The healthcare sector is evolving at an extraordinary pace, driven by new technologies and a rapidly expanding body of clinical knowledge. Healthcare professionals (HCPs) are under growing pressure to stay current with massive growth in information, emerging innovations and shifting best practices, all while managing rising patient demands. Among these innovations, artificial intelligence (AI) is transforming how diagnosis, treatment and care are delivered. AI tools have the potential to support clinical decision-making, streamline workflows and enable more personalised care.
However, the adoption of AI in healthcare brings challenges. These include the risk of clinical errors, misinformation from generative AI, limited transparency in how outputs are generated and algorithmic bias that could exacerbate existing health disparities. To mitigate these risks, AI technologies must be rigorously validated, responsibly deployed and thoughtfully integrated into clinical workflows.
To fulfil AI’s potential, it must be designed to work for every patient, not just those who are well-represented in training data sets. This calls for a thoughtful coordinated approach to development and implementation. It includes designing clinical decision support (CDS) systems that reflect the diversity of patient populations, integrating AI in ways that enhance care without introducing new barriers and ensuring HCPs are equipped to use these tools effectively.
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