With the development of technology for collecting and analyzing user data, the possibility of intelligent IT services that provide personalized support to individual users is continuously increasing. As technology becomes more sophisticated, personalization in intelligent IT services is increasingly being automated by the systems. However, system-driven approach raises the issues in user experience as users often lose their controls over the systems’ behaviors in the experience of intelligent IT services. In this context, this research aims to investigate the ways to support users’ experience of intelligent IT services, not just as a passive service recipient, but more as a co-creator who actively participates in the process that systems learn about the users over time. To do so, user-centered studies were conducted to understand users’ overall experience of intelligent IT service and their co-performing experience over time in the wild. Based on the results, a framework for designing co-performing experience was developed and its role and value in the design practice was investigated through a workshop-based expert interview. This research contributes to user experience design research and design practice as follows. First, this research proposed a perspective for understanding users’ participation in systems’ learning as a process of building the relationship with intelligent IT services through reciprocal interactions between users and systems. This is different from the existing approach that considers users’ participation in a system’s learning process as task-oriented and fragmented interactions. Second, this research identified important phases and factors that should be considered in supporting users co-performing experience over time. Third, this research proposed co-performing experience design framework, which would provide a thought framework for designing co-performing experience in intelligent IT services. By providing design guidelines for supporting users to understand their role and to co-perform with the systems, the results of this research are expected to contribute to inform the design of intelligent IT services that provide personalized service experience in a more human-centered way.