The integration of AI into end-user oriented software systems introduces additional privacy challenges, due to the large amount of data processed and the unique characteristics of AI engineering, compared to traditional software engineering. Although techniques for minimizing data usage and increasing privacy exist, they are not yet well integrated and often create conflicts with system functionality. In this work, we will develop a comprehensive framework that helps developers of AI-enabled systems to specify privacy requirements, monitor their implementation during all phases of software development, and assess tradeoffs between privacy and functionality.