Marketing Operations Practical insights
Prepare a marketing AI incident runbook
Prepare clear owners for pausing AI campaigns, investigating affected channels and approving corrections when inaccurate marketing content reaches customers.
A marketing AI incident runbook turns an urgent mistake into a sequence of accountable actions. It should help a colleague contain the problem even when the original workflow owner is unavailable. Start with a realistic scenario rather than a long list of abstract risks.
Choose the incident and stopping action
Use an example such as an unsupported price claim appearing in several live ads. Identify who may pause the affected automation, which channels need separate action and how queued content is handled. NIST’s AI risk-management material provides a framework for organizing responsibilities and responses; it is not a guarantee of legal compliance. [1]
Preserve enough evidence
Record the affected asset, campaign ID, publication time, source material and relevant configuration version. Capture evidence before editing when practical, while prioritizing containment. Limit access to sensitive records. The team needs to establish what happened without circulating unnecessary customer information.
Assign correction and communication owners
Separate the decision to stop distribution from the decision about replacement wording or customer communication. In the illustrative price incident, product and commercial owners should establish the correct offer before a new version goes live. Check every placement rather than assuming a correction in one tool updates all copies.
Define the restart decision
Require evidence that the immediate fault is corrected and that related assets were checked. Record who authorizes restart and how the next run will be monitored. Afterward, update the source, instruction or control that allowed the problem. Rehearse the runbook periodically with a harmless example so that contact details and pause instructions work when time is limited.
Sources and evidence
Sources checked on 4 October 2026. Proposed workflows and hypothetical examples are editorial analysis.
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