AI Economics practical guide
Help the Same Team Do More: Designing Human + AI Workflows
An effective Human + AI workflow gives retrieval, organisation, extraction, classification and first drafts to AI, while exceptions, judgement, communication, commitments and final approval stay with accountable people. The goal is greater capacity, not a layoff promise.
Map the current process before buying tools
Record each step, wait, duplicate entry, source, owner, exception and approval. Without a baseline, there is no reliable way to know whether AI improved the workflow.
Define the AI-to-human handoff
Every AI output needs a purpose, trusted source, review rule, exception path and owner. Human accountability matters particularly for financial, legal, medical, employment and customer-commitment decisions.
Implementation KPI checklist
- Processing time, backlog and response time.
- Hours released, human-review rate and exception time.
- Error and rework, completion rate and source traceability.
- AI cost and cost per completed workflow.
Method references and review date
These sources provide related definitions, frameworks or implementation considerations. The method is synthesised by iGears and is not a fixed provider quotation or an outcome promise.
Last reviewed: 30 August 2026
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