Artificial Intelligence and Indian Healthcare: Historical Roots, Present Trends, and Future Prospects

Introduction

Healthcare in India has long been a dynamic blend of ancient wisdom, empirical observation, and technological innovation. From Ayurvedic treatises written thousands of years ago to the computational revolution of the 1960s, medicine has been shaped by humanity’s pursuit of systematic knowledge. In 2025, artificial intelligence (AI) represents the latest stage of this evolution, promising to transform diagnostics, clinical decision-making, and healthcare delivery across India.

While AI is often described as “new,” its intellectual lineage can be traced through both India’s classical medical heritage and the foundational work in computer science and AI during the mid-20th century. Ancient Indian physicians like Sushruta and Charaka emphasised systematic observation and documentation, while philosophical schools such as the Cārvāka championed empiricism over metaphysics. These principles resonate strongly with today’s debates on AI transparency, data-driven validation, and evidence-based healthcare.

This blog explores AI in Indian healthcare by situating present-day developments in the continuum of historical roots (ancient and modern), examining trends in 2025, and outlining future prospects and ethical challenges.

Ancient Indian Foundations of Medical Knowledge

Sushruta: The Father of Surgery

The Sushruta Samhita (c. 600 BCE) is among the earliest comprehensive surgical treatises in human history. It catalogued more than 300 surgical procedures and over 120 surgical instruments (Sharma, 1992). Crucially, Sushruta advocated for systematic training and observation, encouraging practitioners to practice surgical skills on models (e.g., fruits, animal skins) before treating patients.

• AI connection: Just as Sushruta demanded rigorous training and testing before live surgery, AI systems today must undergo validation trials before deployment in clinical settings. The insistence on structured protocols mirrors the modern need for algorithmic transparency and testing.

Charaka: Physician and Philosopher of Diagnosis

The Charaka Samhita (c. 300 BCE) focuses on internal medicine and diagnostics. Charaka argued that diagnosis must be based on direct observation, inference, and patient history (Dash & Sharma, 2001). He described disease as a dynamic imbalance, requiring careful analysis of symptoms and contextual factors.

• AI connection: Charaka’s emphasis on pattern recognition and contextual reasoning resembles how AI systems analyse vast amounts of patient data to detect anomalies. For example, machine learning models in oncology echo Charaka’s holistic approach by considering multiple biomarkers and patient histories simultaneously.

Dhanvantari: Holistic Healing and Preventive Care

Dhanvantari, mythologised as the divine physician, symbolises the cultural foundation of Indian medicine. He represents holistic well-being, emphasising prevention as much as cure.

• AI connection: Preventive AI tools (e.g., predictive analytics in public health, wearable devices monitoring vitals) extend this philosophy into the 21st century. AI thus becomes a modern embodiment of Dhanvantari’s preventive ethos.

The Cārvāka School: Empiricism and Skepticism

The Cārvāka school of materialist philosophy (c. 600 BCE) rejected metaphysical claims and insisted that direct perception (pratyakṣa) was the only reliable source of knowledge (Bhattacharya, 2011).

• AI connection: The Cārvāka insistence on empirical evidence parallels the requirement for AI systems to be trained on real-world clinical data and validated through prospective trials. The rejection of “black-box explanations” resonates with today’s calls for explainable AI.

Taken together, these ancient contributions reflect a deeply rational, empirical, and holistic orientation in Indian medicine — one that provides a philosophical foundation for AI integration in healthcare.

Computational Roots: AI and Medicine in the 1960s

Although ancient traditions shaped Indian medicine for millennia, the 1960s marked a pivotal modern moment, when computer scientists first applied algorithms to medical reasoning.

• Ledley and Lusted (1960) argued that diagnostic reasoning could be expressed mathematically and formalised into computational logic. Their work in Science laid the intellectual foundation for medical expert systems.

• McCarthy (1956) proposed “programs with common sense,” introducing symbolic reasoning that would underpin early AI approaches.

• Feigenbaum and Buchanan (1963) developed DENDRAL, a program that could generate hypotheses in organic chemistry, proving that computers could assist in scientific discovery.

• Link to Indian context: These developments paralleled India’s early investments in computer science and medicine during the post-independence era. Although AI applications were limited in India until the 21st century, the 1960s laid the conceptual framework that modern Indian AI health startups (like Qure.ai or Niramai) now embody.

The echo of ancient rationalism and the birth of computational reasoning together create a continuum of knowledge traditions informing today’s AI in Indian healthcare.

Present Trends in 2025: AI in Indian Healthcare

Integration with Digital Infrastructure

The Ayushman Bharat Digital Mission (ABDM) has established interoperable digital health records, patient health IDs, and APIs that allow startups and hospitals to integrate AI solutions into workflows (Ministry of Health and Family Welfare, 2021).

Diagnostics and Imaging

AI tools in radiology (e.g., Qure.ai for chest X-rays), oncology, and breast cancer screening (e.g., Niramai’s thermal imaging) are now being deployed at scale. These platforms speed up diagnosis, reduce costs, and expand specialist access (World Economic Forum, 2025).

Lightweight and Localised AI Models

2025 sees a shift towards smaller, domain-specific AI models that can operate in low-resource environments and support multiple Indian languages (NITI Aayog, 2018).

Telemedicine and Remote Monitoring

AI-driven chatbots and wearable devices are extending care to rural populations, aligning with India’s public health goals (IMARC Group, 2024).

Regulation and Ethics

The Central Drugs Standard Control Organisation (CDSCO) is developing regulatory frameworks for AI-driven medical devices, while the Indian Council of Medical Research (ICMR, 2023) has issued ethical guidelines focusing on accountability, equity, and explainability.

Future Prospects

1. Ayurveda and AI Integration: NLP tools can digitise Ayurvedic texts (Charaka Samhita, Sushruta Samhita) for modern clinical research and personalised medicine.

2. Preventive Healthcare: Predictive AI models can monitor population health, echoing Dhanvantari’s emphasis on prevention.

3. Sovereign AI: Developing indigenous AI models ensures data sovereignty and local validation.

4. Equity in Healthcare: AI must be scaled equitably to prevent widening urban-rural divides.

Conclusion

From ancient treatises of Sushruta and Charaka, through the empirical philosophy of Cārvāka, to the symbolic reasoning of the 1960s, India’s healthcare tradition reveals a long-standing commitment to evidence, empiricism, and holistic care. In 2025, AI continues this legacy, offering transformative opportunities while demanding caution and responsibility. By combining historical wisdom with modern innovation, India can position itself as a global leader in ethical and equitable AI-driven healthcare.

References 

• Bhattacharya, R., 2011. Studies on the Cārvāka/Lokāyata. Firenze: Firenze University Press.

• Dash, B. & Sharma, R.K., 2001. Charaka Samhita: Text with English Translation. Varanasi: Chowkhamba Sanskrit Series.

• Feigenbaum, E.A. & Buchanan, B.G., 1963. DENDRAL: A computer program for generating explanatory hypotheses in organic chemistry. Stanford Artificial Intelligence Project, Technical Report.

• IMARC Group, 2024. India Artificial Intelligence in Healthcare Market: Industry Trends, Share, Size, Growth, Opportunity and Forecast 2024-2029. IMARC Services.

• Indian Council of Medical Research (ICMR), 2023. Ethical guidelines for application of artificial intelligence in biomedical research and healthcare. New Delhi: ICMR.

• Ledley, R.S. & Lusted, L.B., 1960. Reasoning foundations of medical diagnosis. Science, 130(3366), pp.9–21.

• McCarthy, J., 1960. Programs with common sense. In: Proceedings of the Teddington Conference on the Mechanization of Thought Processes. London: HMSO.

• Ministry of Health and Family Welfare, 2021. Ayushman Bharat Digital Mission: Strategy Overview. New Delhi: Government of India.

• NITI Aayog, 2018. National Strategy for Artificial Intelligence. New Delhi: Government of India.

• Sharma, P.V., 1992. Sushruta Samhita: With English Translation of Text and Dalhana’s Commentary. Varanasi: Chaukhamba Visvabharati.

• World Economic Forum, 2025. 4 ways India is deploying AI and innovation to revolutionize health. [online] Available at: https://www.weforum.org [Accessed 25 September 2025].

JAI HIND