The World Intellectual Property Organization, the International Telecommunication Union, and the World Health Organization are collaborating in a novel way to investigate the possibilities of AI in conventional medicine. Their latest study looks at the ways in which technology can support, advance, and improve these age-old treatment techniques.
The WHO, the ITU, and the WIPO had launched a joint technical brief, mapping the application of artificial intelligence in traditional medicine during the AI for Good Global Summit in Geneva on 11 July, 2025.
According to the report, TCIM (Traditional, Complementary, and Integrative Medicine) is used by billions and practiced in 170 countries, reflecting global reliance on traditional healing methods. It (TCIM) encompasses a range of holistic healing methods, practices, and therapies that are rooted in ancient healthcare systems. These are derived from the cultures and traditions of different countries.
AI Meets Traditional Medicine: Key Global Developments
- AI-powered diagnostics are being used in Ayurgenomics: This project represents an exciting intersection of Ayurveda and genomics, aiming to understand the genetic basis of Ayurvedic principles and practices. A scientific breakthrough that combines genomics with Ayurvedic principles. This initiative aims to identify predictive disease markers and personalize health recommendations using AI-based analysis of Ayurvedic constitution types.
- Machine learning models identifying medicinal plants: The ability to automatically identify medicinal plants for TM use by images of their leaves would reduce the need for expert input and save time. Study uses ExG-ExR index to identify plants from leaf images, extracting data without manual thresholds. The ExG-ExR index effectively identifies binary plant regions regardless of lighting. The original color pixels of the binary image serve as a mask to isolate leaves as sub-images. Plant species are then classified by color and texture features of each extracted leaf using a logistic regression classifier, achieving 93.3% accuracy.
- Analysis of traditional medicine compounds to treat blood disorders in the Republic of Korea: Researchers at the Bio-Synergy Research Center in Daejeon, South Korea, recently developed CODA (Context-Oriented Directed Associations)— a software that draws on recent advances in artificial intelligence and biotechnology. The team plans to use CODA to explore the therapeutic potential of chemical compounds found in traditional medicines.
AI-Powered Healing
AI aids healthcare via image analysis, predictive modeling, and chatbots using machine learning and natural language processing. These innovations have the potential to reduce diagnostic errors, improve treatment outcomes, and enhance the overall patient experience.
However, as Artificial Intelligence continues to advance, it is essential to explore its role in supporting the principles of TCIM, which places a strong emphasis on individualized care and a holistic view of health.
- Diagnostic augmentation: AI-powered diagnostic tools can analyze patient data, including medical records and imaging results, to assist in early disease detection and differential diagnoses. TCIM practitioners can benefit from these tools to support their assessments and develop a more comprehensive view of their patients’ health.
- Personalized treatment plans: TCIM emphasizes individualization in patient care. Artificial Intelligence can analyze a patient’s comprehensive health profile to recommend treatments. These treatments combine conventional medical approaches with complementary therapies, tailored to the patient’s preferences and needs.
- Predictive analytics for preventive medicine: A central tenet of TCIM is preventive care. Artificial Intelligence excels in identifying health trends and predicting disease risks, enabling proactive interventions to prevent illnesses. By providing insights into patients’ unique health trajectories, Artificial Intelligence further supports the preventive focus of TCIM.
AI’s Bias in Ancient Healing
While Artificial Intelligence may also improve diagnosis, treatment, and access to care, it also raises concerns about data privacy, bias, accountability, and the potential deterioration of the patient-practitioner relationship. To balance these risks and benefits, strict regulatory oversight and a thorough assessment of ethical frameworks are required.
- Artificial Intelligence systems rely on vast amounts of data, including sensitive patient information, which can be vulnerable to breaches and misuse.
- Artificial Intelligence algorithms can perpetuate existing biases if trained on skewed datasets, leading to unequal access to care and unfair treatment of certain groups.
- Clear lines of responsibility and accountability must be established for AI-related errors and adverse events.
- The integration of Artificial Intelligence should not come at the expense of the patient-practitioner relationship.
- The integration of Artificial Intelligence in healthcare can have broader societal impacts, including potential job displacement and exacerbation of existing inequalities.
With the power of AI, the future of medicine might be in the past. The potential is enormous, as the WHO, ITU, and WIPO report clearly shows. The world must now ethically harness technology to ensure its benefits reach everyone, everywhere. We need to learn how to cooperate with the new ally of the old traditions.
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