Urban inequality is shaping the future of cities globally as much as technological advancements. Urban poor have lived through the industrial revolution, digital revolution, dot-com era, and now the fourth industrial revolution, with each era promising social and economic mobility as an answer to intergenerational inequality. Can Artificial Intelligence (AI) present a breakthrough in the cycle of urban inequality? We surmise the answer is yes, provided AI is used not as a remedy but as an amplifier to reach the last one first.

As the world’s first Global South host of the AI Summit, India’s ambition to position itself as a leader in inclusive AI is unmistakable. India rightly focused on AI’s impact in seven areas: Human capital, social empowerment, safe AI, resilience, science, democratising resources, and economic growth. Now, it’s time that the tech giants, governments, and international organisations align AI mandates with the promise of leave-no-one-behind in urban India.

We put forth one ask from each of these three powerful stakeholders to resolutely commit to address stubborn development challenges.

One, make urban data a public good and AI a governance multiplier. India’s flagship urban missions, including, PMAY, AMRUT, SBM, and SCM, have invested heavily in digital infrastructure, geospatial tagging, dashboards, and a slew of tools offered by technology partners. When complemented with the national geospatial mission and national urban digital mission, collectively these unparalleled investments in urban digital architecture can, in theory, unlock the development efficiencies. However, much of this data architecture remains fragmented, siloed and incompatible across different platforms and missions. Furthermore, data are inaccessible to researchers, communities and innovators.

Cities such as New York, London, Barcelona and Singapore, among others, have embraced open data and given public access to geospatial data, real-time APIs and statistics on city networks and built-assets down to the building footprints, bike points, car occupancy status. In doing so, cities have empowered civic innovation ecosystems and its social impact. According to a study by McKinsey, open data could add more than $3 trillion to the global economy.

Why should urban India, home to more than 3,000 urban local bodies, not do the same?

Open, interoperable urban datasets — land records, building approvals, infrastructure inventories, climate risk layers, grievance logs — would unlock economic and social innovation. If urban missions mandated public data standards and AI-enabled interoperability across departments, planners could simulate densification scenarios, entrepreneurs could design cooling solutions for heat-stressed wards, and civil society could hold infrastructure investments accountable.

Data transparency is not a threat to governance; it is a multiplier of governance capacity. Without open standards, every new “digital-twin” risks becoming a one-city showcase — a fashionable pilot — rather than a scalable national reform.

Two, put the principle of leave no one behind (LNOB) first and AI for spatial equality and environmental justice. International organisations have unequivocally expressed the strategic importance of urban India in achieving the global social, economic, and environmental goals. By virtue of their commitment to LNOB, international organisations are also uniquely positioned to bring the entire weight of their technical, financial, and institutional prowess to unconditionally target the most disadvantaged urban groups first.

If “AI for All” slogan is to carry meaning, it must begin where risk converges for the urban poor— overheated neighbourhoods, flood-prone settlements, polluted drinking waters, and housing clusters next to landfills. The question for international organisations is not how well they advocate for sophisticated AI models. It is how well these bodies lead by example and invest in robust AI tools to showcase their accountability, transparency, sustainability and collaboration in the development sector first.

Over 26 UN agencies, multilateral and bilateral institutions, and global think tanks have established a strong presence in India. However, the operational presence of these institutions, projects, investments, and target groups are either publicly unavailable or hidden behind reams of documents. International organisations must commit to a composite dashboard that compiles their projects and pipelines as spatial data that is accessible to all.

The objective is not to admire dashboards. It is to redirect capital towards communities that face compounding socio-economic and climate risks, i.e. as a priority, cool vulnerable wards, prevent the next flood in slums, and expand dignified shelter at scale — across their entire portfolios, not just the headline few.

LNOB must become an algorithmic design principle for environmental justice and spatial equality, not just a slogan in policy documents.

Three, embrace AI as an influencer. Meta’s chief AI officer Alexandr Wang gushed that “GDP of AI [is] set to grow exponentially” at a fireside chat with former British Prime Minister Rishi Sunak at the AI Impact Summit. Indeed, the market capitalisation of the tech giants is already comparable to the GDP of most developed countries. With palpable excitement, tech CEOs shared their vision on AI’s potential to tackle humanity’s greatest challenges and open the doors to a new era for social good.

Undeniably, big data and AI models are being deployed in urban development as use cases for digital twins, predictive zoning, smart permitting, spatial governance, demand forecasting, and much more, to good effect. They can test trade-offs in real time: What happens to heat stress if reflective roofing becomes mandatory in EWS clusters? How does mixed-income zoning alter land values and commute burdens? Also, simulate the impact of zoning reform, transit-oriented development and higher floor-area ratios on affordable housing supply and infrastructure load.

However, the challenge is not innovation in one metropolis; it is in institutionalisation across thousands of municipalities. AI-enabled planning innovations as a social good can overcome the binding constraints of municipal capacity.

Big tech has proven the ability of bringing together half of the world’s population on one platform — trends that reach millions within hours, customised feeds for billions, connecting influencers with the most ardent followers. Big tech can commit with unrelenting dedication to create a platform to connect proven innovations with the right partners to scale-up and fund, use algorithms to push innovations into the feeds of implementers, donors, and facilitate cross-disciplinary partnerships at a global scale.

With responsible adoption of digital technology which adheres to privacy guardrails, data security, and ethical considerations, AI can be governed as public infrastructure. AI will not manufacture land or erase inequality. But AI infrastructure that is open, interoperable and places equity first can sharpen decisions, expose blind spots and shift capital towards those historically left behind. The test is if “welfare for all and happiness of all” can be turned into policy. Or else, the promise will stay as summit poetry.

Parul Agarwala is an independent urban development practitioner with previous professional stints at UN, The World Bank, and New York City Planning Department. Priyanka Kochhar is a sustainability policy advisor and co-founder of The Habitat Emprise Foundation, working at the intersection of climate action, green infrastructure, and urban development. The views expressed are personal

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