An AI workflow handoff map describes how work moves from an input through AI assistance, human review and an authorized decision to an accepted outcome. Its purpose is to expose the steps that a faster draft can hide. The map is a leadership discussion tool, not a security assessment, software specification or authorization to automate a process.
The AI and organizational design guide explains why roles and handoffs matter. This worksheet makes one workflow explicit before a team changes it. Use approved tools and information-handling arrangements; do not enter confidential records into an unapproved AI service for the sake of completing a map.
Map the current process first
Choose a bounded, low-risk example such as drafting an internal summary from approved non-sensitive information. Record how the work happens today: the starting input, each contributor, review, decision, receiving person and condition for completion. Include waiting and rework, not just the activities someone performs.
Do not start with a future diagram that assumes every desired automation already works. A map of the actual process reveals whether a proposed change removes a constraint or moves more unfinished work to another person.
Use a row for each handoff
Copy these fields: Input; producing role or tool; output; receiving role; acceptance check; authorized decision; return route; evidence retained. Mark unknown fields as unresolved questions. An output can be complete as a draft and still be unaccepted for use.
In the illustrative summary workflow, AI produces a draft. A designated reviewer checks it against the approved source. The responsible human decides whether it can be circulated. If a claim cannot be supported, the draft returns for correction or is not used. The tool’s confidence or fluent wording does not authorize publication.
Name the human review that is actually required
Specify what the reviewer must check, what information they need and whether they have capacity to do it. A label reading “human in the loop” is not enough if nobody knows what the human is responsible for. Some tasks may require specialist approval or may not be suitable for AI assistance at all.
NIST’s AI Risk Management Framework core includes defined human-AI roles and oversight. This map is our editorial discussion aid, not proof of NIST compliance or a complete risk-management program.
Mark failure and return conditions
Identify when the team should not use the output: unsupported claims, an unavailable required source, an unauthorized input or a review that cannot be completed. Name who handles the question and what happens to work already waiting downstream.
Use established organizational incident and approval processes when required. Do not infer that a manager can change data access, security controls or high-impact decision responsibilities merely because the map reveals a delay.
Compare the whole cycle
Record drafting, review, waiting and rework for comparable work before and during a bounded test. Count accepted usable output, not just generated documents. The AI pilot scorecard helps review total effort and quality alongside speed.
If faster production makes the review queue longer, investigate the handoff rather than declaring success from drafting time alone. Discuss the leadership and operating design with Shannon using a non-sensitive example of the workflow you want to improve.
About this resource: Prepared with AI-assisted drafting. Examples and templates are illustrative, not reported client outcomes, a validated assessment or a substitute for required policies and qualified supervision.