Dilip Jose, Chief Executive Officer of Manipal Hospitals, has emphasised that while artificial intelligence (AI) holds transformative potential for healthcare, its deployment must be approached with caution and supported by robust ethical and regulatory frameworks. Speaking at a recent industry forum, Jose highlighted that patient safety, data protection, and ethical governance should be prioritised before scaling AI solutions across clinical settings.

Jose noted that although AI technologies can significantly enhance diagnostic accuracy, operational efficiency, and clinical decision-making, healthcare organisations must first establish strong guardrails to safeguard sensitive patient information and uphold trust in medical systems. “Before widespread implementation of AI in healthcare, it’s essential to build clear regulatory and ethical guardrails that ensure patient privacy, clinical accountability and safety,” he said, underscoring growing concerns around data security in sensitive health contexts.

The call for structured governance aligns with emerging global discussions on responsible AI use, where frameworks and standards are being developed to guide the safe, effective and ethical deployment of AI in medicine. Consensus-driven guidelines such as the FUTURE-AI recommendations advocate for fairness, transparency, explainability and accountability in AI systems  from design through clinical use — to build trust among clinicians and patients alike.

Healthcare leaders have increasingly recognised that rapid innovation must be balanced with caution. Integrated governance, transparent validation processes, and compliance with regulatory requirements are key to ensuring that AI-enabled tools complement clinical expertise rather than supplant it. As Jose emphasised, without strong guardrails and clear accountability, the risks associated with AI deployment in high-stakes medical environments could outweigh its benefits.

The remarks come amid heightened interest in AI applications across the healthcare continuum  from predictive diagnostics and personalised treatment planning to workflow automation and remote patient monitoring  underscoring the urgency of establishing robust policies and ethical norms that can guide responsible innovation.