Reputation risk is the possibility that visible AI errors—such as biased recommendations or hallucinated outputs—will damage trust and credibility. The risk grows when failures affect customers directly or become public. section 12.3.2
Reduce reputational damage by making failures visible, manageable, and correctable:
- Explain limitations, error types, and likely user impact rather than presenting the system as infallible. section 12.3.2
- Use audit logs and oversight mechanisms to support transparency, accountability, and rapid correction. section 12.3.2
- Communicate through status dashboards, targeted notifications, and periodic product updates when mistakes affect users. section 12.3.2
A public-facing AI error
A customer-facing system produces biased recommendations or hallucinated outputs. Audit logs and oversight help identify and correct the problem before it escalates, while transparent customer communication focuses on improvements and next steps. section 12.3.2
