India's military leadership is sounding an alarm about the nation's AI warfare readiness, warning that without rapid integration of artificial intelligence into defense systems, the country risks falling behind China's People's Liberation Army (PLA) and Pakistan's military capabilities. The strategic imperative is clear: as adversaries systematically weaponize AI for autonomous drones, real-time targeting, and command-and-control systems, India must accelerate its own AI-warfare program while establishing governance frameworks that keep humans meaningfully in control of lethal decisions.

Why Is AI Becoming Central to Modern Military Strategy?

The evolution of AI in warfare accelerated dramatically after the 1991 Gulf War, when satellite-enabled information sharing demonstrated the military advantage of networked decision-making. The United States developed what strategists call Decision Centric Warfare (DCW), integrating AI and unmanned systems to compress the time between detecting a target and authorizing a strike. Project Maven, launched in 2017, operationalized deep-learning computer vision to detect and classify objects in surveillance video at machine speed, reducing what once took hours to minutes.

The Russia-Ukraine War became the first major conflict where both sides systematically deployed AI for military purposes. Ukraine used AI for battlefield facial recognition, signals analysis, and cyber defenses. Russia fielded AI-enabled loitering munitions (essentially autonomous drones that can hunt targets), automated targeting systems, and generative AI for disinformation campaigns at industrial scale. The conflict exposed a critical vulnerability: neither side had resolved the governance questions of who is accountable when AI systems make targeting decisions.

During the recent Israel-Iran military operations, AI systems demonstrated both extraordinary capability and troubling opacity. Israel's "Tashan" system identified Iranian ballistic-missile launch points in real time, enabling counter-battery strikes before launchers could relocate. The "Bina" Unit generated situational assessments, including civilian-casualty risk estimates. Yet a U.S. missile strike on a girls' school in Minab, Iran, killed more than 175 civilians, predominantly children, attributed to outdated mapping data. The Maven Smart System generates 3,000 targeting options daily, rendering meaningful human review nearly impractical due to what researchers call "automation bias," where the human in the approval chain becomes just a procedural formality.

What Governance Challenges Does Military AI Present?

The central problem is structural: AI has outpaced every governance mechanism designed to keep humans in meaningful control. AI targeting recommendations, unlike conventional intelligence assessments, are embedded in billions of opaque parameters that even developers cannot fully explain. Anthropic's chief executive acknowledged he could not guarantee the reliability of his systems and was designated a "supply chain risk" by the Pentagon for this unpredictability and black-box behavior. Yet Claude, Anthropic's AI model, continued to operate within Maven on classified military networks despite the company's refusal to remove ethical guardrails.

The Anthropic-Pentagon dispute exposed a governance void. No legal or institutional framework existed to determine accountability for the outcome. Additionally, AI misalignment, the divergence between AI behavior and human intent arising from biased training data or distributional shift, poses escalating risks. Technologies perfected by one nation can be adapted and weaponized against it.

How Can Military Leaders Establish Effective AI Governance?

• Structured Human Authorization: No AI-generated targeting recommendation should proceed to engagement without a two-step human authorization process. Approval interfaces must not be ceremonial; they should be binding standards that enforce genuine human deliberation.
• Doctrine and Rules of Engagement: Military doctrine must specify where AI may autonomously generate targets, where human deliberation is mandatory, and what categories of targets are categorically excluded from AI-only recommendations. Operational tempo must not be permitted to override oversight architecture.
• Professional Military Education: Future leaders must be trained to synthesize technology with judgment at far greater speed and under escalatory pressure. PME must cultivate the habit of questioning AI outputs and demanding multiple analytical perspectives before decisions are taken.

"Speed divorced from scrutiny is institutionalized recklessness. Leadership must treat oversight architecture as a prerequisite to capability expansion," stated Air Vice Marshal Prashant Mohan VSM (Retd), an expert on AI in military operations.

Air Vice Marshal Prashant Mohan VSM (Retd), Author on AI in Warfare

The U.S. Department of Defense's January 2026 AI Acceleration Strategy mandates a "wartime approach" to transform the force into an "AI-first" organization. This illustrates both ambition and risk: private-sector integration at scale amplifies capability but multiplies the dependencies and failure modes that adversaries can exploit.

What Is India's Current AI-Warfare Position?

India's strategic environment demands urgent yet rigorous integration of AI into warfare. The People's Liberation Army has structured its entire modernization trajectory around AI integration. Major Chinese technology companies, including Baidu, Alibaba, and Tencent, are systematically co-opted for military AI development. Pakistan's Centre of Artificial Intelligence and Computing (CENTAIC) is transferring AI capabilities to Pakistan's military. During Operation Sindoor, Pakistan appeared to receive real-time satellite intelligence and AI-backed targeting support through this channel.

India thus confronts a two-front AI challenge. While India's AI-warfare program has achieved tangible operational capabilities, the pace of adversarial advancement creates a window of vulnerability. The nation must accelerate integration while simultaneously building the governance frameworks, professional military education, and ethical guardrails that prevent the accountability gaps witnessed in recent conflicts. Without this dual approach, India risks acquiring powerful AI capabilities without the institutional maturity to control them responsibly.

The stakes extend beyond military effectiveness. As military AI systems become more autonomous and opaque, the risk of escalation, civilian harm, and uncontrollable conflict increases. India's military leadership must prioritize governance and doctrine alongside capability development, ensuring that AI serves human strategic intent rather than replacing it.