AI Output Needs Too Much Checking
When reviewing and correcting AI output takes as long as doing the work, the workflow may be moving effort rather than saving it.
Measure the whole task
Include preparation, prompting, retrieval, checking, corrections and escalation. Compare equivalent cases with the existing process rather than counting only generation time.
Use review rules tied to consequences
Separate low-impact drafts from actions involving money, customers or system changes. Define what evidence a reviewer must see, what they can approve and which uncertainties require escalation. A model confidence score alone is not sufficient evidence.
Reduce avoidable review work
Use constrained outputs, approved source material and clear acceptance criteria. Route incomplete or contradictory inputs to a person instead of generating a plausible answer that someone must unravel.
What to prepare for a review
Bring a short workflow description, representative examples, available evidence and the outcome you expected. Start with anonymised examples; agree a secure method before sharing sensitive records.
Get help with this workflow
Explore AI Workflow Redesign for a scoped independent review.
Tell us where AI is getting stuck
Describe the workflow, what you expected and what is happening instead. We will clarify the scope and information needed for a review.
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