In India, a pothole is rarely just a pothole. It is a metaphor, a mood and sometimes, a meme. It is the reason your cab driver mutters about karma and your startup founder misses a pitch meeting because the expressway has turned into a swimming pool. But what if roads could detect their own distress, predict failures before they happen, and even suggest how to fix them?

That is not science-fiction but the emerging reality of AI-powered infrastructure.

According to KPMG’s 2025 report AI-powered road infrastructure transformation- Roads 2047, artificial intelligence is slowly reshaping how India builds, maintains, and governs its roads. From digital twins that simulate entire highways to predictive algorithms that flag out structural fatigue, the country’s infrastructure is beginning to show signs of cognition.

From concrete to cognition

India’s road network spans over 6.3 million kilometers – second only to the United States. As per KPMG, AI is now being positioned not just as a tool but as a transformational layer. Technologies like Geographic Information System (GIS), Building Informational Modelling (BIM) and sensor fusion are enabling digital twins – virtual replicas of physical assets that allow engineers to simulate stress, traffic and weather impact in real time. The National Highway Authority of India (NHAI) has already integrated AI into its Project Management Information System (PMIS), using machine learning to audit construction quality and flag anomalies.

Autonomous infrastructure in action

Across urban India, infrastructure is beginning to self-monitor. Pune’s Intelligent Traffic Management System (ITMS) and Bengaluru’s adaptive traffic control systems are early examples of AI-driven urban mobility.

Meanwhile, AI-MC, launched by the Ministry of Road Transport and Highways (MoRTH), uses GPS-enabled compactors and drone-based pavement surveys to optimise road construction.

Beyond cities, state-level initiatives are also embracing AI for infrastructure monitoring. As reported by ETInfra earlier, Bihar’s State Bridge Management & Maintenance Policy, 2025 employs AI and machine learning for digital audits of bridges and culverts. Using sensors, drones, and 3D digital twins, the state has surveyed over 12,000 culverts and 743 bridges, identifying damaged structures for repair or reconstruction. IIT Patna and Delhi have been engaged for third-party audits, showing how AI can extend beyond roads to critical bridge infrastructure in both urban and rural contexts.

While these examples demonstrate the potential of AI-powered maintenance, challenges remain. Predictive maintenance, KPMG notes, could reduce lifecycle costs by up to 30 per cent and improve asset longevity, but much of rural India—nearly 70 per cent of the network—still relies on manual inspections and paper-based reporting.

Governance and the algorithm

India’s road safety crisis is staggering: over 1.5 lakh deaths annually. AI could be a game-changer. KPMG estimates that intelligent systems can reduce emergency response times by 60 per cent, and improve traffic efficiency by 30 per cent. AI also supports ESG goals— enabling carbon modeling, EV corridor planning, and sustainable design.

But technology alone won’t fix systemic gaps. The promise of AI hinges on institutional readiness – spanning urban planning, enforcement, and civic engagement.

While NITI Aayog has outlined a national AI strategy, and MoRTH has initiated digital reforms, state-level adoption remains fragmented. Some states have set up AI cells within their PWDs; others lack the technical capacity or policy mandate.

KPMG calls for a unified governance framework — one that enables interoperability, safeguards data, and fosters public-private partnerships. Without it, India risks building smart systems on shaky foundations.

As India looks towards 2047, the road ahead is both digital and political. And if AI can help us listen to our roads, perhaps we’ll finally learn to fix them before they speak in potholes.

This would be Mistral AI’s first fundraise since a June 2024 round in which it was valued at €5.8 billion, Bloomberg reported Wednesday (Sept. 3), citing unnamed sources.

Mistral AI did not immediately reply to PYMNTS’ request for comment.

According to the Bloomberg report, Mistral AI, which is based in France, is developing a chatbot called Le Chat that is tailored to European user as well as other AI services to compete with the dominant ones from the United States and China.

It was reported on Aug. 3 that Mistral AI was targeting a $10 billion valuation in a funding round in which it would raise $1 billion.

In June, it was reported that the company’s revenues had increased several times over since it raised funds in 2024 and were on pace to exceed $100 million a year for the first time.

PYMNTS reported in June 2024, at the time of Mistral AI’s most recent funding round, that the AI startup raised $113 million in seed funding in June 2023, weeks after it was launched, secured an additional $415 million in a funding round in December 2023 in which it was valued at around $2 billion, and then raised $640 million in the round that propelled its valuation to $6 billion.

“We are grateful to our new and existing investors for their continued confidence and support for our global expansion,” Mistral AI said in a post on LinkedIn announcing the June 2024 funding round. “This will accelerate our roadmap as we continue to bring frontier AI into everyone’s hands.”

In June, Mistral AI and chipmaker Nvidia announced a partnership to develop next-generation AI cloud services in France.

The initiative centers around building AI data centers in France using Nvidia chips and will expand Mistral’s businesses model, transitioning the AI startup from being a model developer to being a vertically integrated AI cloud provider, PYMNTS reported at the time.

Portland Public Schools folded some guidance on artificial intelligence into its district technology policy for students and staff over the summer, though some district officials say the work is far from complete.

The guidelines permit certain district-approved AI tools “to help with administrative tasks, lesson planning, and personalized learning” but require staff to review AI-generated content, check accuracy, and take personal responsibility for any content generated.

The new policy also warns against inputting personal student information into tools, and encourages users to think about inherent bias within such systems. But it’s still a far cry from a specific AI policy, which would have to go through the Portland School Board.

Part of the reason is because AI is such an “active landscape,” says Liz Large, a contracted legal adviser for the district. “The policymaking process as it should is deliberative and takes time,” Large says. “This was the first shot at it…there’s a lot of work [to do].”

PPS, like many school districts nationwide, is continuing to explore how to fold artificial intelligence into learning, but not without controversy. AsThe Oregonian reported in August, the district is entering a partnership with Lumi Story AI, a chatbot that helps older students craft their own stories with a focus on comics and graphic novels (the pilot is offered at some middle and high schools).

There’s also concern from the Portland Association of Teachers. “PAT believes students learn best from humans, instead of AI,” PAT president Angela Bonilla said in an Aug. 26 video. “PAT believes that students deserve to learn the truth from humans and adults they trust and care about.”

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