Many of today’s and tomorrow’s smart cities will rely upon services and distributed systems that will apply machine learning and artificial intelligence in their operational logic. These smart applications along with their appliances are data-driven, i.e., their smartness is typically based on the collection, exchange, and the processing of large amounts of user data and user information. For individuals, however, this usage of data may mean be both: (a) an exciting journey to discover the new opportunities of smart cities and (b) an uncertain path to ominous consequences when user data is misused. Hence, the ethical dilemmas and data privacy implications increase when such data is shared across multiple stakeholders, e.g. in distributed artificial intelligence (AI) engineering process, which involves multiple parties. As a result, there is an increasing demand for empowering the users with means, capabilities, and techniques to monitor and eventually to control data disclosure. Users as well as system operators are looking for mechanisms and tools which inform users or operators/stakeholders about the aftermath of the data collection or tools which enforce the data protection and governance requirements in pro-active way and even when conventional privacy enhancing techniques are not applicable. This chapter aims to explore the challenges, requirements, benefits, and functionalities of Digital Sovereignty in a smart city environment. The focus also comprises the necessity and hurdles for engineering, implementation, and development of monitoring and control techniques for future distributed system that can accommodate digital sovereignty when multiple stakeholders are involved and when data is processed in a collaborative way.