Over the last five years, we have seen an unprecedented surge in electric vehicle (EV) adoption in India. With EV sales crossing the 2 million mark as of January 2025, and the government pushing ambitious targets under PM E-Drive, FAME II, and state EV policies, we are at a pivotal moment in our electric mobility journey.
While there is a massive push due to subsidies, climate consciousness, and rising fuel prices, there’s a widening hole in this transition that could derail the momentum: we are investing heavily in building EV charging stations without paying enough attention to making them intelligent. The growing population and vehicle ownership will require smart systems infrastructure. So, it’ll not just be about how many charging stations we set up across the country, but a smarter way to discover and manage them, because building EV charging infrastructure alone cannot fulfill those needs.
So, what’s the real problem?
In many Indian cities, particularly Tier 1 and 2 cities, finding a charging station, more specifically, finding one that works with no queue and offers compatible connectors, is the biggest challenge. Currently, we’re just adding thousands of chargers, both public and private, across cities, highways, and smaller towns, without solving for accessibility, reliability, and user experience. This is causing the investment to go underutilized. Moreover, it’s causing the stations to lie idle while users still remain anxious due to a lack of real-time data and interconnectivity.
Moreover, startups working in the EV ecosystem in India are majorly focused on rollout targets, charger types, port compatibility issues, or fast-charging systems, but what’s missing is the layer of software that could power discovery, reservation, dynamic pricing, energy management, and station analytics.
This makes it even more crucial that we invest in intelligent-first infrastructure to encourage EV adoption, especially for four-wheeler vehicles, which are relatively slow in the country.
Why do we need intelligence for EV Infrastructure?
In traditional fuel retail, everything is easily accessible. There are thousands of fuel stations, visible from metres away, easily findable on apps like Mappls or Google Maps, with backlit signage displaying the types of fuel available, and human experience calculating how long it’ll take to fuel up. Moreover, the operators built their efficiency around predictability and standardization to improve the customer experience all year round.
EV charging, in all those terms, is way more nuanced due to the variety of connectors, charging speeds, user interfaces, and payment systems, all of which contribute to a fragmented experience. Furthermore, adding issues like real-time availability, wait times, and breakdowns makes the experience less convenient. All of this has led to range anxiety, a lack of faith in the overall EV ecosystem, and ultimately a loss of customer base.
So, this is where we need intelligence:
Discoverability:
A charging station not listed on a digital map might as well not exist. We need to ensure discoverability, regardless of the network, brand, or ownership. This will only be possible if charge point operators, aggregators, OEMs, and navigation platforms integrate with open APIs and standardized data protocols.
While some stations have listed themselves on discovery platforms, several are still missing, especially from smaller towns. The Ministry of Power has already taken steps by publishing centralized charging infrastructure databases, but we need nationwide real-time updates as a norm, not a luxury.
Utilization through interoperability:
EV charging stations require significant financial investment, and staying idle throughout the day adds to the cost burden. The problem here is that the underused chargers are a problem not because of low demand, but because of non-interoperable software and poor visibility. If we ensure interoperability, both at the software and hardware levels, we can empower different EVs and different networks to work together seamlessly. All the while ensuring that their resources are utilized and no customer goes away.
Moreover, the recent inclusion of EV infrastructure in the Harmonised Master List of Infrastructure by the government is a progressive step.
Planning based on user experience:
For most public and private stakeholders, the current narrative is centered on capital expenditure: how many chargers, at what cost, in how many cities. But what we need to start asking is: How many of these are actually being used? How often? By whom?
User behavior data, like preferred charging hours, frequency, idle times, and payment methods, should inform everything from charger placement to pricing models. This data-led planning is what will turn infrastructure into value.
Making predictive maintenance mandatory:
Part of the intelligence over investment approach would involve planning in advance or installing software that predicts potential downtime. We can not let EV charging infrastructure be part of the ‘build it and forget it’ syndrome, because the real problem then wouldn’t be a station going offline, but it would be when a user discovers it too late.
We’ll need intelligent charging networks that use data analytics and IoT to monitor station health continuously, which could track heat signatures, voltage irregularities, usage cycles, and wear-and-tear patterns. This will allow operators to service high-risk units before breakdowns occur proactively. If we don’t build such a network, we risk thousands of chargers lying dysfunctional with no way for users or operators to know until complaints pile up.
While the Bureau of Indian Standards (BIS) has already issued guidelines that proactive analytics and software alerts must become standard across all public charging infrastructure, this should also be equally applicable to the growing private charging infrastructure.
Load management will be crucial:
As more EVs come online, especially fleets, we’ll see an even greater pressure on the grid, especially during peak hours for electricity consumption. Without smart load balancing, we risk straining and destabilizing our grid.
Intelligent stations equipped with dynamic load management can optimize charging speed based on real-time grid conditions, time-of-day pricing, and even renewable energy availability. This doesn’t just prevent brownouts, but it creates a more sustainable ecosystem where EVs are assets to the grid, not liabilities.
Moreover, we could implement peak load shaving and smart tariff structures if charging stations are connected to a central, intelligent system, one that can respond dynamically rather than operate on a static schedule.
Commercial fleets will further accelerate intelligent infrastructure
While conversations around EV charging often focus on private vehicles, it’s commercial fleets, such as delivery vans, ride-hailing cars, and transport vehicles, that will ultimately shape how charging networks evolve. These fleets operate on fixed routes, adhere to tight schedules, and experience regular downtimes, making them ideal candidates for smart charging infrastructure.
On one hand, private vehicles can charge once at home and drive to and from their destinations without needing a second charge. In contrast, commercial fleets that rely on their vehicles for income face a different situation. It’s the fleets that could push the charge point operators to maintain high standards, as the fleet operators don’t just bring consistent demand, but they also bring the need for efficiency.
So, when multiple vehicles need to charge throughout the day, charging stations must offer more than just a plug. They should be able to provide features like energy management, real-time availability, dynamic load balancing, seamless billing systems, and guaranteed uptime to become essential. If we want charging networks to keep up, intelligence can’t be an afterthought. It needs to be built into the system from day one.
What could we learn from around the globe?
Countries like Norway and China are among the global leaders in EV adoption. For example, Norway’s high EV penetration didn’t just come from subsidies; instead, it came from well-managed public infrastructure, software-backed payments, and consistent user feedback loops.
Whereas China’s EV boom was driven by standardized connector types, nationwide platform integrations, and city-level mandates for data sharing among all operators.
When it comes to India and its diversity and scale, we cannot simply copy-paste from other countries, but we can definitely learn from them while building smart and intelligent systems from Day 1. We don’t have to retrofit old infrastructure, as we can build smart-first systems that integrate seamlessly into existing systems.
The road ahead
To achieve our target of 30% EV penetration by 2030, with 70% in commercial segments, we must shift our focus from investing in EV charging infrastructure to building intelligent systems.
To achieve this, we’ll need a nationwide mandate for real-time charger status visibility, government-supported open-data platforms for charger APIs, uniform standards for smart meters and digital payments, public-private partnerships where intelligence is the foremost priority mandated in any future tenders, and deployment of AI-led load management in high-traffic charging zones.
The EV movement in India will not succeed on infrastructure alone. It will succeed when the experience of discovering, accessing, and trusting a charger is as seamless as filling up petrol.
We don’t just need thousands of new chargers. We need smart ones that talk to each other, learn from data, and serve people, not just policies.
Because in the end, it’s not about how many chargers we build, it’s about how intelligently we operate them.
