By Manoj Dhanda, Founder & CEO, Utho Cloud
India’s digital infrastructure story has largely been defined by connectivity, cloud adoption, and data centres. The company has developed the necessary infrastructure for developing a growing digital economy. However, as companies create more data and technologies like AI and automation increase computational intensity, there is one other critical piece of infrastructure that is becoming more important than ever before. Does India have sufficient compute power, and can companies have access to it when they need it?
“Compute” essentially refers to the computing power required for executing applications and processing data. Even though it has always been an essential element of the IT infrastructure, its significance is changing. Having the capability of storing data has never been enough; now companies require computing power to process it effectively.
The shift from cloud to compute
The use of cloud computing led to a shift in the way businesses were managing their IT infrastructure. Instead of investing in physical infrastructure, they could make use of computing power, storage, and networking resources based on their needs. The nature of those workloads, however, is evolving.
AI has brought compute requirements into sharper focus, particularly with the growing use of GPUs for model training and inference. But demand extends beyond AI. Financial institutions rely on computing for risk analysis and fraud prevention. Manufacturers need computing for simulations, automation, and machine vision. Healthcare and research organisations process increasingly complex datasets, while businesses across sectors use real-time analytics. As these applications grow, compute is moving from being a technical component in the background to becoming a strategic infrastructure resource.
AI is raising the compute bar
AI is one of the strongest drivers of this shift. Developing and deploying AI systems can require specialised processors, substantial memory, high-speed networking, and considerable storage. India’s AI Compute initiative reflects the growing emphasis on access to high-performance computing, with GPU infrastructure being made available to startups, researchers, academia, MSMEs, and industry.
However, expanding compute capacity is not simply about adding more GPUs. Different workloads require different configurations, while demand can vary between training, inference, analytics, and conventional enterprise applications. The focus will therefore need to move from compute capacity alone to usable compute capacity infrastructure that can be provisioned according to workload, scaled when required, and managed efficiently.
Why location will matter
The location of computing infrastructure is also becoming increasingly important. With the increasing volume of sensitive data being held in digital formats, companies need to think about the location of their data. Residency issues, regulatory considerations, and security concerns may dictate the choice of the infrastructure, especially for those dealing with finance, personally identifiable data, medical, or governmental information.
Location is also important when it comes to performance. Analytics, IoT, industrial computing, and AI inference may be facilitated by computing located closer to the source of data or the end user. It would help promote a decentralised infrastructure strategy where large data centres are supplemented by cloud-based facilities in the region and edge computing sites. Such an approach can bring processing closer to where it is needed while supporting different performance and workload requirements.
Beyond data residency
The increased significance of computing is also highlighting the issue of digital sovereignty. The ability to see inside the infrastructure that processes such data will be essential when it is scaled up and becomes an integral part of business operations. Keeping such data and computations within the same national jurisdiction may prove useful in certain scenarios to meet certain requirements.
In other words, sovereignty goes beyond the question of storage. It concerns understanding where the data is processed, what infrastructure supports it, and what kind of legal regimes control all of this. For the case of India, domestic computing infrastructure will play a key role in building a resilient digital sovereignty ecosystem.
Making computing more accessible
However, capacity alone does not comprise the entire problem; there is the issue of accessibility as well. While it is true that big companies have the financial power to build infrastructure, start-ups and MSMEs, researchers, and smaller tech teams might require something more versatile. Cloud computing can help provide access to infrastructure without much expenditure on hardware at the initial stage.
This can be particularly useful for experimentation. A business developing an AI application may require substantial computing resources during development but considerably less once a workload is optimised. The ability to scale resources according to demand can help organisations manage both infrastructure requirements and costs. For India, wider access to compute could also determine how broadly advanced technologies are adopted across the economy.
The infrastructure-energy connection
Another factor cannot be ignored is power. High-performance computing takes lots of energy, and data centers need electricity and cooling. With increased demand for compute, digital infrastructure and energy infrastructure will have a growing convergence.
Building computing capacity will thus need more than just processing units. It will take investments in data centres, networking, power facilities, air conditioning, and other capabilities. Efficiency will matter alongside scale. Increasing infrastructure without ensuring effective utilisation could raise both costs and energy consumption.
Building for the next digital chapter
India has already built much of the foundation for a connected digital economy. The next stage will increasingly depend on what that infrastructure can process, not simply how much information it can carry or store. Compute will be central to that transition, with applications extending from AI and advanced analytics to manufacturing, financial services, healthcare, research, and public infrastructure.
The next competition in digital infrastructure will probably not only revolve around the number of servers, data centres or GPUs built. It will increasingly focus on whether there is enough computing power available in the right place, in the right quantity, under proper security and governance, and at an acceptable price. India’s digital advantage will ultimately depend not just on generating more data, but on having the infrastructure to turn that data into useful outcomes. The next chapter of the country’s digital infrastructure story may therefore be about building accessible, distributed, and resilient compute infrastructure that allows more of the economy to make effective use of digital technology.