Why AI Governance Matters Before You Deploy a Single Algorithm

The race to deploy AI in clinical settings is accelerating. Radiology AI, pathology AI, clinical decision support — the pipeline of CE-marked and FDA-cleared tools has never been fuller. But governance frameworks are falling behind, and that gap is where risk lives.

Good AI governance is not about slowing deployment. It is about ensuring that what you deploy actually performs in your population, with your workflows, under your regulatory requirements. A tool validated on European data may behave differently in a Gulf population. A workflow assumption baked into the algorithm may not match your radiology department's reporting structure.

Start with a governance committee before the first vendor conversation. Define your AI principles, your evaluation criteria, your post-deployment monitoring cadence. Make it clinical-led, with technology as a support function. The organisations getting the most value from AI are the ones who treated governance as the foundation, not the afterthought.