A lot of responsible AI conversation focuses on the risks of moving too fast, but there's another risk that gets less attention: standing still.
The status quo has real costs. Staff burning hours on manual data entry. Managers rebuilding the same reports every month. Critical information living in someone's head or a spreadsheet no one else can find.
Responsible AI isn't just about deploying carefully, it's about being honest about what avoiding it costs too. Burnout, inefficiency, and errors from manual processes are also patient safety issues.
The question isn't just "is this AI safe to use?" It's "what's the cost of not using anything better than what we have now?"
What this means for health organizations
When you assess an AI tool, weigh its risks against the risks of your current process, not against a perfect one. Measuring how much time today's process takes, and how often it produces errors, gives you a fair baseline.
