Data in Action: AI, Digital Twins and Analytics for Urban Mobility (Part I)

Artificial intelligence, predictive analytics and digital twins are becoming increasingly prominent in urban mobility. Yet many cities continue to face a fundamental challenge: understanding when these tools add value, what data and institutional capacities they require, and how they can support real decision-making. 

This session explores practical experiences with advanced analytical tools in mobility planning and operations. Contributions will showcase how cities, operators, researchers and solution providers are applying AI-assisted forecasting, digital twins, behavioural analytics, real-time operational tools and multimodal data platforms to address mobility challenges. 

Rather than focusing on technology for its own sake, the session will examine the conditions under which these approaches improve planning, support operational decisions and generate measurable outcomes. Speakers will discuss implementation barriers, data requirements, governance and lessons learned from deployment. 

The intended output is a practical understanding of how cities can assess, adopt and scale analytical tools that contribute to more effective and responsive urban mobility systems.