As increasingly complex socio-technical systems (STS) emerge, made of citizens and intelligent algorithms, the urban dimension of Artificial Intelligence (AI) becomes more evident. AI could empower cities to face complex urban challenges or create further vulnerabilities and exacerbate urban issues. For example, navigation systems suggest directions that make sense from an individual perspective but, due to network effects, may create chaos if too many drivers are directed on the same route. The emergence of STS is likely to amplify these network effects, either positively or negatively, but we largely ignore how. This project aims to study the impact of human mobility on Urban Well-Being (UW) and design next-generation AI assistants that allow us to control this impact and benefit from it. We will focus on navigation systems (NS) and public mobility services (MS).NS (e.g., Google Maps) use routing algorithms to suggest the most comfortable path to reach a specific destination. NS’ impact on the urban environment is still largely unclear and may cause several problems. This is because they are typically optimised to keep an individual driver's travel time as short as possible, and they do not care about collective effects on the city, such as whether the streets can absorb the traffic, the traffic compromises safety or creates more pollution. MS (e.g., car-sharing, ride-hailing) provide affordable alternatives to traditional transportation, promising to increase the accessibility of urban areas. However, NS’ collective impact on the quality of the urban environment is largely unclear. Recent studies suggest that ride-hailing services may increase road traffic, climate emissions and traffic congestion, and racial segregation.The URBAI project has a threefold purpose: 1) to design indicators to measure UW along environmental quality, security and segregation; 2) to study the impact of NS and MS on UW using mobility data and simulation frameworks; 3) design and validate next-generation AI assistants that allow us to control the impact of human mobility and benefit from it reaching a trade-off between user satisfaction and UW. URBAI can lead to significant technical advancements that can open new research directions and facilitate the development of external independent research in AI, network science, and computational social science. The project's ambition clearly goes toward improving our society, and has the potential to provide a solid foundation for future sustainable AI technologies for smart cities.