Artificial Intelligence (AI) is no longer a speculative frontier technology. It is now a structuring force in global power competition, reshaping how states gather intelligence, conduct warfare, project influence, manage borders, secure cyberspace, and even shape public perception. Although hosting the AI Impact Summit 2026, India signalled to the world its readiness in AI, a deeper question remains: is India prepared to treat AI not merely as an engine of economic growth or digital governance, but as a foundational pillar of national security?
The last decade has witnessed a profound transformation in the character of warfare. The battlefield is no longer confined to land, sea, air, or even space; it extends across the electromagnetic spectrum, data networks, social media ecosystems, satellite constellations, supply chains, and financial infrastructures. Conflicts are increasingly hybrid, persistent, and below the threshold of declared war. They are accelerated by machine learning, shaped by predictive analytics, and mediated by autonomous systems. States that successfully integrate AI into their national security architectures are not merely enhancing capability; they are redefining strategic advantage.
The last decade has witnessed a profound transformation in the character of warfare. The battlefield is no longer confined to land, sea, air, or even space. It is dispersed across the electromagnetic spectrum, data networks, social media ecosystems, satellite constellations, supply chains, and financial infrastructures.
India stands at a critical juncture. It possesses world-class AI talent, a vast digital ecosystem, a growing space programme, and one of the world’s largest armed forces. It also faces security competition in the region while navigating a complex geopolitical environment in a fractured multipolar world. In response, the Indian national security establishment has adopted several technological tools, including AI, to perform tasks. Yet the pace of this AI adoption remains uneven and often siloed. Without a comprehensive doctrinal and institutional shift, India risks strategic lag in a domain where delay compounds vulnerability.
It is essential to understand AI not as a separate technological tool, but as a comprehensive transformation of national security practice.
The Changing Character of Warfare: From Industrial to Algorithmic Conflict
Historically, warfare evolved alongside technological revolutions. The industrial age produced mass mobilisation and mechanised warfare. The nuclear age introduced the frameworks of deterrence and strategic stability. The information age has created network-centric warfare and precision-strike doctrines. Today, we have entered what may be called the algorithmic age of warfare.
India stands at a critical juncture. It possesses world-class AI talent, a vast digital ecosystem, a growing space programme, and one of the world’s largest armed forces.
The defining features of contemporary conflict include:
- Decision-Speed Dominance: Victory increasingly depends on the ability to process, interpret, and act upon data faster than adversaries.
- Data-Centric Operations: Intelligence, logistics, targeting, and command structures revolve around data fusion at scale.
- Persistent Hybrid Engagement: Conflict extends across information ecosystems, cyberspace, and economic infrastructure.
- Autonomy and Human-Machine Teaming: Machines assist or execute decisions under defined parameters.
- Grey-Zone Escalation: States operate below overt war, applying pressure incrementally.
AI is now the core system that connects intelligence, defence, cyber, space, and maritime security. It improves pattern recognition in complex environments, supports predictive modelling, automates repetitive analysis, and allows autonomous systems to act with awareness. For India, this shift is critical amid persistent two-front wars, intensifying competition in the Indian Ocean, and expanding information warfare. Therefore, AI must be embedded across all levels of the national security architecture.
The nuclear age introduced the frameworks of deterrence and strategic stability. The information age has created network-centric warfare and precision-strike doctrines. Today, we have entered what may be called the algorithmic age of warfare.
Modern intelligence generates vast amounts of data from satellites, drones, intercepted communications, financial networks, and social media. Human analysts alone cannot manage this scale. AI can classify signals, detect anomalies, combine multiple intelligence streams, predict escalation risks, and identify insider threats. The United States (US) integrates AI across agencies through cloud infrastructure and joint data-sharing platforms under initiatives such as JADC2, thereby improving cross-domain coordination.
China follows a civil-military fusion model in which civilian AI companies directly support military intelligence and “intelligentised warfare.” Russia applies AI in hybrid warfare, including automated cyber operations. India has taken steps such as establishing the Defence AI Council (DAIC), the Defence AI Project Agency (DAIPA), the iDEX initiatives for defence innovation, and AI-based surveillance systems along its borders.
Similarly, control of the electromagnetic spectrum is now central to warfare, as it is to cyber conflict. Radar, satellites, communications, and missile systems depend on it. China has invested heavily in AI-enabled spectrum dominance within its anti-access/area-denial strategies, whereas the US integrates AI-driven spectrum awareness into joint command systems.
For India, this shift is critical amid persistent two-front wars, intensifying competition in the Indian Ocean, and expanding information warfare.
India has strengthened its cyber capacity through several institutional and regulatory measures, but it still requires more robust indigenous AI-based threat-detection systems to secure power grids, telecommunications networks, financial systems, and defence infrastructure. For example, South Korea has introduced AI-patrolling cars that integrate voice recognition, video analysis, and real-time data processing, or modern tools developed by central agencies like the Bureau of Police Research & Development (BPR&D), India, to closely monitor the dark web and conduct predictive and pre-emptive analysis of existing threats. Although India has expanded drone use and space-based maritime surveillance in the Indian Ocean Region, current technology does not enable the detection of deep-sea submarines via satellite.
India’s Structural Challenges
India’s structural challenges are not due to a lack of ambition but to gaps in coordination and capacity. Integrating artificial intelligence into India’s national security architecture presents several operational and technological challenges.
One of the most significant issues is the existence of institutional silos across organisations, including the armed forces, ministries, and private technology firms, hampering the integration of AI and the national security domain. A particularly critical issue is the lack of integration across intelligence, surveillance, and reconnaissance (ISR) systems to support decision-making. India currently lacks robust platforms that can unify multi-sensor data through edge computing and AI analytics. In addition, training and deploying advanced AI systems require massive computational infrastructure, including high-performance GPUs and large data centres, which are still limited domestically.
India must ensure better alignment between ministries and agencies. Instead, it should develop a democratic AI security framework grounded in accountability, robust institutions, indigenous technologies, and a coordinated national strategy.
Defence procurement policies are traditionally slow and risk-averse, making it difficult to rapidly develop and deploy emerging technologies such as generative AI systems. Furthermore, there is a shortage of specialised AI talent within the defence ecosystem, compounded by traditional institutions’ reluctance to recruit from the private sector. These technological, organisational, and infrastructural challenges collectively slow India’s ability to fully integrate AI into its national security framework.
Although initiatives such as iDEX and the Technology Development Fund have attempted to bridge this gap, collaboration remains limited. Another structural challenge is the absence of data sharing, edge computing, and networked warfare systems. AI-enabled military operations require interoperable platforms that allow different systems, sensors, and units to communicate seamlessly. However, India currently lacks uniform standards for such integration.
Finally, funding and institutional coordination remain major constraints. While organisations such as the Defence AI Council and initiatives under the IndiaAI mission are important steps, the absence of a cohesive national framework for defence AI development continues to slow progress.
Conclusion: From Symbolism to Strategic Transformation
AI is changing warfare in intelligence, cyber operations, the electromagnetic spectrum, information warfare, logistics, and space. India has the talent and capacity to develop AI systems.
India’s AI security model must learn from countries like the US, China, and Russia, but adapt to its democratic system and threat environment. For example, the US shows the value of integration and public–private partnerships. Through institutions such as the Joint AI Centre and the Defence Innovation Unit, it connects technology firms with defence needs and builds shared cloud systems for intelligence and joint command. China offers a lesson on strategic coherence through the civil-military fusion model, which ensures that advances in civilian AI quickly support military goals.
India needs to build its sovereign AI in the national security domain. This is crucial because defence applications rely on sensitive datasets such as satellite imagery, electronic intelligence, and battlefield information, which could be vulnerable if processed through foreign platforms.
India should not copy this centralised approach, but it must ensure better alignment between ministries and agencies. It should develop a democratic AI security framework grounded in accountability, robust institutions, indigenous technologies, and a coordinated national strategy. The real challenge is not access to AI technology but the transformation of institutions to use it effectively.
Lastly, India needs to build its sovereign AI in the national security domain. This is crucial because defence applications rely on sensitive datasets such as satellite imagery, electronic intelligence, and battlefield information, which could be vulnerable if processed through foreign platforms. To achieve sovereign AI, India must build a complete national AI stack by investing in domestic compute infrastructure, such as GPU clusters and secure defence clouds, harmonising and integrating government datasets, and collaborating among the military, academia, and industry.
In today’s tech-driven world, strength comes not only from innovation but also from integration. India’s main task is not just writing better code but reforming its institutions to use AI effectively. And that transformation must begin now.
Soumya Awasthi is a Fellow with the Centre for Security, Strategy and Technology at the Observer Research Foundation.
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