As cities expand and governance becomes more data-driven, artificial intelligence is emerging as a key tool to modernise urban administration in Madhya Pradesh. The Urban Department is looking at AI as a way to improve efficiency, transparency, and citizen-focused services across Urban Local Bodies (ULBs).
AI is expected to strengthen municipal service delivery through predictive and intelligent systems. It can help optimise revenue collection from property tax and water charges, reduce leakages, and improve compliance. AI-powered grievance systems using chatbots and automated prioritisation can speed up complaint resolution. It can also support water and sewerage management by detecting leaks, identifying unusual consumption patterns, and flagging disruptions in real time.
Urban systems generate large volumes of data through GIS platforms, property tax systems, smart meters, AEBAS attendance systems, and e-governance portals. AI can analyse this data to identify revenue gaps, forecast urban growth, and support better planning and policymaking. This shift allows governance to move from reactive responses to proactive decision-making.
AI can also improve transparency by detecting irregularities in procurement, contracts, and spending. It can monitor workforce deployment, automate compliance checks, and support audits. These measures reduce manual intervention and build public trust.
With integration into GIS and satellite data, AI can support land-use planning, traffic management, disaster preparedness, and climate-resilient urban design. This is especially important for growing cities like Bhopal, Indore, Jabalpur, and Gwalior.
AI adoption can also boost municipal finances by identifying unassessed properties, improving tax compliance, and optimising tariffs. This helps increase revenue and supports investment in infrastructure and services. At the same time, it creates demand for skilled roles such as data analysts and AI operators, building a digital workforce.
The eNagar Palika 2.0 (ENP 2.0) project highlights practical use cases. ML-based GIS analytics can detect encroachments, identify unregistered properties, flag unpaid taxes, and assess property values. AI can also compare approved building plans with actual structures to detect violations.
To ensure success, the department must focus on data readiness, secure systems, ethical AI use, and staff training. A phased rollout with pilot projects and integration with existing platforms will support smoother adoption.
AI is set to become a strategic enabler for efficient, transparent, and sustainable urban governance in the state.
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