India’s aspiration to emerge as a global artificial intelligence (AI) leader is backed by strong vision and growing investment. PwC estimates that AI could add nearly $967 billion to India’s GDP by 2035, reshaping industries, accelerating innovation, and redefining productivity. But this future relies on far more than data or algorithms. It depends on the strength of the digital infrastructure that enables AI to function. Unless India bridges the significant gaps in its network capabilities, the benefits of AI may remain limited to a select few instead of powering inclusive growth.
What’s slowing down this journey?
Connectivity: The Missing Link in India’s AI Journey
For AI to operate at scale, whether in autonomous logistics, real-time smart city systems, or remote rural diagnostics, it requires fast, reliable, low-latency networks. India’s current digital foundation, however, remains uneven. While urban areas enjoy advanced 5G connectivity, vast stretches of rural and semi-urban India still struggle with inconsistent 4G or even weaker networks. This creates an AI readiness divide that closely mirrors the existing digital divide.
The consequences are far-reaching. In sectors like telemedicine or AI-enabled learning platforms, network performance is critical. If a specialist in Delhi can deliver real-time guidance but a patient in a remote district cannot connect due to network issues, the promise of AI collapses precisely where it is needed most.
Connectivity as the Fuel for Intelligent Systems
AI systems thrive on data, both in training and deployment. To function effectively, they require:
Networks Built for Speed
Modern AI is increasingly embedded in everyday environments, not just operating in distant cloud servers. Autonomous logistics systems, for example, could streamline India’s complex supply chains, but only if they process sensor inputs and make routing decisions in milliseconds, not minutes.
Similarly, remote medical diagnostics, crucial for addressing rural healthcare gaps, depend on the instant transfer of high-resolution images and video. Even a slight delay can impact diagnostic accuracy, underlining why low-latency, high-bandwidth connectivity is a core requirement.
Intelligent Computing Close to the User
AI’s future lies in distributed computing. Instead of routing all data to centralized facilities, edge computing brings processing closer to the point of data generation.
Given India’s vast geography, this approach is not just efficient, it is essential. Strategically located edge nodes improve inference speed, reduce dependence on national bandwidth, and allow services to function even during network disruptions. But this model requires wide, robust network coverage linking users, edge sites, and central systems.
Stability That AI Can Learn On
AI models evolve continuously through constant training and updates. This loop demands a stable connection between data sources, training systems, and deployment environments.
In a country where weather, power variability, and infrastructure challenges can disrupt connectivity, ensuring stability is no small task. And interruptions don’t just inconvenience users, they compromise the reliability and learning capabilities of AI systems.
Without these building blocks, India risks creating an AI economy centred around Tier 1 cities, leaving rural regions to contend with network outages and bandwidth constraints.
Government Initiatives: Strengthening the Base Layer
The government has been driving rural fibre expansion through initiatives such as BharatNet. By improving broadband access across villages and remote clusters, BharatNet creates the foundational layer that AI-enabled services require. Telemedicine, remote learning, and digital agriculture can only scale when every location is reliably connected to intelligent systems. This initiative is critical to bridging the AI-readiness gap and ensuring that intelligent technologies reach the grassroots.
ICT Players: Powering the Backbone of Intelligent India
India’s Information and Communications Technology (ICT) players are at the forefront of strengthening this digital backbone. Their responsibility goes beyond expanding coverage, they are reengineering the very architecture of connectivity. Through rural fibre expansion, satellite-based internet, and support for regional edge data centres, they are laying the foundation for more inclusive, future-ready networks.
However, meaningful impact requires collective action across government, industry, and regulators. Incentivising investments in underserved areas, simplifying rights-of-way processes, and embedding AI-readiness metrics into initiatives like Smart Cities and Digital India can accelerate much-needed infrastructure development.
AI for All, Not a Select Few
If India’s AI ambitions are to translate into broad-based progress, digital infrastructure must be viewed as a national priority, much like power, roads, or water. The cost of inaction is high. In an era defined by intelligence, connectivity determines one’s ability to participate in economic growth, access quality healthcare, and fully engage in the digital economy. Poor networks risk deepening the very inequalities AI aims to solve.
AI’s true strength lies in its capacity to democratize opportunity. But that vision can only become real when every citizen, regardless of geography, can tap into the networks that power intelligent systems.
India’s digital future demands faster, wider, and more resilient networks. And the time to build them is now.
The article has been written by Pinkesh Kotecha, Chairman and Managing Director of Ishan Technologies
