What is the story about?
India’s hosting of the AI Impact Summit in February 2026 arrives at a pivotal moment. As the country advances toward its vision of Viksit Bharat, the summit presents a timely opportunity to define how artificial intelligence (AI) can be harnessed to transform urban governance. With cities projected to
contribute nearly 70% of India’s GDP by 2050, and urban populations expected to nearly double, the question is no longer whether urban growth will occur – but whether it will be managed with efficiency, equity, and resilience. This transformation must serve the public good, embedding intelligence into governance systems rather than simply adding more sensors.
The last decade has laid critical groundwork. National urban missions such as the Atal Mission for Rejuvenation and Urban Transformation, Swachh Bharat Mission, Pradhan Mantri Awas Yojana and the Smart Cities Mission have prioritised urban development and improved service delivery. The Smart Cities Mission (2015-25)
delivered more than 8,000 projects worth Rs. 1.64 lakh crore ($18.2 billion), including integrated command centres, smart roads and digital classrooms. Yet critiques highlight its top-down design, the creation of exclusive zones, and limited municipal ownership. The lesson is clear: technology without governance capacity risks deepening divides. As India prepares for its next phase of city-making and urban rejuvenation, AI must be deployed in ways that strengthen local institutions and build citizen trust.
India is uniquely positioned to lead this shift. Over 56% of metro adults in India already
use generative AI tools – the highest share in the Asia Pacific region. Bengaluru hosts nearly a quarter of India’s digital workforce, making it one of the world’s leading AI talent hubs. Combined with open data platforms and a vibrant ecosystem, India has the ingredients for intelligent governance. The challenge lies in connecting these national strengths with the everyday realities of municipal administration, when fragmented data sets and limited capacity often constrain innovation.
Global experience underscores that technology alone is insufficient; governance capacity is decisive. Singapore’s
Smart Nation strategy was built over decades, beginning with civil service computerisation in the 1980s, evolving through the IT 2000 plan in 1992, and leading up to the Smart Nation initiative in 2014. Its success lies in long-term investment in data infrastructure, open-data, and whole-of-government integration. In 2023, Singapore advanced its AI strategy with a focus on continuously improving public service delivery. Barcelona’s civic data commons reframed urban data as a public good, granting residents control over their data. New York City’s AI
Action Plan (2023) introduced algorithm registries, bias audits, and an Office of Algorithmic Data Integrity, ensuring accountability in public ‑sector deployments. Most recently, the Global Observatory for Urban Artificial Intelligence, GOUAI (2025), launched by the Barcelona Centre for International Affairs alongside the cities of Barcelona, Amsterdam and London, in partnership with UN-Habitat, promotes ethical urban AI practices and applications worldwide. These examples highlight the importance of institutional design, transparency, and citizen trust—principles India must embed as it scales AI across its cities.
For India, the first priority is to build a long-term urban data infrastructure. For example, urban transport data remains fragmented across metro rail corporations, municipal bus services and traffic police departments, with little interoperability – a clear barrier to AI-enabled mobility solutions. India must invest in reliable, integrated and independently verifiable urban data systems, akin to Singapore’s decades-long efforts. Without this foundation, AI risks inefficiency, bias, and fragmentation. A sustained commitment to data quality and interoperability will be the bedrock of intelligent urban governance.
Second, India should localise the IndiaAI Mission for cities. Approved in 2024 with a Rs. 10,300 crore ($1.14 billion) investment, the IndiaAI Mission focuses on national compute infrastructure, datasets, and startup funding. However, the most tangible impact of AI will be felt in cities, where governance intersects directly with citizens’ lives. Bridging IndiaAI for urban transformation would multiply returns for both. Identifying IndiaAI–Urban as a priority pillar would allow AI assets to be curated for municipal use, enabling vetted models for traffic management, waste collection, grievance redressal, and citizen service delivery.
Third, India should launch an Urban AI Challenge. Startups should maintain civic assets, urban flood risk alerts, public safety, and multilingual citizen services. Winning pilots could receive joint IndiaAI–MoHUA funding and be mandated to open‑source their models, ensuring replication across cities. This would not only accelerate adoption but also democratize access to AI solutions, creating predictable procurement pathways for innovators while embedding transparency into the system.
Fourth, India should create a repository of city-specific use cases to disseminate proven solutions nationwide. A national repository, aligned with initiatives like GOUAI, would allow municipalities to learn from each other and adopt ethical AI practices more quickly. This would accelerate diffusion, reduce duplication, and ensure that smaller cities benefit from innovations pioneered in larger metros.
The strategic convergence of AI and urban rejuvenation is clear. For AI, cities provide real-world testbeds and measurable outcomes. For cities, AI offers analytical depth and citizen-centric adaptability. For startups, predictable procurement pathways emerge. For citizens, transparency and fairness are institutionalised. India’s next urban transformation will not be about more sensors—it will be about smarter linkages between missions, adaptive intelligence, and citizen trust. If India seizes this moment, it can set a global benchmark for inclusive and intelligent urban governance, defining how the world’s fastest urbanising‑ democracy uses AI for the public good.
Bhawna Prakash is Adjunct Fellow (non-resident) and former Senior Fellow with the Chair on India and Emerging Asia Economics at the Centre for Strategic and International Studies (CSIS) in Washington D.C.
The last decade has laid critical groundwork. National urban missions such as the Atal Mission for Rejuvenation and Urban Transformation, Swachh Bharat Mission, Pradhan Mantri Awas Yojana and the Smart Cities Mission have prioritised urban development and improved service delivery. The Smart Cities Mission (2015-25)
India is uniquely positioned to lead this shift. Over 56% of metro adults in India already
Global experience underscores that technology alone is insufficient; governance capacity is decisive. Singapore’s
For India, the first priority is to build a long-term urban data infrastructure. For example, urban transport data remains fragmented across metro rail corporations, municipal bus services and traffic police departments, with little interoperability – a clear barrier to AI-enabled mobility solutions. India must invest in reliable, integrated and independently verifiable urban data systems, akin to Singapore’s decades-long efforts. Without this foundation, AI risks inefficiency, bias, and fragmentation. A sustained commitment to data quality and interoperability will be the bedrock of intelligent urban governance.
Second, India should localise the IndiaAI Mission for cities. Approved in 2024 with a Rs. 10,300 crore ($1.14 billion) investment, the IndiaAI Mission focuses on national compute infrastructure, datasets, and startup funding. However, the most tangible impact of AI will be felt in cities, where governance intersects directly with citizens’ lives. Bridging IndiaAI for urban transformation would multiply returns for both. Identifying IndiaAI–Urban as a priority pillar would allow AI assets to be curated for municipal use, enabling vetted models for traffic management, waste collection, grievance redressal, and citizen service delivery.
Third, India should launch an Urban AI Challenge. Startups should maintain civic assets, urban flood risk alerts, public safety, and multilingual citizen services. Winning pilots could receive joint IndiaAI–MoHUA funding and be mandated to open‑source their models, ensuring replication across cities. This would not only accelerate adoption but also democratize access to AI solutions, creating predictable procurement pathways for innovators while embedding transparency into the system.
Fourth, India should create a repository of city-specific use cases to disseminate proven solutions nationwide. A national repository, aligned with initiatives like GOUAI, would allow municipalities to learn from each other and adopt ethical AI practices more quickly. This would accelerate diffusion, reduce duplication, and ensure that smaller cities benefit from innovations pioneered in larger metros.
The strategic convergence of AI and urban rejuvenation is clear. For AI, cities provide real-world testbeds and measurable outcomes. For cities, AI offers analytical depth and citizen-centric adaptability. For startups, predictable procurement pathways emerge. For citizens, transparency and fairness are institutionalised. India’s next urban transformation will not be about more sensors—it will be about smarter linkages between missions, adaptive intelligence, and citizen trust. If India seizes this moment, it can set a global benchmark for inclusive and intelligent urban governance, defining how the world’s fastest urbanising‑ democracy uses AI for the public good.
Bhawna Prakash is Adjunct Fellow (non-resident) and former Senior Fellow with the Chair on India and Emerging Asia Economics at the Centre for Strategic and International Studies (CSIS) in Washington D.C.
