Archive
Each experiment tests AI against a real business workflow with a human baseline alongside. Newest first. Every page shows the method, the results, the failures and the limits of what was established.
Using the ten structured cases from Experiment #002, a human and an AI each assigned a priority, a next action, a reason and something to avoid. Both converged on the same operational pattern. AI was more conservative about missing information and stronger on operational prerequisites; the human was more commercially proactive and read customer psychology.
Ten synthetic packaging and printing inquiries were converted into a structured table by a human (about 30 minutes) and by an AI model. AI output was more systematic in extraction, completeness and flagging missing information. Human judgment remained stronger on commercial context. No time-saving figure was established.
We ran 10 synthetic customer inquiries through a qualification workflow — interpret the message, identify missing information, decide the next action — and compared how a human and an AI model handled them. The inquiries were incomplete more often than not, and the next action was rarely obvious.
Research updates
Get new FIELD experiments and findings when we publish them.
