Artificial Intelligence in healthcare: what lies ahead

Artificial intelligence is being deployed at scale in India's healthcare system across diagnostics, drug discovery, disease surveillance, and telemedicine — ...

What Happened

Artificial intelligence is being deployed at scale in India's healthcare system across diagnostics, drug discovery, disease surveillance, and telemedicine — with both government-led initiatives and private sector platforms driving adoption.
Key milestones: AI-enabled screening tools have been integrated into the National TB Elimination Programme and the National Diabetic Retinopathy Screening Programme; the eSanjeevani telemedicine platform processed 282 million consultations by November 2025, using AI assistance.
The AI-powered Media Disease Surveillance System has generated over 4,500 disease outbreak alerts, enabling faster epidemic response.
Outcomes data shows a 27% decline in adverse TB outcomes attributable to AI-powered diagnostic tools enabling earlier detection by non-specialist health workers.
The government launched SAHI (Strategy for Artificial Intelligence in Healthcare for India) and BODH (Benchmarking Open Data Platform for Health AI) at the India AI Impact Summit 2026, establishing a governance and benchmarking framework for health AI.
Key challenges include data privacy, algorithmic bias affecting marginalised populations, digital infrastructure gaps in rural areas, and the absence of a comprehensive health data protection law tailored to AI applications.

Static Topic Bridges

ICMR Ethical Guidelines for AI in Healthcare

The Indian Council of Medical Research (ICMR) released the Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and Healthcare — the first national-level regulatory framework for health AI in India. These guidelines govern AI-based tools used for diagnosis, screening, therapeutics, preventive treatment, clinical decision support, public health surveillance, and complex data analysis involving human participants or their biological data.

The guidelines emphasise transparency, accountability, non-maleficence, and inclusivity as core ethical principles for health AI.
They require AI tools to be validated on diverse Indian population datasets to avoid bias arising from models trained predominantly on Western demographic data.
Clinical AI tools must undergo rigorous validation trials before deployment, with performance benchmarks established against human expert baselines.
The guidelines distinguish between AI tools used by clinicians (decision support) and those making autonomous decisions (which require higher regulatory scrutiny).
ICMR's framework is aligned with global guidelines from WHO and OECD on AI in health, while addressing India-specific concerns such as linguistic diversity and rural-urban digital divides.

Connection to this news: SAHI and BODH, launched in 2026, operationalise the ICMR ethical framework by creating a national strategy and an open benchmarking platform — translating principles into governance infrastructure.

Ayushman Bharat Digital Mission (ABDM) and Digital Health Infrastructure

The Ayushman Bharat Digital Mission (ABDM), launched in September 2021, is the foundational digital health infrastructure upon which AI applications are being built. ABDM aims to create a unified national digital health ecosystem by connecting patients, healthcare providers, insurers, and public health agencies through interoperable digital records.

Core component: Ayushman Bharat Health Account (ABHA) — a unique health ID linking all medical records of an individual; approximately 739 million ABHA IDs created by early 2025.
Over 363,000 health facilities and 564,000 healthcare professionals registered on the ABDM platform.
Over 490 million health records linked with ABHA IDs, enabling longitudinal patient data that AI tools can analyse for diagnostics and care planning.
ABDM follows a "privacy by design" and federated architecture — no centralised repository of individual health data; data exchange happens after explicit patient consent.
The Digital Personal Data Protection Act (DPDPA), 2023, and its 2025 Draft Rules apply to health data processed under ABDM, creating a statutory privacy layer above the operational framework.

Connection to this news: ABDM's federated, consent-based architecture is the enabling infrastructure for ethical AI deployment in healthcare — allowing AI tools to access population-scale data for training and inference while maintaining individual privacy safeguards.

AI Applications in Indian Healthcare: Key Use Cases

AI in healthcare encompasses a wide range of applications, from imaging and diagnostics to drug discovery and public health surveillance. In India, government programmes have prioritised AI tools that can extend specialist-level care to non-specialist and rural settings.

Diagnostics: AI-powered chest X-ray analysis tools deployed under the National TB Elimination Programme enable community health workers without radiology training to flag potential TB cases for specialist review, improving detection in resource-limited settings.
Diabetic Retinopathy Screening: AI-based retinal image analysis under the National Diabetic Retinopathy Screening Programme allows trained technicians at primary health centres to conduct ophthalmologist-level retinal screening.
Disease Surveillance: The AI-powered Media Disease Surveillance System (MDSS) monitors news and social media in multiple languages to detect early signals of disease outbreaks, generating over 4,500 alerts and enabling faster public health response.
Telemedicine: eSanjeevani, India's national telemedicine platform, uses AI-assisted triage and consultation support; processed 282 million consultations by November 2025.
Drug Discovery: AI is being used to accelerate identification of new drug molecules, particularly for diseases prevalent in India (TB, malaria, leishmaniasis), reducing the time and cost of early-stage discovery.

Connection to this news: Each of these use cases demonstrates AI's potential to address India's core healthcare challenge: providing quality care at scale with a limited specialist workforce — which is why the "what lies ahead" question centres on both scaling successes and managing risks.

Regulatory Challenges: Data Privacy, IT Act, and Health AI Governance

India's regulatory framework for health AI is an evolving patchwork of sector-specific guidelines (ICMR), generic data protection law (DPDPA 2023), and the Information Technology Act, 2000 with its amendments.

IT Act, 2000 (Section 43A and the Sensitive Personal Data or Information Rules, 2011): The first statutory framework requiring entities handling sensitive personal data — including health data — to maintain reasonable security practices. However, these provisions predate AI and do not address algorithmic accountability.
Digital Personal Data Protection Act (DPDPA), 2023: India's comprehensive data protection law; classifies health data as sensitive personal data requiring explicit consent for processing. Its applicability to AI-based health tools is being worked out through the 2025 Draft Rules.
The absence of a specific AI regulation act in India means health AI is governed through a combination of ICMR ethical guidelines (voluntary/advisory), DPDPA (statutory, data-focused), and sector-specific guidelines from the National Health Authority (NHA).
Algorithmic bias: AI models trained on skewed datasets can produce systematically inaccurate results for underrepresented groups (tribal populations, rural communities, linguistic minorities) — a concern the ICMR guidelines explicitly flag.
The SAHI strategy and BODH benchmarking platform address regulatory gaps by providing government-endorsed standards and performance metrics that developers and deployers must demonstrate compliance with.

Connection to this news: The article's "what lies ahead" framing captures precisely this regulatory moment: India has proven AI can work in healthcare, but the governance framework to ensure it works safely, equitably, and at national scale is still being constructed.

Key Facts & Data

ICMR released Ethical Guidelines for AI in Biomedical Research and Healthcare — India's first national health AI regulatory framework.
SAHI (Strategy for AI in Healthcare for India) and BODH (Benchmarking Open Data Platform for Health AI) launched at India AI Impact Summit 2026.
ABDM: Approximately 739 million ABHA health IDs created; 363,000+ health facilities registered; 490 million+ health records linked (as of early 2025).
eSanjeevani telemedicine: 282 million consultations processed by November 2025.
AI-powered Media Disease Surveillance System (MDSS): 4,500+ outbreak alerts generated.
National TB Elimination Programme AI tools: Associated with 27% decline in adverse TB outcomes.
Digital Personal Data Protection Act (DPDPA), 2023: Classifies health data as sensitive personal data requiring explicit consent.
IT Act, 2000 Section 43A and SPDI Rules, 2011: First statutory framework for health data security in India.
India has approximately 1 doctor per 854 people (WHO recommends 1 per 1,000) — AI-assisted care is a policy imperative, not merely a technological option.
PMSSY (Pradhan Mantri Swasthya Suraksha Yojana) and AIIMS expansion are parallel government efforts to address specialist workforce gaps that AI tools complement.