When your AI workflow produces work, but not results.

Follow one real item from start to finish.

Choose a recent example and ask the person who does the work to walk it through: what arrived, what the tool produced, who checked it, where it went, and what happened next. Use a sanitized example. The gap may be a missing input, a weak output, an absent owner or a failed handoff.

Define the outcome in plain language: “A person reviews an accurate draft and assigns the next action,” for example. A generated summary or a successful run alone does not prove the work was completed.

Find your next investigation.

Pick the symptom that best matches one workflow. This is a starting point, not an automatic diagnosis. Your selection stays in this browser page and is not sent to us.

Check the handoffs, not just the prompt.

• Input: Is the needed context available, current and appropriate to share? Compare an approved source with what the tool receives.
• Output: Does the result include the facts and format the next person needs? Compare a corrected example with the original.
• Destination and owner: Where should the result land, and who is responsible for the next action? A notification without an owner can become another inbox.
• Exceptions: What happens when a record is ambiguous, a connection fails or the same event arrives twice? Keep uncertain work visible for a person to resolve.

Change one thing and check the outcome.

Choose a small, reversible change. Test a normal case, a missing-input case and a failed or repeated handoff using approved examples. Record what happened, who will review exceptions and how to return to the previous process. For external messages, keep the result as a draft until an authorized person approves it.

Then use the pilot scorecard to compare completed work and corrections over a short trial. The meeting-notes guide shows a concrete handoff.