What Healthcare Leaders Should Ask Before Buying Clinical AI

Questions about evidence, workflow, accountability and monitoring before clinical AI reaches patient care.

Demand evidence for the intended setting

Performance can change across patient populations, equipment and clinical environments. Ask how the system was evaluated, which groups were represented and whether the proposed use matches the evidence. A general accuracy figure rarely explains clinical usefulness.

Map the human decision process

Leaders should define who reviews output, how disagreement is handled and when the tool must not be used. Training and workload matter: a system that adds alerts or duplicate documentation may reduce rather than improve care quality.

Plan monitoring before procurement

Model updates, changing practice and local data can affect results. Contracts should cover version changes, incident reporting, data handling and exit support. Assign accountable clinical, technical and governance owners before deployment rather than after a problem occurs.