Presentation: AI-enabled urban asset management – predictive maintenance at scale

As infrastructure ages and budgets tighten, cities are turning to AI-powered monitoring to extend asset life and reduce unplanned failures. This session explores how predictive models, condition-based alerts and automated inspections can strengthen maintenance programmes across roads, bridges, buildings and utilities. It highlights both the technical enablers and the organisational shifts required to embed AI into daily operations.

Key talking points:

• Deploying sensors and computer vision to monitor structural health in real time
• Using predictive analytics to prioritise repairs and optimise maintenance cycles
• Integrating asset-level insights across transport, facilities and utility teams
• Building governance, data quality controls and staff readiness for AI-driven maintenance