Authored By Dr. Markus Ploesser

Artificial intelligence (AI) is increasingly used by patients to obtain health information, interpret symptoms and explore treatment options, raising questions about its safety in pain management and integrative care. This commentary examines recent evidence on general-purpose large language models and purpose-built AI applications used in pain- related contexts. Current studies suggest that contemporary AI systems can provide highly accurate and useful information for relatively bounded tasks, including pain pharmacology, patient education and some aspects of rehabilitation. Newer models generally outperform earlier systems, highlighting the rapidly changing nature of the evidence base. However, high factual accuracy does not necessarily translate into safe individualised treatment advice. Important limitations include incomplete responses, inconsistent adherence to clinical guidelines, difficulty reasoning from incomplete clinical information and failure to account for patient-specific contraindications or other contextual factors. Purpose-built AI rehabilitation and chronic-pain self-management tools show promising results, particularly when operating within clearly defined therapeutic pathways. Evidence from integrative medicine is similarly mixed: AI has demonstrated substantial specialist knowledge in areas such as acupuncture and traditional Chinese medicine, while recommendations concerning dietary supplements appear less consistently reliable. The safety of AI in pain care therefore depends less on whether AI is inherently “safe” or “dangerous” than on the task it is asked to perform. AI appears most valuable as a tool for education, evidence navigation and supported self-management, whereas diagnosis, medication changes and complex individual treatment decisions continue to require clinical judgement, appropriate safeguards and human oversight.