A Comparative Analysis for GenAI-Enabled Learning Systems for Urban Portfolios in ECIS

The UNDP City Experiment Fund supports municipalities across Europe and Central Asia as they advance the Twin Transition by integrating green and digital solutions through urban portfolios designed to function as learning systems. As these cities shift from design to implementation, they face growing demands for faster reflection, stronger knowledge-sharing, and more adaptive decision-making than traditional tools such as manual monitoring or periodic workshops can provide.

This project examines how GenAI-enabled learning tools compare to conventional municipal learning methods in supporting strategic learning, knowledge diffusion, and portfolio management. The SIPA team will review existing literature, analyze current GenAI tools used within UNDP, and map learning practices across selected cities. Interviews and case studies will help identify strengths and weaknesses in current systems and clarify where AI tools such as predictive analytics, generative decision support, and automated reporting can enhance municipal learning processes. The goal is to provide UNDP with a practical, data-driven set of recommendations on how to integrate GenAI tools into city portfolio management to strengthen adaptability, improve coordination, and accelerate progress on the Twin Transition. The final report will offer a comparative framework and clear strategies that cities can use to embed continuous learning as a core capability.