Exception-based human review

There are roughly three ways to put AI into a workflow that used to be manual:

Model	Who does the default path	Where people spend their time
Human-first	People, with AI suggestions	Every item
Fully autonomous	AI	Nowhere, until something breaks
AI-first, exception review	AI	Only the items automation failed or got wrong

I prefer the third. People stay in the process, but their attention goes to the cases that need it.

What it needs

• A clear signal for “this needs a person”: a failed step, a validation rule that didn’t pass, or a likely duplicate.
• A review tool built for correcting things quickly, since that’s all reviewers do there.
• A way back into the automated path once an item is fixed.

Where I’ve applied it

• An AI-first OCR pipeline, with people for the exceptions: document classification and OCR extraction on Cloudflare Workers, with human review for failures and corrections.
• Human handoff in support automation is a related shape in customer support: automation and AI-assisted replies first, with a handoff to a person.

Being honest about it

“AI-first” sounds like a claim about accuracy, but it isn’t one. Without measured accuracy and throughput, all I can say is how the workflow is shaped, not how well it performs.