India’s Roads Get Smarter: AI Could Spot Potholes Before They Exist

India’s 6.3-million-kilometer road network is among the largest in the world, serving as the backbone of commerce, connectivity, and economic growth. Yet, it faces recurring challenges such as deteriorating road quality, slow response to maintenance issues, and one of the highest rates of road fatalities globally.

A recent KPMG report, AI-Powered Road Infrastructure Transformation—Roads 2047, examines how Artificial Intelligence (AI) can transform the way India builds, monitors, and governs this critical public asset.

The report underscores the deployment of digital twins, enabled by Geographic Information Systems (GIS), Building Information Modelling (BIM), and sensor fusion. These digital replicas of physical roads and highways allow for real-time simulation of stress, traffic, and weather impacts.

The National Highways Authority of India (NHAI) has already deployed AI in its Project Management Information System (PMIS), automating construction audits and enabling proactive intervention in cases of quality deviation.

Initiatives such as the Ministry of Road Transport and Highways’ AI-MC platform use GPS-enabled compactors and drone-based pavement surveys to optimize road construction. State-level policies, including Bihar’s State Bridge Management & Maintenance Policy (2025), leverage AI and 3D modeling for digital audits of bridges and culverts, with academic institutions like IIT Patna and IIT Delhi engaged for third-party verification.

India continues to report over 150,000 road fatalities annually. According to KPMG, AI-enabled predictive maintenance and Intelligent Traffic Management Systems (ITMS) could reduce emergency response times by up to 60% and improve traffic efficiency by 30%. This would significantly advance public safety objectives and support Environmental, Social, and Governance (ESG) goals, including carbon modeling and sustainable road design.

Despite these advancements, several challenges persist. Approximately 70% of India’s roads are in rural areas, where inspections are still conducted manually and reported on paper. State-level AI adoption remains fragmented, with varying levels of technical capacity and policy readiness.

The report calls for a national governance framework that ensures:

• Interoperability between state and central systems,
• Data security and privacy safeguards,
• Clear policy mandates for AI adoption, and
• Public-private partnerships to drive innovation and funding.

Such a framework must align with India’s broader AI strategy (as outlined by NITI Aayog) and with global best practices on ethical and transparent AI deployment.

The integration of AI into India’s road infrastructure marks a profound shift from concrete to cognition. However, technology alone cannot bridge systemic gaps. The success of AI-driven infrastructure will depend on the strength of India’s legal and policy frameworks, particularly in ensuring accountability, safeguarding data, and harmonizing governance across states. As India looks toward 2047, the legal road ahead is as critical as the digital one. Without robust frameworks, India risks creating “smart” systems on shaky legal foundations. With them, however, AI could not only reshape roads but also redefine infrastructure governance itself.