Digitalization is one of the most powerful and profound developments that affect industry and society. With digital technologies such as software, data, and artificial intelligence (AI), companies in the software-intensive systems domain are facing a rapid transformation of their businesses and a fundamental shift in how systems are built. The essence of digitalization is continuous value delivery to customers and systems that improve and learn over time. Today we build systems – tomorrow we will grow systems. This is accomplished by continuous practices (e.g., DevOps, DataOps, MLOps), data-driven and experimental development, and effective use of AI technologies such as machine- and deep-learning (ML/DL) models. This talk takes a holistic perspective when exploring how software engineering practices are in the process of changing and what the implications of these changes are. Based on longitudinal empirical research conducted in close collaboration with software-intensive systems companies in e.g., the telecommunications, automotive, manufacturing, security and surveillance industry, as well as companies in the Software-as-a-Service (SaaS domain), it provides illustrative examples on how software engineering practices are in the process changing and how these changes affect business, architecture, process and organization.