Written by Rohit Pandharkar
Donald Trump made big news by announcing “Project Stargate”, a $500 billion initiative, within 24 hours of swearing in as the president of the US. While the micro details and execution of this project are being discussed, there is no doubt that artificial intelligence (AI) technology and its implications are going to have an inordinate impact on the global economy, geopolitics, as well as the day-to-day life of the world population. Given this potential, it is important for India to show a clear intent to play a strong role in shaping the world of AI and to meaningfully execute impactful initiatives and incentivise innovation within the country.
Matching ambitions with investments
The very first expectation from this year’s Union Budget would be to increase the size of budgetary allocation for AI compared to the approximately Rs 10,300 crore India AI mission budget that was announced earlier. A small comparison would be that this entire national budget is smaller than what some of the hyperscaler internet companies in the US have been investing for their own internal AI divisions. This amount has to multiply several folds (perhaps more than 3X) to make a meaningful impact in the fast-changing world of AI.
The next question is, where should this budget be spent?
The AI budgets could be split into: [1] National Graphics Processing Unit (GPU) Cloud Infrastructure [2] Upskilling and training missions [3] Incentivising Startups and MSMEs for AI adoption [4] R&D and Innovation grants [5] Adoption of AI in Public Enterprises and Public Services [6] Creation of National AI standards, policies and governing boards [7] Incentivising GPU and Chip manufacturing businesses in India.
Given the recent stance taken by leading countries owning the GPU manufacturing facilities and upcoming rationing of GPU chips to other nations, India needs to make serious efforts towards creating its own supply chain and manufacturing ecosystem for making GPUs as well as building expensive GPU cloud datacenters. This has to happen at an accelerated pace, since once the GPU and chip technology rationing starts, the gap between nations who have it and those who don’t have it will magnify within a few months. Imagine not having enough GPUs to build enterprise-level AI systems and hence lacking the speed, productivity, intelligence levels, and cost benefits that come from running AI applications.
Prompt factory of the world
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The second biggest area the government should spend on is AI upskilling. India has the maximum number of software developers compared to anywhere else in the world and many more brains waiting to be trained in areas like prompt engineering. Everyone does not necessarily have to learn coding or complex mathematics and algorithms for this. Even learning how to prompt engineer to design marketing emails, or learning to create new image art works, or writing drafts for legal documents, creating recipes for certain business processes, and analysing data by asking questions in simple language can actually allow a person with minimal linguistic and logical skills to perform the tasks of an otherwise skilled and learned analyst or designer in today’s world.
Imagine the “low skill, high output at low cost with high speed” revolution this can create. This can allow India to become the “Prompt Factory of the world”. However, this would require strong and wide-scale programmes to be run by government and educational and enterprises alike to run “Prompt Engineering Academies” at a massive scale. This could be similar to how Maharashtra Government once ran MS – CIT program where youth all over the state could enrol for a basic course teaching them elementary computer and IT skills with a certificate that stood for genuine upskilling evidence. Given the proliferation of smartphones and internet connectivity, these programmes could also be run digitally where anyone having access to a mobile phone and internet could also learn such skills and perform remote jobs and earn money by running a “prompt engineering task factory”.
On the other hand, AI innovation, R&D, and AI product startups are another end of the spectrum where higher-end AI applications could be built through government incentives. While there is an ongoing debate among intellectuals on whether India can afford or needs to spend on heavy spends like building large language models on its own, it is clear that whether LLM creation or LLM finetuning and LLM application builds, India needs to get its grip over these things and get a seat at the global stage like it did during the IT revolution in 2000s.
All in all, India needs to rise to the challenge and make a mark in the global AI race, in its own way – the India way – by making democratic and frugal use of AI technology to help the population rise. Let’s hope the Indian budget makes justice to the AI allocation by staying true to these expectations.
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The writer is partner, technology consulting, EY India. Views expressed are personal.
