India is in the middle of a massive infrastructure overhaul. Through initiatives such as National Infrastructure Pipeline, Smart Cities Mission 2.0 and Gati Shakti, the government is heavily investing in developing world-class urban spaces, energy, transport and public services. Simultaneously, the government’s flagship IndiaAI Mission is focusing on building indigenous artificial intelligence (AI) models and bolstering the country’s digital public infrastructure.
Indian Infrastructure takes a look at how AI is currently being deployed across sectors and the way forward…
In the transport sector, adaptive traffic systems such as Bengaluru Adaptive Traffic Control System adjust signal timings in real time using sensor and camera data, improving flow and reducing emissions. Meanwhile, Maharashtra’s Pune Expressway uses AI to detect violations and automate penalties. In the railways sector, Vande Bharat trains in the Howrah division are using telemetry data to flag issues before breakdowns, improving uptime. Moreover, Indian Railways is adopting AI across multiple operations, from protecting wildlife with an AI-powered intrusion detection system that alerts trains about animals on tracks, to optimising seat allocations post charting using predictive models. It is also using AI to inspect and sort onboard linen, enhancing efficiency and passenger service. Meanwhile, in logistics and freight, AI streamlines cargo flow across dedicated freight corridors and automates operations at ports such as Jawaharlal Nehru Port Trust. At airports, Delhi’s Indira Gandhi International Airport has deployed the unified total airside management system, which uses AI, IoT and radar data to monitor aircraft, ground vehicles and baggage in real time. These systems optimise routing, reduce delays and cut fuel consumption, vital for an economy dependent on fast and efficient supply chains.
AI enables accurate demand forecasting and real-time load balancing in the energy sector, essential for integrating intermittent sources such as wind and solar. For example, Power System Operation Corporation Limited, in collaboration with IIT Delhi, has built AI models for better solar and wind forecasting. At NTPC Limited’s Centre of Excellence, AI analyses turbine sensor data to predict faults. South Bihar Power Distribution Company Limited has partnered with REC Limited and Bidgely to deploy AI and machine learning solutions to curb power theft, improve service delivery and boost operational efficiency. With 5G-enabled grids being piloted, AI will soon support distributed, real-time decision-making across power networks.
Parallelly, technologies such as digital twins and geographic information systems (GIS), powered by AI, can simulate future traffic, population shifts or climate impacts, guiding long-term development. City control centres, such as the AI-integrated ones coming up in Panchkula, Haryana, combine feeds from CCTVs, utilities and citizen services to support predictive governance, identifying issues before they become emergencies. In construction, AI is helping track project timelines, flag potential cost overruns and detect design clashes using digital twins – virtual replicas of infrastructure projects that can be stress-tested in simulation before real-world execution. Recently, Genesys International announced that it will deploy digital twin technology in Hubballi-Dharwad, Karnataka, to boost infrastructure management and governance through precision mapping.
AI is transforming how cities handle one of their most crucial resources. In flood-prone cities such as Patna, Bihar, AI-enabled pump houses automatically activate pumps based on real-time rainfall and water-level data. In Manimajra, Chandigarh, AI manages water flow and pressure using sensors and remote terminal units to reduce leakage and ensure equitable distribution. Bengaluru uses AI to monitor borewell extraction and detect overuse trends. Hospitals in the city are deploying AI dashboards to track water usage, flag leaks and identify conservation opportunities. Finally, India’s telecom sector is undergoing its own AI-powered upgrade. Self-healing networks now analyse usage patterns in real time to adjust parameters, manage traffic and reduce call drops. Predictive maintenance keeps towers and base stations functional with minimal downtime. With 5G roll-out accelerating, AI-based radio access network controllers are being deployed to manage spectrum dynamically, reroute traffic and cut latency. This is essential for next-gen use cases such as smart cities, connected vehicles and industrial automation, all of which rely on low-latency, high-reliability networks. AI also improves customer-facing services. Chatbots trained in regional languages reduce service load. Fraud detection tools flag SIM swap or phishing patterns in real time. Even tower placement and signal propagation are being optimised using AI models, cutting costs and improving coverage.
Overcoming roadblocks
Despite the AI momentum, there are real challenges. Much of India’s legacy infrastructure lacks the sensors, records or digitisation needed to generate clean, usable datasets. Water pipelines, old discom networks and rail infrastructure do not produce the kind of real-time data AI thrives on. A 2024 industry survey found that 43 per cent of IT leaders cited the lack of quality data as a key barrier. Further, many public agencies still rely on outdated manual systems that lack interoperability. AI thrives on interoperability and real-time inputs, but bureaucratic silos often block both. Furthermore, 36 per cent of organisations reported a shortage of in-house AI expertise. Many rely on outsourced or academic partnerships to build and manage AI models, which limits internal capacity building.
What’s next
The real upgrade is building intelligence into the core of infrastructure. Despite current barriers, AI’s role in infrastructure is poised to only deepen. With the roll-out of 5G, IoT and edge computing, infrastructure will become more data-rich. Interestingly, every vehicle, power line and intersection will become a node in a learning system.