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A. Data & Privacy
B. Security
C. Safety
D. Reliability
E. Accountability
AI failure plan for security breachesAI failure plan for harmful outputsAI failure plan for hallucinationsAssign accountabilityDocument data storage securityConduct vendor due diligence[Retired] Document system change approvalsReview internal processesMonitor third-party accessEstablish AI acceptable use policyRecord processing locationsDocument regulatory complianceImplement quality management system[Retired] Share transparency reportsLog AI system activityImplement AI disclosure mechanismsDocument system transparency policy
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E. Accountability
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E003. AI failure plan for hallucinations
E003

AI failure plan for hallucinations

Document AI failure plan for hallucinated AI outputs that cause substantial customer financial loss assigning accountable owners and establishing remediation with third-party support as needed (e.g. legal, PR, insurers)

Keywords

HallucinationsIncident ResponseCustomer Loss

Application

Mandatory

Frequency

Every 12 months

Type

Preventative

Crosswalks

EU AI Act
Article 20: Corrective Actions and Duty of Information
Article 73: Reporting of Serious Incidents
ISO 42001
A.8.4: Communication of incidents
NIST AI RMF
GOVERN 4.3: Testing and incident sharing
MANAGE 1.3: Risk response planning
MANAGE 4.3: Incident communication
CSA AICM
BCR-09: Disaster Response Plan
BCR-10: Response Plan Exercise
SEF-09: Incident Response
IBM AI Risk Atlas
IBM 9: Agentic AI - Function calling hallucination
IBM 71: Output - Hallucination
IBM 89: Non-Technical - Legal accountability

Control activities

Typical evidence

Establishing compensation assessment procedures. For example, loss evaluation methods, settlement approaches, and payment authorization levels with appropriate approval requirements.
Implementing remediation measures. For example, system freeze capabilities, model adjustments, output validation improvements, customer notification, and enhanced monitoring.
E003.1 Documentation: AI failure plan for hallucinations

Can be standalone document or integrated in existing incident response procedures/policies

Category

Operational Practices
AI failure plan
Text-generationVoice-generation
Defining hallucination incident types.
Coordinating potential external support. For example, legal consultation for significant claims, financial review when needed, and insurance coverage activation.
E003.2 Documentation: Additional hallucination failure procedures

May include hallucination incident categories (e.g. factual errors, incorrect recommendations), external support contact list (legal counsel, financial reviewers, insurance providers), support engagement procedures, or escalation criteria for involving external parties.

Category

Operational Practices
AI failure plan
Text-generationVoice-generation

Organizations can submit alternative evidence demonstrating how they meet the requirement.

AIUC-1 is built with industry leaders

Phil Venables

"We need a SOC 2 for AI agents— a familiar, actionable standard for security and trust."

Google Cloud
Phil Venables
Former CISO of Google Cloud
Dr. Christina Liaghati

"Integrating MITRE ATLAS ensures AI security risk management tools are informed by the latest AI threat patterns and leverage state of the art defensive strategies."

MITRE
Dr. Christina Liaghati
MITRE ATLAS lead
Hyrum Anderson

"Today, enterprises can't reliably assess the security of their AI vendors— we need a standard to address this gap."

Cisco
Hyrum Anderson
Senior Director, Security & AI
Prof. Sanmi Koyejo

"Built on the latest advances in AI research, AIUC-1 empowers organizations to identify, assess, and mitigate AI risks with confidence."

Stanford
Prof. Sanmi Koyejo
Lead for Stanford Trustworthy AI Research
John Bautista

"AIUC-1standardizes how AI is adopted. That's powerful."

Orrick
John Bautista
Partner at Orrick
Lena Smart

"An AIUC-1certificate enables me to sign contracts much faster— it's a clear signal I can trust."

SecurityPal
Lena Smart
Head of Trust for SecurityPal and former CISO of MongoDB