, and the armed forces. The Indian Army’s AI Incubation Centre was established with Bharat Electronics Limited (BEL) to operationalise indigenous innovation, including voice transcription tools, drone analytics and predictive maintenance. The government has also earmarked ₹100 crore annually for armed forces AI projects. India is also boosting its defence capabilities with a new Rs 300 crore Centre of Excellence for artificial intelligence like SarvamAI, SAMA (Situational Awareness Module for the Army), and others to reduce reliance on foreign technology and enhance national security. This institutional ecosystem shows India’s broader strategic objective of technological self-reliance under the Atmanirbhar Bharat (Self-reliant India) framework.
AI Applications in Indian Warfighting
India’s military adoption of AI is currently concentrated in four principal operational domains: Intelligence, Surveillance, and Reconnaissance (ISR); autonomous and unmanned systems; logistics and predictive maintenance; and cyber and electronic warfare. In ISR, platforms like Project SANJAY and SAMA are complemented by DRDO’s AESA radar imaging systems and ML models fed by civilian satellites such as GISAT for terrain and troop movement analysis. The National Centre for Geo-Informatics further collaborates on AI-driven border monitoring. In the autonomous and unmanned domain, the Army and Navy are integrating autonomous systems ranging from loitering munitions, including the Nirbhay cruise missile and the stealth UCAV AURA (Ghatak), with AI guidance to semi-autonomous UGVs like the “Muntra” mine-clearance vehicle, which uses obstacle avoidance algorithms for operations in contested terrain. Project SAVIOR by the Navy is evolving to develop autonomous anti-submarine warfare vessels, and CASCADE-ASW crafts are in Make-II trials. On the logistics and predictive maintenance front, AI systems analyse historical operational data to forecast equipment failures, optimise spare parts, and reduce platform downtime across diverse theatres. In Jan 2026, the Indian Army shared the update: “The Indian Army has launched Depot Integration Management Edition (DIME), a pan-Army digital platform that delivers real-time visibility of logistic items from units to Army Headquarters, transforming Army logistics,” which is developed jointly by the Indian Army and Bhaskaracharya National Institute for Space Applications and Geo-informatics (BISAG-N). Lastly, in cyber and electronic warfare, AI systems such as CERT’s intel threat use ML and are deployed to detect anomalous network behaviour, identify malware, and enable adaptive responses to electronic threats. However, such cyber-AI fusion efforts are mostly classified.
Challenges
Despite significant progress, India’s defence AI ecosystem faces structural and operational challenges. The most critical gap is the absence of a unified inter-service data platform, as the Joint All-Domain Command and Control (JADC2) capability does not exist yet in the Indian military. Another constraint is computing power at the tactical edge. The AI model requires substantial processing, and getting the capabilities to forward-deployed units, rather than relying on rear-echelon cloud systems potentially vulnerable to adversary interdictions. India’s dependency on foreign technology in these critical areas creates strategic vulnerabilities. India also occupies an ambiguous position on Lethal Autonomous Weapons Systems (LAWS). It raises questions regarding accountability, escalation control, and the “human-in-the-loop” principle over lethal decisions. India’s challenge is, however, no longer conceptual acceptance of AI but scaling innovation into deployable military capabilities.
Way Forward
India must adopt a long-term and integrated approach to emerge as a credible AI-enabled military power. The ETAI framework must move from a governance document to a deployed certification mechanism. Most importantly, a Joint AI Command or equivalent inter-service data sharing platforms must be established.
India’s genuine advantage is its talent base. The DRDO Young Scientists Laboratories and the iDEX pipeline feed a defence tech startup ecosystem that nations having state-directed models cannot replicate easily. Partnerships with the US (iCET framework), Israel, and France should be focused towards AI hardware co-development, not just on system procurements. Investments in semiconductor capability, edge computing, and secure defence cloud infrastructure must be accompanied by software innovations. India should define a clear doctrinal position, not only to appease multilateral forums but also to set internal red lines before the technology races advance ahead of accountability.
Conclusion
India’s approach to AI in warfare is ambitious but evolving. It has gone from task forces and symposiums to real-time battlefield deployment in under seven years. The ECAS system, Anuman 2.0 (weather forecasting system), Trinetra, and drone swarm acquisition show that the doctrines are in practice. Nonetheless, many advanced capabilities remain under development or classified. Continued focus on secure data, indigenisation, and ethical frameworks will remain crucial. India has an ecosystem, the strategic motivation, and also the operational experience. The question is whether institutional reform can keep pace with evolving technology.
