Artificial intelligence is also transforming the healthcare industry by assisting us to diagnose earlier, both tailor therapies and better manage patients via the evolution of ML algorithms, predictive analytics as well as robotic help. Although these developments improve accuracy and specificity, they also raise intricate ethical considerations including problems of algorithm transparency data or privacy fairness. This article takes a critical look at the problem of biased datasets that could lead to perpetuating health disparities, potential patient autonomy breaches and loss of personalized care because AI-driven decisions. In addition, with more impact in clinical outcomes the highest accountability becomes blurry raising ethical and regulatory questions that require urgent attention. Using case studies, this study examines AI as a double-edged sword capable of revolutionizing potential healthcare improvements and liabilities. We argue for general ethical guidelines addressing fairness, interpretability and accountability to be developed that put AI in a supporting role thereby being part of the “social network” combating multimorbidity as an environment with heterogeneous interactions requires such collaborative actors along continuum of care from patient toward treatments.