General Internal Medicine Physicians

Diagnose and provide nonsurgical treatment for a wide range of diseases and injuries of internal organ systems. Provide care mainly for adults and adolescents, and are based primarily in an outpatient care setting.

The occupation of General Internal Medicine Physicians has an estimated automation risk of 37.5%, which is closely aligned with the base risk for the field at 38.2%. This moderate risk reflects the growing capabilities of artificial intelligence and robotics to handle certain complex, data-driven medical tasks. The top three most automatable aspects of the job are centered on processes that are heavily based on data analysis and established protocols: analyzing records, reports, test results, or examination information to diagnose medical conditions; treating internal disorders such as hypertension, heart disease, diabetes, or organ-specific ailments; and prescribing or administering medication and therapies. Advances in AI technologies have made significant inroads in reading diagnostic imaging, flagging abnormal lab results, and even recommending evidence-based treatments, making these aspects particularly susceptible to automation. Despite the increasing sophistication of automation in healthcare, several core responsibilities of General Internal Medicine Physicians remain resistant to automation. The most resistant tasks involve higher-level conceptual, creative, and physical decision-making skills that are less amenable to standardization. These include planning, implementing, and administering complex health programs for injury and illness prevention and treatment in diverse settings; performing intricate surgical operations to repair or improve body functions; and conducting research to develop or test new medications, treatments, or procedures. Such responsibilities demand not just technical expertise, but also nuanced judgment, adaptability, collaboration, and problem-solving in unpredictable, dynamic environments—skills that current AI and robotics struggle to replicate. A significant bottleneck for automation within this occupation is the demand for originality, as shown by its associated skill importance (3.0% and 3.6%). Medical professionals frequently face unique cases requiring innovative approaches, especially when tailored care or creative problem-solving is critical for effective patient outcomes. Tasks involving clinical intuition, constructing individualized treatment plans, and navigating ethical or psychosocial dimensions lean on a physician’s ability to think imaginatively and adapt to new information. While AI can support physicians by providing data and suggesting options, the core ability to generate original solutions in unpredictable clinical scenarios remains an essential and distinctive human skill, impeding further automation risk for General Internal Medicine Physicians.