India’s efforts to shore up its artificial intelligence (AI) infrastructure will bolster, rather than cannibalise, established Southeast Asian tech hubs like Singapore and Malaysia, according to industry leaders from the subcontinent. Speaking at the Gitex AI Asia 2026 conference in Singapore, tech executives at the forefront of India’s AI infrastructure boom outlined how the country’s massive scale will serve as a testing ground for the broader Asian market.
Sunil Gupta, co-founder and chief executive of Indian datacentre giant Yotta Data Services, and Jay Chandan, chairman and CEO of Gorilla Technology, a UK-based supplier of AI-powered smart city applications, recently inked a landmark agreement to deploy thousands of graphics processing units (GPUs) across India. During a fireside chat, the two leaders discussed the details of the roll-out, driven by New Delhi’s push to build sovereign AI capabilities to protect national data and cater to domestic needs.
With a population of 1.4 billion, including a billion smartphone users connected to the internet, India currently accounts for over half of the world’s digital payment transactions. This has led to an increased demand for processing and storing data within the country’s borders. And with the growing adoption of AI in recent years, users are now worried about what will happen to their data, said Gupta, particularly in terms of privacy and security concerns regarding how their information is used and managed by AI systems. “People want sovereign AI and sovereign models trained on sovereign data,” he said. “That’s a huge wave in India right now, supported fully by the government.”
Through the state-backed IndiaAI Mission, the Indian government is heavily subsidising computing costs, paying infrastructure providers to allocate GPUs to local model builders, researchers and academia. “We’re looking at about 5,000 GPU cards to be deployed for our AI workloads in the first six months,” said Chandan, adding that the partnership aims to eventually scale up to 36,000 GPUs. Under the agreement, Gorilla will provide the GPU infrastructure, while Yotta will operate the GPUs at its Navi Mumbai datacentre to deliver AI compute services, including GPU clusters, bare-metal GPUs, AI lab workstations and AI model endpoints to enterprises and government customers.
Solving the ROI challenge
Gupta noted that while many enterprises have developed AI use cases across a range of industries, including finance, media, entertainment and manufacturing, not all have made it to production. “The CFO [chief financial officer] is not convinced,” he added. “If I invest in these GPUs, models, datasets and skill sets, will I get a return? We have to bring down the cost so they can cross that line into production. If they start experimenting and become successful, then they’ll scale up.” By offering GPU infrastructure through an elastic, low-cost consumption model, Yotta and Gorilla aim to make enterprise AI commercially viable, generating returns on investments in three to five years, said Chandan.
However, the build-up of India’s AI infrastructure has raised questions about whether the subcontinent could syphon tech investments away from Southeast Asian digital hubs. “In all the meetings I’ve had, people ask, ‘Is India going to replace Singapore, Malaysia and Vietnam?’ That’s not going to happen,” said Chandan. “India is not here to replace anybody. India is here to help you build scale and velocity. It’s here to show you that you can build these large-scale models, and you can be successful with an efficient cost base.” Gupta added that India’s sprawling datacentres are also helping to solve global supply chain challenges. He revealed that due to GPU shortages elsewhere, enterprises from Europe and the Middle East are increasingly looking to India to host their AI training and inference workloads. “Because India is geopolitically safe compared to many other areas, it has the potential to become a major hotspot for serving global AI demand,” he said.
Background on India’s sovereign AI ambitions
The IndiaAI Mission, launched with a budget of over $1.2 billion, aims to build a comprehensive AI ecosystem that includes computing infrastructure, data platforms, and skilling initiatives. The government has also established the IndiaAI Innovation Centre to foster collaboration between startups, academia, and industry. In addition, the mission promotes the development of foundational AI models trained on Indian languages and datasets, ensuring that AI systems are culturally appropriate and aligned with national priorities. This push for sovereign AI reflects broader global trends, where countries are seeking to reduce dependence on foreign AI services and maintain control over sensitive data.
India’s advantage in scale is also evident in its telecommunications infrastructure. With Reliance Jio and Bharti Airtel rolling out 5G services rapidly, the connectivity backbone for AI workloads is strengthening. The Indian Space Research Organisation (ISRO) is even exploring orbital datacentres to bypass terrestrial power constraints. These initiatives, combined with the government’s focus on digital public infrastructure, position India as a leader in the next wave of AI adoption.
Global implications and regional dynamics
The partnership between Yotta and Gorilla is just one example of the large-scale GPU deployments happening in India. Other vendors, such as Nvidia, have announced collaborations with Indian infrastructure providers to supply tens of thousands of GPUs. This capacity is not only for domestic use but also for serving clients in the Middle East, Africa, and Europe who face GPU shortages and high energy costs at home. India’s relative political stability and lower operational costs make it an attractive destination for AI data processing.
In Southeast Asia, Singapore remains a major AI hub, but its land and power constraints limit the scale of datacentres. Malaysia and Vietnam are also expanding, but India’s ability to deploy massive infrastructure quickly gives it a competitive edge. Rather than displacing these hubs, Indian executives argue that the subcontinent will complement them by providing overflow capacity and serving as a testbed for region-specific AI models. For example, multilingual AI models trained on Indian languages can be adapted for other Asian markets with similar linguistic diversity.
Enterprise adoption and ROI hurdles
Despite the enthusiasm, the return on investment for AI remains a significant challenge for enterprises. Many companies have run small-scale pilot projects but struggle to justify the costs of full production deployments. The flexible pricing model offered by Yotta and Gorilla addresses this by allowing enterprises to pay for GPU compute on a consumption basis, reducing upfront capital expenditure. This model is particularly appealing for startups and medium-sized businesses that want to experiment with AI without committing to long-term contracts.
Gupta emphasised that the key to unlocking AI’s potential is making it accessible and affordable. “We are seeing interest from sectors like healthcare, where AI can analyse medical images, and agriculture, where AI can optimise crop yields. But these organisations need proof that the technology works and that they can see a return within a reasonable timeframe.” The partnership aims to provide that proof through success stories and case studies that demonstrate tangible business outcomes.
In addition to cost, talent shortage remains a barrier. The IndiaAI Mission includes plans to train 100,000 professionals in AI and data science over the next three years, with a focus on both technical skills and ethical AI practices. This will help enterprises overcome the skill gap and accelerate adoption. With the combination of subsidised compute, talent development, and government support, India is poised to become a major player in the global AI landscape.
Source: ComputerWeekly.com News