In this keynote I will introduce the front-edge robotics and artificial intelligence (AI) research my team has been conducting in healthcare at Heriot-Watt University. First, I will talk about the currently running project on “Autonomous and Intelligent Laparoscopy Trainer with Real-Time Feedback - AILap”. In this project we are developing the next-generation laparoscopy training platform by bringing together physical realism and AI to provide automated real-time feedback along with the assessment. Our goal is to eliminate the need for supervision and enable self-training with immediate and effective feedback for laparoscopy training. Then, I will talk about the Robotic Surgery Trainer we have developed in our laboratory. Robotic surgery requires specific set of skills. Tele-operation for a robotic system with hand controllers, the delay in the hand commands to be translated into robotic movements, slowness of the robotic movements, remote 2D or 3D vision of the actual operation, and lack of haptic feedback are some of the challenges that robotic surgery poses. There are not yet dedicated, low-cost, and widespread training platforms; rather, surgeons mostly train with the same type of robotic surgery system they use in surgery. This is expensive for the institutions and provides very limited access to the surgeons for training. Our setup is a low-cost training platform replicating the challenges that a robotic surgery system poses and enables widespread access through internet connected control of the actual physical system. Finally, I will talk about the design and development of a robotic hand-exoskeleton for assessment of hand spasticity, of a wearable exoskeleton prototype to assist nurses when they bend their body for lifting and other purposes, and of a laser ablation instrument that allows travelling a laser beam on tissue for ablation in surgery.