Artificial Intelligence in Modern Warfare: AI’s Role, Challenges and India

Context

The strategic-military landscape is undergoing a transformative shift, with Artificial Intelligence (AI), military autonomy and algorithmic warfare redefining the nature of modern warfare.

How is AI Reshaping Modern Warfare?

• AI-Enabled Battlefield Awareness: AI integrates data from satellites, drones, sensors and intelligence networks to generate a common operational picture, enabling commanders to assess threats and coordinate operations in real time.
  • g. The U.S. Project Maven employs AI to process drone imagery for intelligence and target identification.
• Machine-Speed Targeting: AI-powered kill webs connect sensors, command centres and weapon systems, reducing the time between target detection and engagement.
  • g. The U.S. Joint All-Domain Command and Control (JADC2) initiative links assets across land, sea, air, space and cyber for rapid targeting.
• Drone-Centric Warfare: Unmanned systems have become indispensable for intelligence, surveillance, reconnaissance (ISR), precision strikes, logistics support and damage assessment, lowering operational risks to troops.
  • g. The Russia–Ukraine War has demonstrated the large-scale use of FPV drones for reconnaissance and precision attacks.
• Autonomous Warfare: AI-enabled autonomous platforms can independently navigate, detect and engage targets with minimal human intervention, expanding the role of machines in combat operations.
  • g. Israel’s Harpy loitering munition autonomously detects and destroys enemy radar installations.
• Startup-Driven Defence Innovation: Defence innovation is increasingly being led by agile technology startups developing AI, autonomous systems and advanced military software in partnership with conventional defence industries.
  • g.Anduril Industries has developed the AI-enabled Lattice platform for autonomous surveillance and battlefield command and control.

What are the Key Challenges for India in Modern AI Warfare?

• Lack of an Integrated AI Battlefield Network: India lacks a unified AI-enabled command-and-control architecture capable of integrating data from land, air, sea, space and cyber domains into a single operational picture.
  • g. Projects such as Project Sanjay and the Combat Information Decision Support System (CIDSS) are under development, but India still lacks an integrated multi-domain battlefield network comparable to advanced militaries.
• Limited AI Integration in Military Operations: AI-driven decision support, predictive analytics, autonomous systems and human-machine teaming remain at an early stage of operational deployment.
  • g. The Army AI Incubation Centre is fostering AI innovation, but large-scale integration across the Army, Navy and Air Force remains limited.
• Limited Persistent Space-Based ISR Capabilities: India lacks sufficient Low Earth Orbit (LEO) satellite coverage for continuous intelligence, surveillance and reconnaissance (ISR), constraining real-time situational awareness.
• Interoperability and Software Integration Constraints: AI integration is hindered by the diverse mix of foreign and indigenous military platforms operating on incompatible software architectures.
  • g. Integrating Russian, French, American and indigenous platforms into a unified AI-enabled command network remains difficult due to proprietary and closed software systems.
• Slow Defence Procurement and Institutional Reforms: Defence acquisition and organisational processes have struggled to keep pace with the rapid advancement of AI, software and autonomous technologies.
  • g. Despite reforms under the Defence Acquisition Procedure (DAP) and iDEX, procurement and induction cycles remain significantly slower than commercial technology innovation.

Way Forward

• Develop an Indigenous AI Battlefield Network: Build an integrated AI-enabled command-and-control platform that fuses real-time data from land, air, sea, space and cyber domains for faster decision-making.
  • g. Develop an indigenous battlefield management system on the lines of Ukraine’s Delta, adapted to India’s multi-front operational environment.
• Advance Autonomous Drone Warfare: Develop indigenous AI software for autonomous drone swarms capable of collaborative navigation, target recognition and mission execution with human oversight.
  • g. Scale up swarm technologies under iDEX and Army Design Bureau initiatives.
• Scale Indigenous Drone Production: Create a robust domestic drone manufacturing ecosystem to ensure affordable, mass deployment during high-intensity conflicts.
  • g. Expand production through the Production Linked Incentive (PLI) scheme and private defence startups.
• Expand Space-Based ISR: Increase the number of Low Earth Orbit (LEO) satellites to enable persistent intelligence, surveillance and reconnaissance across multiple theatres.
  • g. Fast-track the Space-Based Surveillance (SBS-III) programme with greater participation from private space companies.
• Prioritise Software-Centric Defence Modernisation: Shift defence investment from hardware-centric procurement towards AI, software, cloud computing, cybersecurity and advanced data analytics.
  • g. Allocate a dedicated share of the defence modernisation budget for AI and digital warfare technologies.

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