Pinkesh Kotecha, Chairman and Managing Director, Ishan Technologies
India’s artificial intelligence (AI) journey is entering a decisive phase. The shift from experimentation to scale is well underway, and enterprises are now embedding AI into core operations across customer experience, network optimisation, cybersecurity, and decision intelligence. What is becoming increasingly clear, however, is that AI success will not be defined by algorithms alone. It will be defined by the strength of the digital infrastructure that enables it.
As organisations move from pilot projects to production environments, infrastructure is no longer a backend consideration. It is emerging as the foundation of the AI economy.
India’s momentum in this space is significant. According to NASSCOM, the country’s AI market is expected to reach $17 billion by 2027, growing at over 25 per cent compounded annual growth rate. This rapid expansion is not just driving demand for AI tools, but also for the underlying systems that can support large-scale deployment.
AI at scale is an require robust Infrastructure
Much of the current AI discourse continues to focus on advancements in large language models and generative capabilities. While these developments are important, they represent only one layer of the ecosystem. AI at scale is fundamentally an infrastructure challenge. It requires sustained computational power, high-speed data processing, and the ability to deliver real-time outcomes with minimal latency. Without this foundation, AI initiatives struggle to move beyond controlled environments.
This is where a structural shift is underway. Enterprises are aligning AI adoption with investments in cloud, data centres, and high-performance computing environments. In India, this trend is accelerating, with data centre capacity expected to double from approximately 870 megawatt (MW) in 2023 to over 1,700 MW by 2026, driven by demand from AI workloads, cloud adoption, and data localisation requirements. This expansion signals a broader transition where infrastructure is no longer viewed as support, but as a strategic differentiator.
Connectivity will define the next phase of AI growth
If data centres and compute form the backbone of AI, connectivity is what enables it to function in real time. AI-driven applications, from predictive analytics to autonomous systems, require ultra-low latency, high bandwidth, and uninterrupted network reliability. These are not incremental improvements, they are foundational requirements for AI to operate at scale.
At the same time, the expansion of fibre infrastructure provides a strong base for high-capacity data transmission. The next phase of AI growth will be network-defined. Without robust, low-latency connectivity, even the most advanced AI systems will face limitations in real-world deployment.
The convergence of infrastructure layers
AI does not operate in silos, and neither can the infrastructure that supports it. The future of AI will be shaped by the convergence of multiple infrastructure layers, including data centres, cloud platforms, network infrastructure, and edge computing. These elements are increasingly being integrated into a unified ecosystem designed to support real-time processing and decision-making.
Edge computing, in particular, is gaining traction in sectors such as telecom, manufacturing, and logistics, where latency-sensitive applications require processing closer to the source of data. This shift towards decentralised computing is critical for improving efficiency and enabling faster insights. Organisations that can successfully integrate these layers will be better positioned to scale AI effectively and sustainably.
Building an AI-ready digital ecosystem
For India to fully realise its AI potential, strengthening digital infrastructure will be critical. This includes expanding AI-ready data centre capacity, accelerating the rollout of high-speed, low-latency networks such as 5G and fibre, and ensuring seamless integration across cloud and edge environments. It also requires robust data governance frameworks and strong cybersecurity measures to support increasingly complex digital ecosystems.
India is well positioned to emerge as a global leader in AI. However, leadership in this space will not be defined solely by innovation at the application layer. It will be determined by the ability to build and scale the infrastructure that powers it.
In the AI economy, infrastructure will not just support growth, it will define it.
