The realm of traditional medicine (TM), encompassing practices such as Ayurveda, traditional Chinese medicine (TCM), Thai traditional medicine (TTM), and indigenous healing systems, holds a vast wealth of knowledge developed over centuries. These practices have successfully treated generations of people using natural methods rooted in holistic understanding and observing complex patterns in health and disease. However, the modern world presents new challenges: increasing demand for evidence-based practices, personalization of healthcare, and scalable, accessible treatment solutions. Artificial Intelligence (AI) stands at the intersection of these demands, offering transformative potential to elevate and expand the application of TM. AI’s capacity to process and analyze vast amounts of data, recognize complex patterns, and make predictive analyzes can revolutionize TM in multiple dimensions. This essay explores the potential benefits of integrating AI with TM, highlighting key areas where this synergy could bring significant advancements (Figure 1, Supplementary Figure S1).

TM diagnostics—pulse reading, tongue inspection, body element examination, facial observation (Figure 2)—are rich pattern-recognition tasks but susceptible to inter-observer variability. Current evidence shows that ML has been used to differentiate TCM diagnostic patterns on curated datasets (e.g., dampness-heat in type 2 diabetes) and to structure acquisition protocols for sensor-based pulse assessment, with performance dependent on feature standardization and context (Liu et al., 2023; Tian et al., 2024; Zhou et al., 2024). Future potential includes interoperable signal standards, ontology alignment across systems, and external validation with multi-site cohorts (Lu et al., 2024).

A hallmark of TM is its focus on individualization—treatments tailored to a person’s specific constitution, lifestyle, and symptoms. Unlike many modern medical treatments, which often follow a one-size-fits-all approach, TM considers a person’s holistic profile. AI, with its predictive modelling and data analysis capabilities, can elevate this individualized approach (Ranade, 2024). AI systems can analyse genetic data, environmental factors, and health records to recommend highly personalized treatment plans (Lu et al., 2024). For example, in TCM, a practitioner might assess the balance of Yin and Yang or diagnose a condition based on pulse and tongue readings. Another, in TTM, a practitioner used the balance of body element concept to diagnose through present body element examination (Mahajaroensiri et al., 2017) and pulse reading. AI could augment this process by analyzing subtle biometric data that may be too complex for humans to process quickly, offering more precise and personalized diagnostic results (Liu et al., 2023; Tian et al., 2024). This combination of ancient practice and modern technology could lead to highly customized treatments that are effective and harmonious with an individual’s unique biology (Supplementary Figure S2).

TM often follows a holistic approach, treating the symptoms and underlying causes of illness. However, predicting the outcomes of specific treatments, especially in complex cases, can be challenging. AI’s predictive analytics tools can model potential outcomes based on patient data, offering a more data-driven approach to traditional treatments (Bae et al., 2024). By processing complex data and identifying intricate patterns, these intelligent systems can predict potential treatment candidates, understand disease pathology and verify target proteins with remarkable accuracy. For instance, researchers have developed sophisticated AI-driven models, such as multi-target-based polypharmacology prediction systems, that showcase the ability of AI to screen TCM compounds efficiently (Liu et al., 2021). This predictive capability would enhance both the safety and effectiveness of treatments, giving practitioners the confidence that their chosen therapies are optimal for each patient. Furthermore, it could help refine the criteria for patient selection, ensuring that traditional treatments are applied where they are most likely to have a positive impact (Bae et al., 2024).

AI enables large-scale curation of herbal knowledge, prioritization of bioactive compounds, target prediction, and interaction risk assessment (Zhou et al., 2024; Song et al., 2024). Importantly, safety models predicting risks such as drug-induced liver injury (DILI) based on chemical structure illustrate how AI can augment risk assessment for herb and herb–drug combinations (Liu et al., 2021). Future potential requires TM-specific external validation datasets and integration with pharmacovigilance.

AI-assisted digitization makes scattered textual and oral knowledge searchable and interoperable, supporting education and research (Song et al., 2024; Srivastava and Upadhyay, 2024; Li, 2024). Standardized terminologies and cross-tradition mappings (e.g., TTM body elements, TCM patterns, Ayurvedic doshas) are prerequisites for multilingual corpora and knowledge graphs; expert-elicited resources on pulse characteristics by innate body elements in TTM provide anchors for such work (Tantiwongsekunakorn et al., 2025).

AI-enabled teleconsultation can extend access to TM practitioners and support remote triage and monitoring (Rastogi et al., 2022). Current evidence is promising for feasibility and reach; future potential hinges on rigorous evaluation of diagnostic concordance, safety, equity, and patient understanding. See validation and reporting checklist for AI in TM (Supplementary Table S2).

AI can help integrate TM with biomedicine by identifying potential synergies and risks, including herb–drug interactions, promoting safer combined regimens (Maria, 2024; Alowais et al., 2023).

The integration of AI into TM has the potential to bring about a new era of healthcare. By leveraging AI’s ability to process complex data, recognize patterns, and personalize treatments, TM can evolve to meet modern healthcare demands while preserving its rich heritage. This synergy between ancient wisdom and modern innovation holds the promise of more effective, accessible, and precise healthcare, benefitting individuals and societies worldwide. As AI technology continues to advance, its role in TM will likely grow, offering exciting possibilities for the future of holistic health and wellness.