With the continuous development of information technology, robotics and data science will certainly have a similar impact on invasive medicine over the next 20 years as it has had on manufacturing technology in the recent decades. Early image-guided systems and surgical robots were employed in the operating room primarily for their accuracy and reliability, as they allowed for faster and safer interventions with minimal tissue damage, targeting especially orthopedics and neurosurgery. On the other hand, a real global breakthrough came with the teleoperated da Vinci Surgical System, ideal for soft tissue procedures. The success and dominance of the da Vinci has dimmed the dozens of other surgical robots already on the market. It partially originated from the teleoperation concept of Robot-Assisted Minimally Invasive Surgery, where the full control of the robotic tools is always maintained by the human operator via the console. Nevertheless, the availability of data at large brings new possibilities, e.g., the in-view integration of preoperative data, data fusion based on surgical navigation, and error compensation have become increasingly available in prototypes. Surgical decision support and the elimination/eviction of potential errors also became increasingly important in telesurgical applications. Appropriate algorithms for handling distortions, delays, and other, even malicious, interference attempts during communication are essential. The concept of robotic telesurgery originates from NASA, and even as of today they are actively exploring the additional possibilities offered by cutting-edge technology to improve surgical systems using data science methods. In the not so distant future, even soft tissue interventions will be performed by autonomous robots. The aim of this article is to present the reader the basic concepts of this modern interdisciplinary field named Computer-Integrated Surgery, and to introduce the most important robots and robotic systems. We provide an overview of the different forms of telesurgery and describe the idea and the complexity of data-driven interventions.