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Scope a mandate

Adoption · Operating decision guide

AI training that proves independent task performance

Otomat editorial · Revised 23 October 2026

A role-based competency rubric using fresh tasks, exception handling, correction effort and maintenance/restoration evidence.

  • Train for the task and its exceptions
  • Agree the rubric before rollout
  • Remediate and reassess on fresh work
  • Maintain competence after changes

Train for the task and its exceptions

Attendance and logins show participation, not capability. Agree what each role must do independently and what must be escalated. Use realistic authorized tasks for practice, then different held-out tasks for assessment. Include missing sources, conflicting information and requests outside scope.

Record eligible users, intended task frequency, accepted completion, correction time, escalations and sustained use over an agreed period. Make the denominator visible. A model upgrade that saves generation time but doubles review effort may worsen the workflow.

Agree the rubric before rollout

Set task-specific numerical thresholds with the functional owner before assessment; there is no universal pass rate. Critical unauthorized actions fail the gate regardless of an average score. Record accommodations and permitted reference materials so assessment measures the real job.

Competency evidence rubric
RoleFresh assessmentEvidence / gate
ExecutiveDefend a go/no-go decision from baseline, full cost and riskCan explain uncertainty, alternatives and retained human decisions
StaffComplete normal and exception tasksAccepted result; correct escalation; review effort within agreed limit
Power userReproduce a failure and propose a bounded fixSource/version identified; evidence preserved; no policy bypass
Maintainer + backupChange, evaluate, release and restoreIndependent record; held-out tests; rollback succeeds

Remediate and reassess on fresh work

Classify failures as unclear procedure, missing knowledge, interface problem, model quality or permission problem. Assign the corrective action to the responsible owner. Retest on new cases and track reviewer effort; repeated coaching on the same example does not demonstrate transfer.

Maintain competence after changes

Material workflow or model changes need targeted reassessment. Primary and backup maintainers each perform an approved change and restoration without the builder taking over. Keep open limitations and support coverage visible in the handover record.

Use the working tools

Blank templates are ungated. Adapt them to the workflow; inputs are not submitted.

  • Open the operating charter
  • Open the value worksheet

Sources and limits

These are Otomat’s proposed operating methods and original decision artifacts. External references inform risk management; they do not certify this method or establish client results. Linked sources were selected for this review; their live revision dates may change.

  • NIST AI Risk Management Framework (2023)

For anonymous documentation and proposal patterns, see delivery evidence and its boundaries.

Related decisions

  • A 100-day AI plan with evidence gates
  • AI-agent permissions: define the data and action boundary

Bring a workflow to the discussion

Share the business goal and constraints through the mandate process. Do not send sensitive production data in the initial brief.

Scope an Operating Mandate
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