For most of the past century, the electricity meter has been the most overlooked object in the Indian home: a whirring dial, a monthly visit from a meter reader, a bill that arrived with little explanation. That era is ending, and quickly.
As of 30 June 2026, 7.24 crore smart meters had been installed across the country, spanning consumer, distribution-transformer and feeder meters. India has committed to 25 crore by FY28. Every one of those devices is a live data point wired into a national grid, and together they are creating one of the largest operational datasets in the world. The question facing utilities, regulators and technology leaders is no longer whether to deploy, but what to do with what the meters are saying.
For Ranvir Singh Rathore, Chief Technology Officer of Genus Power Infrastructure Ltd, the answer begins with a simple premise: the companies building the smart grid must themselves behave like smart organisations. “A company building India’s smart grid must also operate as a smart, data-driven organisation,” says Rathore.
Practising what it deploys
Genus, one of India’s leading smart-metering players, has spent the past few years turning its own house into a showcase for the thesis it sells to utilities. Digital platforms and analytics now run through manufacturing, supply chain, project execution and customer service, with the aim of delivering what Rathore describes as “greater visibility, faster decision-making and stronger operational control.”
On the factory floor, automation and real-time monitoring track production parameters, quality and output. Data from across processes feeds dashboards that surface deviations early. The shift, he says, is from “reactive intervention to more proactive, data-led manufacturing management.”
The same logic applies to management. Rather than relying on retrospective reports, integrated dashboards highlight exceptions, emerging risks and areas needing attention, which is critical when large-scale rollouts span multiple DISCOMs and every stage of execution has a deadline attached.
The backbone of this transformation is Project EnerGize, Genus’s migration from SAP ECC to SAP S/4HANA on RISE. The goal was a more connected operating model with real-time visibility and improved data accuracy. For a business that juggles large-scale manufacturing with AMISP (Advanced Metering Infrastructure Service Provider) projects, that connectivity directly improves planning and execution coordination. “The objective is not simply to digitise individual processes, but to create an integrated digital backbone wherein data flows across functions and enables faster, more informed decisions.”
One architecture, not a collection of systems
Scale is where smart-metering programmes succeed or fail. Millions of endpoints generate billions of readings, across terrain that ranges from dense urban clusters to remote rural feeders. Rathore is blunt about the architectural implication: it “cannot be built as a collection of separate systems but must function as one integrated, resilient operating environment.”
That environment runs from the consumer-end meter, through the communication network and Head-End System (HES), to the Meter Data Management System (MDMS) and cloud infrastructure, and finally into the utility’s core applications. Genus’s own MDMS, Urja+, serves as what Rathore calls “the intelligence layer”, helping utilities monitor network performance, identify communication exceptions and maintain continuity across a vast and varied consumer base.
Connectivity is deliberately heterogeneous. Genus deploys a tailored mix of technologies, including RF mesh, which provides a self-healing communication layer, alongside cellular connectivity, chosen to suit the terrain. Reliability, Rathore stresses, demands more than clever engineering: “we track data completeness and communication consistency meticulously, ensuring insights lead to timely action.”
His framing of the meter’s role is worth noting for any CIO weighing edge-to-cloud architectures: “The smart meter is merely the edge device and the first point in the value chain. The real value unlocks when data flows seamlessly from the field.”
From recording to anticipating: The AI use cases that matter
The commercial case for smart metering rests on what analytics can do with the data. Rathore identifies four areas where DISCOMs stand to gain most.
Loss reduction. By comparing energy supplied with energy billed at different points in the network, analytics can flag abnormal consumption patterns and potential tampering. “This enables DISCOMs to move from periodic, manual checks towards more continuous and data-led identification of potential losses.”
Predictive maintenance. Voltage fluctuations, overloads and other anomalies are early warnings. Spotted in time, they allow utilities to “prioritise intervention before they become larger failures.”
Grid efficiency and planning. Granular load data sharpens demand forecasting and targeted investment, and eases the integration of renewable and distributed energy. The next step, Rathore says, is to move beyond identifying where a problem exists to recommending the response, whether that is load balancing, network reinforcement, transformer augmentation or prioritised field intervention.
Consumer engagement and demand management. Better visibility into usage can, over time, underpin more informed tariffs, demand-response programmes and energy-efficiency initiatives.
AI is the force multiplier across all four. As data volumes balloon, machine learning can automate anomaly detection and generate predictive and prescriptive insight. In Rathore’s words: “The real opportunity is to move from a meter that records what happened to an intelligent grid endpoint that helps utilities anticipate what happens next and determine the most effective action.”
The numbers behind the narrative
Technology claims are cheap; outcomes are not. Rathore points to a national picture that is beginning to validate the approach. According to the latest reported figures for FY21 to FY25:
AT&C losses fell from 21.91% to 15.04%
Billing efficiency rose from 84.08% to 87.59%
Collection efficiency climbed from 92.9% to 97%
He is careful not to over-attribute. Smart metering is “one important contributor within the wider reform programme, alongside feeder segregation, SCADA, distribution-system upgrades and utility process reform.” But the underlying principle is clear: the end-to-end AMI stack converts “raw meter readings into actionable operating information rather than simply collecting data.” For utilities, that translates into more accurate energy accounting, better billing and collections, and faster identification of non-communicating meters or abnormal consumption.
His test for any technology investment is one every CIO will recognise: “Technology delivers value when it improves a real decision.”
Security as an infrastructure issue
When millions of meters become endpoints of the power network, the attack surface changes character. Rathore does not treat cybersecurity as a bolt-on: “A smart meter is a live data point connected to a national grid… Cybersecurity is no longer simply an IT issue. It is an infrastructure and trust issue.”
Genus follows a security-by-design approach, with encryption, access controls, secure data movement, network monitoring and regular security assessments built into the architecture. Internally, that is complemented by controlled access, employee awareness, incident-response preparedness and governance over IT and operational-technology interfaces.
Regulation is catching up. The Central Electricity Authority has notified binding cybersecurity regulations for the power sector, moving the industry from voluntary guidelines to enforceable standards, effective April 2027. “This shift raises the bar for the entire industry,” Rathore says, “and companies that have been building with security at the core, as we have, will be well positioned.” Security, he adds, must “move beyond the perimeter and be embedded across the entire ecosystem.”
Smart Metering 2.0
Where does the meter go next? Rathore is measured about the pace, noting the transition “will happen progressively”, but unambiguous about the direction. The first phase digitised consumption data. The second, which Genus calls Smart Metering 2.0, is about acting on that data in real time, with edge and cloud intelligence working together to detect abnormalities, support predictive asset management and enable faster operational responses.
The meter, in his vision, becomes “an intelligent point of interaction between the consumer, the utility and the grid.”
The next Genus: Beyond the meter
Looking three to five years ahead, Rathore sees Genus evolving “into a broader technology and digital infrastructure partner for the energy ecosystem.” Smart metering stays central, but value will increasingly come “from the intelligence, software and services built around the meter.”
The execution foundation is already in place. Genus aims to install at least 1 crore smart meters during FY27, backed by manufacturing capacity of over 1.8 crore meters annually. All 24 of its AMISP projects have reached Operational Go-Live status, a track record Rathore says “very few companies can match.”
Diversification is under way. On gas, the regulator PNGRB has set a roadmap to 100% smart prepaid coverage across roughly 12 crore connections by FY30, with tenders for 40 to 45 lakh meters expected in FY27 alone. On water, Rathore believes smart metering “will become an even bigger segment than smart electricity meters over the next four to five years,” and notes that Genus has “already made our first moves there.”
The technologies he expects to define the next chapter are AI-driven grid analytics, advanced communication infrastructure enabling real-time grid responsiveness, and the integration of distributed energy resources, so that the meter becomes “the orchestration point for a bidirectional energy economy.”
A grid that anticipates
India is about to wire a quarter of a billion meters into its power network. Whether that becomes the world’s most expensive billing upgrade or the foundation of a genuinely intelligent grid depends on choices being made now, in architecture, in security and in ambition.
Genus has placed its bet. As Rathore puts it: “India has committed to 25 crore smart meters by FY28. Genus intends to be the company that makes that entire foundation intelligent.” If he is right, the humble meter will stop being the thing that tells you what you used, and become the thing that tells the grid what to do next.