Artificial intelligence is rapidly entering healthcare workflows. We are engaging intelligent interfaces around clinical management and encountering intelligence embedded into electronic health records, ambient scribes, prescribing tools, as well as patient facing systems. These tools are powerful, and adoption is accelerating.
Yet most are trained on international data and lack alignment with local clinical standards, regulatory expectations, and health system realities. AI systems remain prone to hallucinations; responses may not be reproducible or auditable, and foreign systems may conflict with local data, intellectual property, and privacy regulations.
The issue is no longer whether AI will be used in healthcare. It already is, and the consequences are already unfolding.
The real question is what kind of intelligence powers these systems, and whether it can be trusted to support safe decisions within our context.