Revolutionising Indian healthcare through responsible AI integration

India’s healthcare system, a sprawling network of public and private providers, faces enduring challenges in delivering quality care to its 1.4 billion citizens. Despite advancements, accessibility, affordability, and quality remain significant barriers, particularly in rural and underserved regions. Overburdened doctors, insufficient healthcare infrastructure, and stark urban-rural disparities further exacerbate these issues. However, Artificial Intelligence (AI) offers a transformative opportunity to address these challenges, promising a more efficient, accessible, and equitable healthcare ecosystem.

AI- From Novelty to Necessity

In a nation facing a significant shortage of doctors and a rapidly growing population, AI is increasingly seen as an essential tool rather than a luxury. The integration of technology into healthcare is poised to redefine the delivery of medical services in India. Globally, the digital health market is projected to surpass $500 billion by 2025, with AI driving significant innovations. (1)Clinicians are increasingly embracing AI’s capabilities. The 2023 (2) Clinician of the Future report (3) highlights that 26 per cent of clinicians globally use AI for clinical decision-making, with 66 per cent expecting to adopt it within the next few years. AI’s capabilities are being harnessed across diagnostics, treatment planning, and public health management. For India, this represents an essential tool to bridge its healthcare gaps.

Key applications of AI in healthcare

Artificial Intelligence offers transformative potential in healthcare through various use cases. Clinical decision support systems can leverage AI algorithms to analyse patient data, assisting doctors in diagnoses and treatment planning. These tools can empower even less-experienced healthcare providers to address routine clinical issues effectively, leading to better patient outcomes. In biomedical research and drug development, AI can accelerate drug discovery by analyzing vast datasets to identify potential compounds, significantly reducing time and costs. This capability is crucial for tackling urgent public health challenges, such as emerging diseases and rare conditions. Additionally, AI can enhance diagnostics in fields like radiology, pathology, and genomics by identifying patterns and anomalies with exceptional accuracy, enabling early disease detection and improving treatment efficacy.

Building responsible AI: The need for multi stakeholder bodies in healthcare in India

India’s healthcare system faces significant structural and ethical barriers to adopting Artificial Intelligence (AI), necessitating a collaborative, multistakeholder approach to address these challenges effectively. Structurally, health data in India is predominantly unstructured, fragmented, and siloed, hindering quality and interoperability. Initiatives like the Ayushman Bharat Digital Mission (ABDM), which aims to digitise health records and establish centralised repositories, have made progress but face limitations due to low adoption rates, inadequate awareness, insufficient funding, and a lack of skilled personnel and infrastructure. Moreover, the absence of a comprehensive regulatory framework for data protection, algorithm accountability, and transparency further compounds these issues.

Ethically, biases in AI systems—stemming from unrepresentative training data—risk perpetuating inequalities, especially in India’s diverse demographic and geographic context. Trust and transparency are equally critical, requiring evidence-based, explainable AI outputs that clinicians can verify and patients can trust, particularly with sensitive healthcare data. 

To address these structural and ethical challenges, India’s healthcare ecosystem—including practitioners, diagnostic providers, insurance companies, hospitals, policymakers, and AI developers—must work together to standardise responsible AI principles, improve data practices, bridge infrastructure gaps, and foster trust through inclusive and ethical frameworks.

Multi stakeholder platforms are vital to this effort, bringing together key players to collaboratively address the sector’s technical, ethical, and operational complexities. By enabling joint problem-solving, these platforms can help ensure the ethical and responsible integration of AI into healthcare, paving the way for a trustworthy and effective AI ecosystem.

Globally, multistakeholder initiatives have demonstrated the effectiveness of collective action in navigating AI challenges. For example, the Global Digital Health Partnership (4) promotes best practices in utilising data and technology for healthcare advancements, while the Partnership on AI (PAI) focuses on the responsible deployment of AI across various sectors, including healthcare. Platforms like the newly established Elsevier’s “Responsible AI in Healthcare” advisory board, comprising leading healthcare voices, aims to guide the ethical development and adoption of AI in India through thought leadership, best practices, and sustained engagement with policymakers. Similarly,  CoRE-AI, a multi stakeholder initiative on AI, housed at The Dialogue, which emphasises the significance of inclusive, cross-sector collaboration in developing frameworks that tackle common challenges across diverse sectors,  including healthcare, to ensure the responsible deployment of AI.

What defines an ideal multi stakeholder body?

An ideal multi-stakeholder body for AI in healthcare in India should prioritise collaboration, knowledge sharing, and ethical guidelines. By bringing together diverse stakeholders, including healthcare providers, technologists, policymakers, and ethicists, this body can foster a conducive environment for responsible AI adoption. To achieve this, the body should focus on hosting dialogues to facilitate knowledge sharing and the exchange of best practices. It should develop ethical guidelines and technical standards to ensure responsible AI deployment while fostering collaboration among healthcare providers, technology firms, and academic institutions. Additionally, the body should support research initiatives and provide resources to drive innovation in AI-driven healthcare solutions. For instance, the Elsevier board in India is working to incorporate these key values to create an ideal multi-stakeholder body in AI-driven healthcare. 

Way forward 

The AI supply chain—spanning developers creating algorithms, deployers integrating AI into healthcare systems, and users such as medical practitioners and policymakers—must work in unison to ensure AI systems are ethical, transparent, and centered on patient care. Policymakers and regulators also play a pivotal role in crafting clear and effective frameworks for responsible AI development and deployment. By fostering collaboration between diverse stakeholders, India can leverage the power of AI to revolutionise its healthcare system. 

References:

1. https://www.prnewswire.com/news-releases/worldwide-digital-health-market-to-hit-504-4-billion-by-2025-global-market-insights-inc-300807027.html#:~:text=Hamburger%20menu-,Worldwide%20Digital%20Health%20Market%20to%20Hit%20$504.4%20Billion%20by%202025,geriatric%20population%20in%20the%20country.
2. https://www.elsevier.com/en-in/resources/clinician-of-the-future-2023
3. https://assets.ctfassets.net/o78em1y1w4i4/kWTSca6VXZ54DBhAIYxJU/386d36dc0c03c4fa8de0365bbb2043e1/Insights_clinician_key_findings_toward_ai.pdf
4. https://gdhp.health/work-streams/policy-environments/