An India-specific AI approach – developed in India for India – is essential to boost EV adoption among the masses to the next level.
When it comes to India’s shift to electric mobility, the issue is no longer one of adoption but of intelligence. Take the numbers: EV sales have gone from a mere 50,000 in 2016 to over 2.08 million last year, and there are now some 6.5 million such vehicles on Indian roads. With an eye on hitting 25% penetration by 2030, the country has been aggressive in its targets. But as India builds out a more digitally connected mobility ecosystem, there is a blind spot that is not getting enough attention. The problem is that the intelligence at the heart of most of these EVs was never designed for India.
You can put together the batteries here and manufacture the vehicle here, but the algorithms behind them – the ones that handle everything from route optimisation and predictive maintenance to rider assistance and fleet management – are typically running on data from elsewhere entirely. For a nation that prides itself on self-reliance and technological sovereignty, being so dependent is a strategic weakness, and frankly, an opportunity left on the table.
India’s Roads: India’s Intelligence
Context defines the whole essence of Artificial Intelligence (AI). It is whatever it learns from data, patterns, and surroundings. But in India, the question of mobility gives rise to conditions that one will not experience anywhere else in the world.
Consider a two-wheeler on the roads of Mumbai, Delhi, Bengaluru and Lucknow. It has to operate in an environment not captured by global datasets. While in other countries the traffic consists mostly of vehicles and a handful of pedestrians, the Indian traffic includes cars, buses, two-wheelers, people, livestock, handcarts, and other means of transportation on the same road. There is weather too, which changes suddenly. And then there is the roads. The way people ride and drive here is dynamic and adaptive, and at times unpredictable.
Put an AI system in India that was trained on the orderly highways of Europe, the road grids of North America or the traffic of East Asia, and you will see its limitations. A battery management system calibrated to European driving habits might overestimate range in India’s stop-and-go traffic. An algorithm for predictive maintenance that has only been tested in temperate climates will not account for the thermal stress an Indian summer imposes on a vehicle. Even the most sophisticated rider assistance systems can be stumped by the intricacies of a crowded urban corridor.
What you end up with is suboptimal intelligence, not just lower efficiency. That is why India cannot simply import models for its foray into AI-driven and future mobility. The nation needs to develop its own indigenous intelligence, one grounded in its data, infrastructure, and how its fellow citizens actually operate on the road.
Indigenous Intelligence: New Powertrain
There was a time when an automaker’s mettle was judged on the strength of its engine. Today, with the advent of EVs, software has become the key point of difference. The mobility leaders of tomorrow will be made or broken not just by their manufacturing scale or battery chemistry, but by how smart their vehicles’ intelligence is.
You see the government’s hand in this with the IndiaAI Mission, which has been given an outlay of Rs 10,371 crore to flesh out the “Making AI in India and Making AI Work for India” vision. And NITI Aayog’s National Strategy for Artificial Intelligence has already flagged Smart Mobility and Transportation as a sector ripe for transformative impact on the economy.
The upshot for the industry is significant. AI offers the means to do things one could not before: optimise battery use in real time based on local traffic, anticipate when a component is about to fail, or allow fleet operators to position their vehicles where demand is forecast. It can even orchestrate traffic to ease congestion in cities and project charging needs across them.
Data Sovereignty: Strategic Imperative
We are set to see an unprecedented surge in mobility data over the coming ten years. Take any connected EV, and it churns out a wealth of information: how the vehicle is ridden, its battery and energy use, charging habits, the state of the road, and even traffic. Put it all together, and one has the raw material for tomorrow’s mobility intelligence.
That brings us to the strategic issue at hand: who will be the owner of the intelligence derived from Indian mobility data? There is a danger for India if the output of its millions of vehicles is put to work training some foreign algorithm; we could end up as mere consumers of next-gen technology instead of the ones making it.
But handle the data with care and use it to build AI at home, and a different story emerges. The nation gets a virtuous cycle. Models honed to local conditions are more precise, which, in turn, leads to better performance and a better user experience. As adoption picks up, so does the data, and with it the quality of the intelligence. It is the kind of feedback loop that has made the world’s top tech firms platform economies. India can do the same with mobility. It is this conviction – that the intelligence must be built here, on Indian data – that shapes how we are building Magron.
Conclusion: Make in India to Think in India
There is more to India’s mobility plans than simply going electric. What we are after is an innovation ecosystem with the heft to go head-to-head on the world stage. In India, the EV market has all the makings of a fast grower over the coming ten years, thanks to a combination of policy backing, local manufacturing and a drive to put in place the necessary charging infrastructure. Industry projections suggest annual demand could reach 11 or 12 million vehicles by 2030, which in turn will require well over a million chargers. To handle that kind of volume, the country needs smart intelligence at every level of the operation, from the energy grid and urban transport to the fleets and the vehicles themselves.
In short, what India needs to focus on is not just “Made in India” but “Thought in India” platforms. One can already spot the change taking place. Government-backed AI research programmes and autonomous mobility efforts are demonstrating what local innovation can achieve – early autonomous mobility prototypes are already being tested on Indian roads, showing that when it comes to Indian traffic, homegrown intelligence beats imported notions any day.
So, for India, the next step in electric mobility is as much about cognition as it is electrification. The country that can marry EV production with its own AI know-how won’t be a passive player in the global revolution; it will be one of the ones setting the terms. As India moves up the ranks of electric mobility, the focus must shift from assembling vehicles here to developing the intelligence for them. After all, in a world of software-defined mobility, the battery isn’t necessarily the most important part of an EV – the brain is.
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