The conclusion frames AI as the organizing principle for future campaigns, warning of governance and accountability failures and calling for doctrine-driven PME, integrated governance, and a two-front AI strategy for India against PLA and CENTAIC-linked capabilities.

Operational case studies like Operations Epic Fury and Roaring Lion show AI aiding targeting, multi-domain integration, and real-time decision support, with tools such as Palantir’s Maven and Israel’s Tashan and ROM/BINA systems illustrating practical deployments.

The article includes a detailed set of notes and references linking to sources and official statements, underscoring a research-based, defense-policy oriented tone.

It highlights the Russia–Ukraine war as a case of scale AI use for battlefield analytics, targeting, cyber defense, and disinformation, while drawing attention to governance and accountability gaps.

Tracing AI’s evolution in warfare from concepts like the OODA loop and network-centric warfare to modern decision-centric, AI-enabled operations, and noting milestones such as Project Maven and autonomous systems developments by major powers.

The piece identifies AI-induced challenges: governance gaps, automation bias and impracticality of exhaustive human review, opaque decision pathways from neural networks, and accountability issues in autonomous targeting.

It assesses India’s AI-warfare readiness—DAIC, DAIPA, IDEX, ETAI—and outlines three structural gaps: technology sovereignty, inter-service fragmentation, and procurement cadence, advocating a sovereign AI approach and a tri-service fusion framework.

Leadership imperatives include enforcing binding two-step human authorization, defining doctrine and engagement rules for autonomous AI, redesigning PME to foster critical questioning of AI outputs, and ensuring all‑of‑government coordination to mitigate vulnerabilities and governance blind spots.