Artificial intelligence is becoming increasingly common in healthcare. According to Elsevier’s Clinician of the Future 2026 survey, 48% of Indian clinicians now use AI in their daily practice
As AI becomes part of clinical workflows, questions around training, trust, governance, and responsible use continue to gain importance.
- Should clinicians rely more on clinical-specific AI rather than general AI tools?
- What are the biggest challenges in integrating AI into healthcare?
- How can medical institutions better prepare doctors and students to use AI responsibly?
Share your experiences and perspectives in the comments.
MBH/PS
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An important discussion!
I think AI has tremendous potential to support healthcare but it should complement, not replace clinical judgement. Proper training, validation and responsible use will be key to building trust and improving patient care.
I believe clinicians should use clinical-specific AI tools because they are designed for healthcare and can provide more relevant, evidence-based support. The biggest challenges are data privacy, accuracy, lack of training, and over-reliance on AI. Medical institutions should provide proper AI education and training so doctors and students can use it responsibly while keeping clinical judgment at the centre.
In today’s highly evolving and fast-paced healthcare sector, AI implementation is definitely a necessity. If you don’t integrate AI for sorting management of daily tasks and speed up your workflow, you will be left behind by your competitors. But always keep in mind being the exploiter of AI, not being dependent on AI for even deciding what to do. Critical thinking and final judgment-making are always kept under your own control.
AI can be very useful in health care, but it cannot replace doctors. AI has to be used wisely. Ai can help to improve diagnosis, treatment plan, and so many things, but it cannot replace the empathy and support that human provides.