India adds a 'third way' on the AI map

As AI reshapes military operations worldwide, the summit provided a platform for showcasing that AI can be harnessed for national security while maintaining ethical guardrails, transparency, and international stability. India's recent battlefield validation of

AI systems during Operation Sindoor in May 2025 places it in a unique position to contribute practical insights rather than limiting discussions to theoretical frameworks, offering real-world experience to inform global conversations.

The United States’ (US) path to AI leadership began with the Sputnik moment of 1957, when the Soviet satellite's launch catalysed the creation of Defense Advanced Research Projects Agency (Darpa) in February 1958, establishing US’ commitment to never face strategic technological surprise again. Throughout the 1960s and early 1970s, Darpa invested millions into AI laboratories at the Massachusetts Institute of Technology, Carnegie Mellon, Stanford, and Edinburgh, funding researchers with remarkable freedom under the philosophy of supporting “people, not projects”. This early investment yielded expert systems like MYCIN, speech recognition breakthroughs, and intellectual foundations for modern AI, though the field experienced major setbacks when overpromised capabilities failed to materialise and funding dried up by the early 1990s. The modern resurgence began in the 2000s with Deep Blue defeating chess champion Garry Kasparov in 1997, Darpa’s autonomous vehicle challenges between 2005 and 2007, and the Pentagon’s embrace of machine learning for practical military applications. The watershed came with the Department of Defense’s “Third Offset Strategy’’ in 2014, which recognised that AI would define the next generation of warfare, resulting in massive investment growth from $600 million in FY2016 to $1.8 billion in FY2024 across 685 active projects. Darpa’s $2 billion AI Next campaign, launched in 2018, along with subsequent programmes for trustworthy AI, adversarial defence through initiatives like Guaranteeing AI Robustness against Deception, and autonomous systems such as Rapid Experimental Missionized Autonomy, positioned the US at the forefront of military AI. Today, approximately 70 per cent of Darpa’s programmes incorporate AI, with demonstrations including AI-piloted F-16s defeating human pilots and commercial AI giants like Anthropic, Google, and OpenAI receiving $800 million in Pentagon contracts, solidifying the US’ strategy of leveraging private sector innovation for military superiority while navigating regulatory uncertainty between administrations.

China’s ascent to AI superpower status is rooted in a decades-long strategic transformation, pivoting from late-1970s academic curiosity to the 2017 “New Generation” roadmap aiming for global leadership by 2030. This journey is fuelled by a massive data advantage from 1.1 billion mobile users and a “national team” of tech giants like Baidu and Alibaba who spearhead sector-specific innovation. By 2025, China had secured nearly 50 per cent of the world's top researchers and over 500,000 new talents, driving a core industry valued at $75 billion.

Confronted by Western chip restrictions, China has pivoted towards “frugal innovation”, demonstrated by the $5.6 million DeepSeek model, emphasising computing efficiency over raw power, while the 2025 AI Plus initiative and a 1-trillion-yuan funding commitment from the Bank of China aim to achieve total technological independence and a fully AI-integrated society by 2035. China’s regulatory landscape is uniquely proactive, characterised by top-down intervention that precedes technological maturity to ensure ideological alignment, with the framework anchored in “Socialist Core Values” mandating that AI content neither subverts state power nor undermines national unity. Key legislation, such as the 2023 Generative AI Measures and the Deep Synthesis Provisions, imposes strict requirements on content labelling, ethical reviews, and data security. A standout feature is the Cyberspace Administration of China's algorithm filing system, which requires developers of public-facing models to submit technical documentation and security assessments within 10 days of launch, creating a rigid compliance ecosystem that balances rapid commercialisation with absolute state oversight and the prevention of social addiction or misinformation.

India’s AI journey represents a deliberate evolution from foundational academic research to coordinated national strategy, beginning with early computer science programmes at the Indian Institutes of Technology, Indian Institute of Science, and the Tata Institute of Fundamental Research in the mid-20th century, followed by the Knowledge-Based Computer Systems project in the 1980s — India’s first coordinated national AI endeavour. Recent acceleration began with the Digital India initiative laying essential digital infrastructure, culminating in NITI Aayog’s landmark National Strategy for Artificial Intelligence in June 2018, which outlined the AI For All vision, emphasising healthcare, agriculture, education, smart cities, and transportation as priority sectors. This was followed by the Responsible AI for Social Empowerment initiative in 2020 and the establishment of the IndiaAI portal in May 2020, with India’s ecosystem growing to include over 1,600 AI-focused startups by 2023 and ranking first globally in AI skill penetration according to the Stanford AI Index Report 2025. The defining moment arrived in March 2024 with the Union Cabinet approving the IndiaAI Mission, a $1.25 billion five-year initiative structured around seven pillars: compute capacity achieving 38,000 GPUs at subsidised rates, an innovation centre developing indigenous large multimodal models, a dataset platform, application development, future skills supporting 500 PhD fellows, startup financing, and safe and trusted AI promoting responsible deployment. India’s unique positioning emerged through the Global IndiaAI Summit in July 2024, which hosted 12,000 experts from 50 countries and showcased India’s Global Partnership on Artificial Intelligence (GPAI)  Lead Chair role. 

The philosophy differentiating India’s approach centres around “AI for Inclusive Societal Development”, as articulated in the NITI Aayog’s October 2025 report, emphasising AI’s potential to empower 490 million informal workers through expanded access to healthcare, education, and financial inclusion.

This development-focused, democratic approach positions India not merely as an AI adopter but as a global hub for ethical, affordable, and socially impactful AI innovation, offering a distinctive model balancing technological advancement with inclusive growth that neither the resource-intensive US nor state-controlled Chinese approaches provide.

The geopolitical landscape of 2026 is defined by different approaches to military AI integration, each reflecting distinct strategic philosophies and operational priorities. Understanding how the US and China are integrating AI into their military operations provides essential context for exploring the best path forward for the Indian military.

The US views AI as central to maintaining its military superiority, investing $1.8 billion in unclassified defence AI programmes across 685 active projects. Darpa’s AI research portfolio has expanded dramatically, with approximately 70 per cent of its programmes now incorporating AI, machine learning, or autonomy, backed by over $2 billion invested through its AI Next campaign since 2018. Research priorities span autonomous drone operations through the Rapid Experimental Missionized Autonomy programme, adversarial AI defence via the Guaranteed Architecture for Robust Defense programme — which protects against attacks like adversarial patches that could make AI misclassify tanks as civilian vehicles — and the Securing Artificial Intelligence for Battlefield Effective Robustness programme that builds AI red teams to test autonomous systems operationally.

It is also looking towards autonomous systems at scale, where Project Replicator (with Replicator 1 announced in 2023 and Replicator 2 in 2024) aims to field thousands of smart, low-cost, expendable, multi-domain platforms to overwhelm adversary networks. Research priorities include neuro-symbolic AI combining deep learning with logical reasoning for explainable decisions, and Collaborative Combat Aircraft — autonomous “loyal wingman’ jets capable of electronic warfare, reconnaissance, and precision strikes alongside crewed aircraft. Recent contracts awarded up to $200 million each to Anthropic, Google, OpenAI, and xAI signal the Pentagon’s strategy to leverage commercial frontier AI models with the aim of retaining strategic advantage. The ultimate goal is AI-enabled decision-making that outpaces human reaction time, compressing the kill-chain.

The People’s Liberation Army (PLA) is evolving from “informationised” to “intelligentised” warfare, viewing AI as a critical technology to bypass Western conventional strengths. Under Civil-Military Fusion, it prioritises swarm intelligence, autonomous vehicles, and cognitive domain warfare — using AI for psychological operations and information manipulation. The 2024 Zhuhai airshow showcased capabilities including Norinco’s Intelligent Precision Strike System, which autonomously models battlefields and executes strikes with minimal human intervention, and the AI-Enabled Synthetic Brigade combining armoured vehicles, drone swarms, and electronic warfare.

Recent integration of DeepSeek AI into PLA weapon systems demonstrates China's emphasis on algorithmic efficiency. An excellent example is the P60 autonomous combat vehicle, which can conduct operations at 50 kmph using DeepSeek systems trained for $6 million compared to the $100+ million typically spent by US companies. PLA research advocates minimal human intervention in autonomous urban warfare, meaning humans authorise deployment while systems make autonomous engagement decisions. The next major domain China has been working on is the integration of AI in its space programme, which is expected to be a game-changer. China is aiming to achieve AI sovereignty by 2030, developing brain-computer interfaces and AI-enhanced exoskeletons to create augmented soldiers.

India’s approach emphasises strategic autonomy through indigenous AI development tailored to the unique security challenges it faces. All three arms of the Indian armed forces have established dedicated AI centres progressing projects in autonomous systems, predictive maintenance, and domain awareness. Recent operational experience during Operation Sindoor has validated tri-service AI integration, achieving fairly high accuracy in target identification through indigenous systems, including the Electronic Intelligence Collation and Analysis System (ECAS) for intelligence analysis and the Integrated Air Command and Control System (IACCS) for air defence coordination. The Indian Army’s AI Roadmap 2026-27 identifies over 85 use-cases prioritising terrestrial and maritime domain awareness, drone swarms, and embedding AI into future weapon specifications. India is looking to position itself as a hub for “frugal AI”, developing affordable open-source models for the global South. However, defence AI spending of ₹100 crore annually is fairly modest when compared with the funding being undertaken by other countries and the level of AI integration they have achieved.

The geopolitical landscape of 2026 is defined by a multipolar struggle for AI dominance, with the US, China, and India following three distinct philosophies of integration, each with unique research priorities and military doctrines that merit deeper examination across research areas, current capabilities, and future trends.

The US continues to view AI as the “Sputnik moment” of the 21st century, with its strategy codified in the 2025 National Security Strategy signalling a move towards transactional realism. The Department of Defense is investing heavily in neuro-symbolic AI, combining deep learning with logical reasoning to make AI decisions “explainable”, alongside autonomous collaborative platforms featuring AI-piloted “loyal wingman” aircraft. Current US military capabilities have operationalised AI across four major domains: decision support, accelerating staff planning, intelligence processing of sensor feeds, predictive maintenance, reducing equipment downtime, and autonomous operations. A Project Replicator has been operationalised with the aim of fielding thousands of low-cost, multi-domain autonomous systems to overwhelm adversary sensor networks through mass and decentralised intelligence. Darpa’s AI demonstrated its ability to autonomously pilot an F-16 in dog fighting scenarios against human pilots in 2023 and flew a Black Hawk helicopter without human control in 2022, while the US Air Force’s Maven Smart System, tested in “Experiment 3” in late 2025, provided real-time target and suggested tactical response to military teams, ensuring information dominance at the tactical level. Looking forward, the US is moving towards “hyperwar”, where

AI-driven decision-making outpaces human reaction time, aiming for a “decision advantage” that reduces the kill-chain to mere seconds.

The PLA’s doctrinal evolution to “intelligentised” warfare views AI as a “leapfrog technology”  to bypass Western conventional strengths. Under Civil-Military Fusion, China is focusing on swarm intelligence and cognitive domain warfare, using AI for psychological operations and deepfakes to manipulate public opinion. The unveiling of ‘Orca’, a 500-tonne autonomous stealth combat vessel, demonstrates China's ability to project naval power without human risk. Future trends show China aiming for “AI Sovereignty” by 2030, focusing on brain-computer interfaces, AI-enabled space warfare capabilities, and AI-enhanced exoskeletons to create “augmented soldiers”. India’s AI journey is characterised by strategic autonomy, building a customised AI stack for unique security challenges. The Indian Army’s AI Roadmap for 2026-27 prioritises terrestrial domain awareness and predictive maintenance for its diverse hardware fleet. Current capabilities demonstrate that lessons from Operation Sindoor have fast-tracked AI-based surveillance and facial recognition, alongside the testing of indigenous drone swarms. While positioning itself as a hub for “frugal AI”, India is ensuring that its military retains its lethality and responsiveness through the use of AI.

India’s AI journey demonstrates impressive progress from institutional frameworks to battlefield validation, but sustaining leadership through 2030 requires strategic action across multiple dimensions. Current spending of ₹100 crore annually is inadequate when compared with the $1.8 billion US defence AI budget and China's estimated multi-billion dollar commitment. A dedicated defence AI fund targeting ₹5,000 crore annually, with clear allocation across research and development, procurement, talent development, and infrastructure, is essential to exploit current gains. This investment should be ring-fenced and linked to measurable outcomes, including indigenous systems deployed, operational capabilities achieved, and strategic vulnerabilities addressed.

While Operation Sindoor demonstrated sovereign AI capabilities, India must expand beyond military applications to develop globally competitive foundation models.

The IndiaAI Mission’s compute capacity expansion to 38,000 GPUs provides infrastructure, but India needs coordinated efforts across Defence Research and Development Organisation, Indian Institutes of Technology, and private sector partners to build models rivalling Generative Pre-trained Transformer 4, DeepSeek and others. BharatGen and similar initiatives should receive prioritised funding with aggressive timelines for deployable systems across defence, intelligence, and critical infrastructure domains. China’s integration of civilian AI breakthroughs into military applications through structured partnerships offers lessons India can adapt democratically to create formal pathways for startups developing AI for logistics, computer vision, natural language processing, and autonomous systems to engage with defence requirements, which would accelerate innovation. Tax incentives, guaranteed procurement commitments, and streamlined security clearance processes could catalyse an ecosystem where breakthrough commercial AI rapidly transitions to defence applications.

The 2026-27 AI Roadmap is a start, but India needs a comprehensive doctrine for AI-enabled joint operations, including updating operational concepts for autonomous swarms, establishing protocols for human-machine teaming, creating training programmes ensuring personnel can effectively employ AI systems, and developing electronic warfare capabilities to counter adversary AI. The AI Impact Summit 2026 has provided India with an ideal platform to champion AI governance frameworks reflecting developing nation priorities. India should build on this and propose international standards balancing innovation with safety, facilitate technology transfer enabling other nations to build indigenous capabilities, and create collaborative research initiatives on AI for development challenges. Positioning itself as the bridge between Western regulatory approaches and Chinese state-led models will allow India to shape norms aligning with democratic values while addressing the global South’s needs.

As AI systems become central to military operations, they become targets. So India must invest in robust cybersecurity protecting AI infrastructure, develop capabilities to detect and counter adversarial AI attacks, establish redundant command and control systems ensuring resilience, and create red teams which test AI system vulnerabilities.

The Computer Emergency Response Team of India should expand its mandate specifically for AI security. While India opposes bans on lethal autonomous weapons, it should lead in establishing voluntary ethical frameworks for military AI deployment through clear policies on human oversight for lethal decisions, algorithmic accountability for AI-driven targeting, transparency mechanisms for AI system development and testing, and regular audits ensuring compliance with international humanitarian law. This would position India as a responsible AI military power and strengthen deterrence credibility.

The Summit took place amid a military AI transition from the experimental to operational across the world’s major powers. The US maintains technological leadership through massive investment and public-private partnerships, but faces regulatory uncertainty following the shift from former president Joe Biden’s comprehensive framework to Trump's deregulatory approach. China pursues “intelligentised warfare” through state-directed integration of AI into autonomous systems, logistics, and cognitive operations, backed by comprehensive regulations prioritising control alongside innovation.

India’s battlefield validation of AI during Operation Sindoor positions it uniquely in discussions on integrating AI in existing systems. The world watched New Delhi host the largest AI summit to date, and India now has the opportunity to demonstrate that democratic governance and AI excellence are complementary. The recommendations outlined — scaled investment, indigenous model development, military-civil fusion, doctrinal evolution, global South leadership, cybersecurity enhancement, and ethical frameworks — provide a roadmap for India to achieve its ambition of becoming a top-three AI power by 2030.

The Summit’s success should be used by India to translate its AI vision into execution, policy into capability, and potential into power. With institutional frameworks established, regulatory coherence achieved, sectoral adoption accelerating, and battlefield systems proven, India stands at an inflection point. The path to AI leadership is clear; the imperative is action.