Individual
The person can ground output, verify it, and own the result as part of normal professional work.
Grounding, validation, ownership, and handoffs are becoming routine. The focus is now operational reliability: reducing reinvention while keeping responsibility and evidence visible.
The person can ground output, verify it, and own the result as part of normal professional work.
AI is part of the shared workflow, with increasingly stable handoffs, validation, backup coverage, and ownership.
Workflow, governance, and measurement are becoming connected instead of operating as separate initiatives.
Normal use is not the same as reliable use. Check whether controls survive exceptions, turnover, and higher consequence work.
Framing the task, desired outcome, and constraints is a normal part of the workflow.
People use approved or relevant sources and make assumptions and limits visible.
Review thresholds are explicit and increase when the consequence of error increases.
The AI-assisted sequence is part of normal operations and does not depend on one champion.
Handoffs, accountability, disclosure, and escalation paths are clear.
Correction load, exceptions, and near misses are used to improve the shared practice.
Assuming adoption means integration. A workflow can be popular and still lack grounding, review, ownership, or a safe response to failure.
Controls and evidence hold during normal variation, people can support one another, and the practice is stable enough to teach without hiding its limits. Continue to Leading, or take the assessment.
Use the AAOS stages to inspect and improve the complete operating loop.