India, May 31 -- Across the world, local governments are discovering that artificial intelligence, when oriented toward a civic purpose, can meaningfully transform the quality of public administration. South Korea's Seoul Metropolitan Government has deployed AI-driven citizen complaint triage systems that reduced average resolution times by over 30%, while Barcelona's integrated municipal analytics platform has improved sanitation deployment efficiency across the city's 23 districts. In India, the Union government's AI-enabled National Consumer Helpline reduced average grievance disposal time from 66 days to 48 days within a single year of algorithmic integration. AI in local governance earns its place by improving the operations of institutions that already carry a clear public mission and know what they can and cannot see. The Municipal Corporation (MC) of Chandigarh is one of the most instructive cases in India in this regard. Chandigarh's MC already operates a comparatively mature digital ecosystem, including online property tax systems, e-billing systems, the BIRBAL AI chatbot for citizen services, etc. The MC has for the first time earmarked Rs.12 crore from its Rs.1,712 crore budget specifically toward AI-linked governance improvements. The MC's own House proceedings actually reveal problem statements that may benefit from the application of emerging technology. These recurring frictions can be clubbed across five distinct clusters. The first is multi-department grievance redressal where complaints across sectors become trapped in departmental jurisdictions. The second is fiscal leakage through weak revenue realisation. The third is low budget execution visibility of large capital allocations with contractor bottlenecks, delayed approvals and poor utilisation rates. The fourth cluster concerns sanitation enforcement and vendor regulation and the fifth is environmental accountability. This is precisely where a carefully bifurcated AI deployment strategy becomes economically and institutionally compelling. The first category of deployment can then be done for fiscal intelligence systems including tools that improve revenue identification, arrear prioritisation, and assessment accuracy within already digitised tax environments. The second use case could involve operational optimisation systems encompassing tools that improve the efficiency of recurring logistical functions such as road maintenance scheduling, sanitation routing, and complaint workflow coordination. These two categories differ in their immediate impact profile but share a common economic rationale where both generate measurable administrative returns against comparatively modest deployment costs. In Chandigarh's case, the fiscal arithmetic is particularly compelling as the MC currently realises approximately Rs.84 crore annually through property tax collections. The Pune MC's AI-GIS-based property mapping initiative, which identified over 11,000 untaxed properties and generated Rs.31 crore in additional revenue, offers a directly applicable Indian precedent. Even a conservative 3-5% improvement in collection efficiency within Chandigarh's existing property tax structure would realistically generate between Rs.2.5 crore and Rs.4 crore annually, against estimated deployment costs of Rs.40 to Rs.60 lakh. International and domestic experience consistently demonstrates that AI deployment in civic systems produces compounding improvements in institutional responsiveness that extend well beyond the initial use case. Nagpur's MC used AI-assisted infrastructure surveys to identify nearly 2,000 faulty manholes within a single municipal zone, enabling targeted repair prioritisation and catalysing citywide audit expansion. In Chandigarh, where solid waste management already commands a Rs.32 crore annual allocation, even a 5% operational efficiency improvement could generate annual savings approaching Rs.1 crore. The BIRBAL chatbot, already operational, provides an existing interface layer through which complaint data can feed directly into such mapping systems. The Chandigarh MC should embrace AI for efficiency and accountability....