New Delhi [India], October 22 : India’s AI market is expected to see a shift in demand towards debt financing for data centres and computing infrastructure. At the same time, the sector faces several risks, including the rapid obsoleteness of graphics processing units (GPUs), uncertain revenue models and evolving governance regulations, according to a report by Union Bank of India. 
The report says India's AI market is expected to witness strong growth, driven by its expanding internet and smartphone user base and rising adoption of generative AI by enterprises. 
India currently has around 880-900 million internet users, with a target of reaching 1.2 billion by 2030, while its smartphone user base stands at approximately 700-750 million. 
“India brings a huge talent pool and one of the world's largest internet user bases to this race, but still lags in indigenous compute infrastructure and foundational models,” it said. 
Also, generative AI is now part of over 60 per cent of large IT deals and India's share of global mobile data traffic is among the highest in the world, which further provides support for AI development and adoption.
The lender highlighted several strengths of India's AI sector, including “World's largest tech talent pool feeding AI development,” a massive internet and smartphone user base generating valuable data, and strong IT services capabilities that enable the adoption and implementation of AI solutions across enterprises.
However, the lender pointed out several weaknesses in India's AI sector, including limited domestic manufacturing capacity for computing infrastructure and graphics processing units (GPUs). 
It noted that India's capabilities in developing foundational AI models are still at an early stage compared to the US and China, while regulatory frameworks related to data privacy and AI governance are still evolving, posing challenges to the sector's growth.
“Rapid global AI hardware obsolescence (18-24 month cycles),” along with global talent poaching to US and Gulf AI labs and regulatory uncertainty on data and AI governance, remain the biggest threats to the overall sector. 
According to the report, India's AI sector offers diverse financing opportunities, with GPU and computing infrastructure requiring high capital investment through structured debt, sale-leaseback arrangements and hyperscaler funding. 
Foundational AI model development, on the other hand, relies on venture capital, private equity, government grants and corporate R&D funding, while AI SaaS and applications attract venture capital, venture debt and revenue-based financing. 
Notably, AI skilling and Centres of Excellence (CoEs), which require lower investment, are primarily supported by government grants, CSR funding and public-private partnerships.
Overall, the lender recommended developing structured and equipment-financing products for GPU clusters and expanding venture-debt partnerships to support AI application companies. 
Over the next three to five years, financing demand is expected to shift towards debt funding for data centres and computing infrastructure, it said.