Global leader: India has capabilities to leverage artificial intelligence

At the recent artificial intelligence (AI) summit, Nvidia Chief Executive Officer Jensen Huang emphasised the graphics processing unit (GPU) maker’s commitment to India. The chief of the world’s most valuable company claims India will grow 20 times in terms of computing capacities in 2024 over 2023, and that it has all the key resources to become a global leader in AI. Nvidia already has close to a third of its employees in India, where it does the bulk of its chip designing and runs many of its algorithmic models. Nvidia is also in a string of partnerships with Indian startups as well as in collaboration and partnership with majors like Reliance Jio, the Tata group, and Bharti Airtel. It is also engaged with several Indian academic institutions and government organisations, and is even exploring the possibility of partnering the Indian judicial system.

 

Mr Huang’s faith that India can elevate itself from being an information technology (IT) back office and cost-reduction centre to being a leading AI production centre is well founded on the face of it. India does have most of the resources required to achieve this value-transformation, and it is plugging the gaps that exist. The country has a large, sophisticated digital economy that churns out huge volumes of data and this makes it ideal for training AI models. Moreover, its unique diversity in terms of multiple local languages could drive research into large language models (LLMs). India also has a large, highly skilled workforce with strong domain skills in computer science and data analytics. There are multiple large and mid-sized information-technology companies, and many tech-driven startups looking to leverage AI for commercial purposes across multiple sectors. There is a strong policy push in favour of inducting technology and academia is receiving the resources it needs for research and development. India is also ramping up its data centre capacity (and energy and telecom network capacities), and its physical computing capacities with the induction of more high-end chips.

 

Interestingly, Mr Huang believes AI may help to bridge the digital divide rather than widen it, which would allay a primary concern for India. His logic is that AI allows people to write programmes using natural language to instruct AI programmes, which will translate the natural language into code. This makes it considerably easier for people with no training to write programmes and that could indeed make life easier for Indians who do lack programming skills. He also offers a nuanced take on the shift in employment dynamics where, he says, AI will not take away jobs but people who learn to use AI well will take away jobs from those less skilled.

 

While Nvidia’s enthusiasm about India’s AI-driven future may be well founded, India should be aware of the dangers of getting locked onto one platform. Nvidia is the market leader when it comes to AI-capable chips and stacks, and it has a tight proprietary ecosystem. But this is an intensely competitive area and no company has retained permanent leadership across previous technological cycles. For instance, IBM was overtaken by Microsoft and Apple, and Nvidia overtook Intel and AMD. Sooner or later, Nvidia will be challenged by one of its current rivals, or by some upstart. At that stage, India’s AI ecosystem will need the flexibility to transit to the next platform with as little disruption as possible. India must plan for that future.