Define what makes an output acceptable before assigning a task to AI.
Redshift perspective · Revised 15 October 2026.
Start with a task, not a demo
Summarising specifications, suggesting tests or matching labels each requires a clear scope. Define permitted inputs and expected outputs before selecting a tool.
Plausible can still be wrong
A proposed mapping may miss a business rule. A test may omit an exception. Have the process owner review outputs; keep the sources and useful corrections.
Measure the entire job
Compare preparation, generation, review and correction time against your existing method. Counting only generation time makes a good demo, not a business case.
Set operational limits
Do not send client data to a service without approval of its use. Document access, confidentiality rules and the final decision owner. Start with synthetic data. Autonomy should be earned through evidence.
AI as the electricity of ERP
The analogy matters: connecting a tool says little about its value. A polished steering summary can miss a major risk. A convincing demo can fail on a business exception. Compare output with a source and an expected result, not just its wording.
Test the process, not just the model
For a proposed action in Procure-to-Pay, what data feeds it, which control spots inconsistencies and who approves execution? Document exceptions, permissions, traces and manual recovery. These are process-design questions, not a prompt competition.