AI can accelerate analysis and routine work, but operational accountability still depends on context, review and clearly assigned human responsibility.
Use AI where the task is clear
AI is most useful when the task, input and expected output are well bounded: summarising documents, classifying information, identifying patterns or assisting a user in finding relevant knowledge.
Keep judgement close to consequence
Where an output can materially affect a person, payment, entitlement, clinical decision or administrative action, the operating design should specify who reviews the output and who remains accountable for the final decision.
Make uncertainty visible
A system should not present generated output with more certainty than the underlying data supports. Source visibility, review states and exception paths help users understand when additional verification is needed.
Govern the whole operating loop
Responsible use is not only a model question. Data quality, access controls, prompts, source material, logging, user training and escalation processes all affect whether AI behaves safely and usefully in practice.