The Indian Express opinion piece explains that as artificial intelligence (AI) systems enter healthcare, discussions must go beyond technical innovation to focus on equity, governance and real-world impact rather than just algorithmic performance. Historically, digital health tools have been introduced piecemeal — through pilots or isolated hospital systems — with regulation lagging behind innovation, resulting in fragmented standards and unclear accountability when harm occurs. The authors argue that treating AI as merely an add-on to clinical practice fails to address deeper systemic issues in health systems that determine how well the technology works for everyone.
India’s new national strategy for using advanced computational systems in healthcare is highlighted as a structural shift — one that treats AI not as a peripheral tool but as part of the health system architecture itself. This approach emphasises building interoperable health records, consent-based data exchange, and nationally aligned standards before deploying AI, recognising that computational tools will reflect the data and institutions that sustain them. Without broad-based infrastructure, AI risk reinforcing existing weaknesses — especially in underserved or rural areas where data and resources are uneven.
A major theme of the article is that fairness must be a design principle, not an afterthought. In diverse societies, current datasets often over-represent urban, insured populations while under-representing marginalised groups, which can lead AI systems to perpetuate or worsen health inequities if safeguards aren’t built in from the start. To prevent this, the strategy advocates for representativeness and equity impact assessments, continuous monitoring, reassessment, and governance throughout an AI system’s lifecycle — rather than one-time approvals at launch.
The authors also note that effective AI governance depends on human capacity and oversight: clinicians must understand limitations, administrators must interpret outputs responsibly, and regulators must grasp risks. Policies around public procurement, interoperability, and clear pathways from pilot projects to scaled deployment are viewed as instruments of stewardship. Ultimately, the article suggests that success will be measured not by technological sophistication alone but by whether AI strengthens trust, widens access, and protects the most vulnerable in health systems.
