MEET DR. DOMUCH

AI WILL BE A FORCE MULTIPLIER IN SHAPING REAL CLINICAL OUTCOMES AND TRANSFORMING HOW HEALTHCARE REACHES THE UNDERSERVED WHILE FORCING HARD QUESTIONS ON REGULATION

- Geetha Manjunath

Artificial Intelligence has crossed a critical threshold in healthcare. We are no longer debating whether AI can work in clinical care—we are now grappling with how it should work, who it should serve, and under what guardrails it must operate. As we move into 2026, ΑΙ promises to reshape diagnostics, personalise treatment pathways and even influence how clinical trials and experiments are designed. Yet alongside this promise lie fundamental challenges around liability, regulation, trust and the evolving role of clinicians.

Al's earliest successes in healthcare were largely technical—recognising patterns in images, signals and large datasets faster than humans could. Today, that capability is translating into real clinical value. In radiology and pathology, AI systems are demonstrating their ability to flag subtle abnormalities, prioritise high-risk cases and reduce diagnostic delays, particularly in primary care and preventive health. AI is enabling risk stratification at scale—identifying individuals who may otherwise never enter the healthcare system until disease has progressed.

At Niramai, we have seen this firsthand through Thermalytix, an AI-based breast cancer screening solution that combines thermal imaging with machine learning to detect early physiological changes associated with malignancy. The technology itself is important, but the larger lesson is this: AI can extend clinical reach. It can bring screening and triage closer to where people live and work, rather than forcing healthcare to remain confined within hospital walls.