Artificial Intelligence as an Assistant in Homeopathy

Artificial intelligence (AI) is increasingly being used in health care, including homeopathy. It can help practitioners by organising patient records, searching literature, navigating repertories, and providing training simulations or pattern support tools. However, if used without care, AI may reduce clinical judgment, over-simplify individual symptoms, or lead to over-reliance on algorithms. Nevertheless, AI can be used responsibly in homeopathy while keeping the practitioner at the centre of care. The role of AI is to assist practitioners rather than replace the delicate art of case-taking and remedy selection. Using it responsibly means always prioritising the individuality of each patient and the totality of their symptoms. AI can be particularly valuable in education, research and clinical support, provided that its tools are validated against trusted homeopathic sources. At the same time, students and practitioners must continue to cultivate their powers of observation, analysis and ethical judgment, ensuring that technology enhances rather than diminishes these essential human skills. When applied thoughtfully, AI can support homeopaths in finding the remedy that most closely matches a patient's totality, without replacing the reasoning, empathy and experience that are central to the practice. With proper guidelines, AI can be a helpful assistant rather than a substitute for the human touch in homeopathy.

AI has been rapidly advancing and finding increasing applications, including managing case records, supporting research through the analysis of large symptom datasets, serving as an educational tool via simulations and remedy- family training exercises. It can even act as a prompt during case-taking, as explored in a recent study in the United Kingdom, where both staff and patients highlighted roles for AI in asking questions, assisting with writing, and directing consultations.[1]

Nevertheless, limitations must be acknowledged. Most AI systems do not yet have access to the latest repertories or full materia medica. AI does not have direct access to paywalled journal content. However, it can provide information, summaries, and insights based on its training data and publicly available sources. For example, AI can retrieve and summarize freely accessible online material from sources such as the Indian Journal of Research in Homoeopathy, Hpathy.com and Qjure.com, and it can guide users on where to find full articles and how to access them through institutional subscriptions, open-access repositories or publisher websites. AI also has access to databases such as Radar software. However, in many cases, the rubrics suggested by AI do not precisely match those found in Radar's repertories. For this reason, AI suggestions must be validated and interpreted by trained practitioners, ensuring that final decisions on remedy selection, potency, and follow-up remain human responsibilities.

To advance this field responsibly, a structured research agenda is needed. Comparative evaluations should test AI-generated remedy suggestions against human practitioners using the same video-recorded cases, particularly where outcomes demonstrate clinical benefit from homeopathy. Educational applications could include training AI to “act like” remedy families, such as Solanaceae, allowing students to practise family differentiation through unscripted dialogue with AI. Similarly, the use of AI as a real-time prompt tool in case-taking deserves systematic exploration, as does the integration of the latest repertories into AI systems, while addressing financial and licensing barriers. Another important avenue for research is to investigate whether AI can help reduce practitioner bias by offering a wider and more neutral spread of remedy suggestions.

In conclusion, AI should be understood as a powerful assistant in homeopathy rather than a substitute for clinical judgment and human insight. By pursuing a structured research agenda and adopting balanced guidelines, the homeopathy community can harness the speed, breadth and analytical strengths of AI while preserving the human-centered ethos at the heart of our practice.

Publication History

Received: 03 September 2025

Accepted: 26 September 2025

Article published online:
22 January 2026

• Reference

• 1 Moschogianis S, Darley S, Coulson T, Peek N, Cheraghi-Sohi S, Brown BC. Seven opportunities for artificial intelligence in primary care electronic visits: qualitative study of staff and patient views. Ann Fam Med 2025; 23: 214-222