India’s bold vision of Viksit Bharat@2047 is rooted in collective ambition to emerge as a fully developed, self-reliant nation driven by inclusive growth, innovation, and sustainability. It envisions an India where economic strength is matched by social equity, where technology powers public good, and where progress is measured not just in GDP but in the quality of life of every citizen. This vision demands a fundamental shift in how we build, govern, and grow. As the nation charts its course, the journey is neither simple nor linear. Rapid urbanisation, resource constraints, and climate vulnerabilities continue to pose complex challenges that demand bold, systemic solutions. As cities swell and infrastructure demands intensify, the question is no longer whether we can build more, but whether we can build smarter, greener, and more resilient systems that align with long-term national goals.
This is where technology steps in – not as a support function, but as a strategic driver of transformation. From artificial intelligence (AI) and digital twins to integrated data platforms and smart mobility systems, digital innovation is reshaping the DNA of urban India. These tools are helping us move from reactive infrastructure to predictive planning, where cities can optimise energy use, simulate growth patterns, and build resilience into every layer of their design.
AI and data driving urban transformation
India’s ambition to become a developed nation by 2047 will be tested in its cities. These urban centres will account for 70% of the country’s GDP by 2030, but they also face rising climate risks, infrastructure strain, and growing population density. This duality of economic promise and environmental peril demands a radical rethinking of how Indian cities are planned, built, and sustained.
The solution lies not just in building more, but in building differently. And at the centre of this transformation is AI, not as a futuristic tool, but as a present-day enabler of smarter decisions and faster responses and more sustainable outcomes. Across sectors, AI is already reshaping the urban playbook:
- AI is transforming how we manage energy and emissions by powering intelligent building systems that automatically optimise lighting, cooling, and ventilation to reduce consumption and carbon output.
- In construction, AI-driven simulations help architects and engineers evaluate the longevity and environmental impact of materials during the design phase, ensuring sustainability is built in from the start.
- Urban mobility is being revolutionised by AI through real-time traffic analysis and smart routing, which are reducing congestion and supporting the adoption of electric and autonomous vehicles.
- To strengthen climate resilience, AI is enabling cities to anticipate extreme weather events such as floods and heatwaves, allowing for proactive design of adaptive infrastructure and emergency response systems.
Building a greener India with AI
As India lays the foundation for a developed, self-reliant future, sustainability cannot remain a peripheral goal; it must become the very bedrock of our infrastructure strategy. In a nation where over 50% of the infrastructure that will exist by 2047 is yet to be built, we are presented with a once-in-a-generation opportunity – to embed sustainability by design, not retrofit it as an afterthought.
This is not just about lowering emissions; it’s about redefining how we think about infrastructure—its materials, its lifespan, its circularity, and its carbon footprint. AI is emerging as the game-changer that empowers us to reimagine construction and urban design through the lens of climate responsibility.
Today, AI is helping India transition from intention to action in sustainability:
- Materials intelligence: AI-powered design tools are helping architects and engineers select materials that are locally sourced, low-impact, and recyclable, reducing embodied carbon before the first brick is laid.
- Designing for zero waste: Generative design algorithms are optimising building shapes and layouts to minimise material waste while maximising energy efficiency—ensuring every square foot built serves a long-term purpose.
- Energy modelling at scale: AI is enabling entire city districts to be modelled for energy use, daylighting, and thermal comfort, allowing green norms to be not only met but exceeded.
- Lifecycle carbon tracking: Smart analytics are tracking carbon emissions across the entire lifecycle of buildings and infrastructure, from construction to decommissioning—ensuring transparency, accountability, and course correction in real time.
Digital twins: Powering smarter cities through AI
At the intersection of AI and infrastructure lies one of the most powerful tools of urban transformation – the digital twin. These intelligent, dynamic replicas of physical assets are redefining how India builds, operates, and sustains its cities.
By integrating real-time data from IoT sensors with advanced AI models, digital twins are enabling a shift from reactive development to predictive design. City planners and engineers can now simulate energy usage, optimise building orientation, test structural resilience, and predict maintenance needs before projects are built. As climate risks escalate and infrastructure demands intensify, AI-powered digital twins offer a new paradigm: cities that think, adapt, and evolve. From reducing carbon emissions and resource waste to enhancing citizen experience and operational efficiency, these virtual models are becoming the digital backbone of urban India.
Conclusion
The road to Viksit Bharat will not be paved by legacy thinking; it will be engineered by intelligence, foresight, and bold innovation. AI-infused technologies like digital twins are no longer optional; they are foundational to building cities that are sustainable by design, resilient by default, and agile in the face of disruption. As we reimagine the cities of tomorrow, we can architect a future where data drives decisions, where infrastructure adapts in real time, and where every structure built is a step toward national transformation.