The proposed AI Incident Reporting Act mandates that developers of advanced AI models report major safety and security incidents to the Commerce Department within seven days of discovery. With civil penalties reaching up to $2 million for violations, your compliance team needs a clear framework now—before the law takes effect.
This checklist helps you prepare for AI incident reporting obligations. Whether you're building AI systems in-house or deploying third-party models, these steps establish the foundation for compliance with federal oversight requirements.
Prerequisites
Before working through this checklist, ensure you have:
- Inventory of AI systems: A complete list of AI models your organization develops or deploys, including their risk classifications.
- Incident response team: Designated personnel with authority to make reporting decisions.
- Legal counsel access: Ability to consult attorneys familiar with federal reporting requirements.
- Documentation system: A secure repository for incident records that supports audit requirements.
Checklist Items
1. Define Your AI System Scope
Action: Document which AI systems fall under "advanced AI models" that would trigger reporting obligations.
Verification: You have written criteria that classify each AI system by risk level, computational requirements, and potential impact domains. Each system has a documented determination of whether it meets the threshold for federal reporting.
Ideal Outcome: A registry where every AI model has a risk classification (high/medium/low), deployment context, and a yes/no flag for federal reporting obligations. Your legal team has reviewed and approved the classification methodology.
2. Establish Incident Detection Mechanisms
Action: Implement monitoring that can detect incidents likely to trigger reporting requirements—model behavior anomalies, security breaches, safety failures, or unintended harmful outputs.
Verification: Your monitoring generates alerts for predefined incident types. You have documented thresholds for each alert category and tested that alerts reach the incident response team within your internal SLA.
Ideal Outcome: Real-time dashboards showing model performance metrics, security event logs with automated anomaly detection, and integration with your existing SIEM or security operations center. Weekly summary reports confirm the monitoring is active.
3. Create Incident Classification Criteria
Action: Define what constitutes a "major safety or security incident" for your AI systems, including specific examples and edge cases.
Verification: You have written definitions for incident severity levels that map to reporting requirements. Your team can consistently apply these definitions—test this by having three people independently classify the same hypothetical incident and compare results.
Ideal Outcome: A decision tree or flowchart that guides responders from initial detection to reporting determination. Include examples: "Model generates discriminatory outputs affecting 100+ users = reportable" or "Attempted unauthorized access to training data without exfiltration = not reportable under this law but document for cybersecurity reporting."
4. Document Your Seven-Day Reporting Process
Action: Map out every step from incident detection to Commerce Department notification, with time allocations and responsible parties for each phase.
Verification: The total timeline from detection to submission fits within seven days with buffer time for delays. Each step has a named owner and backup owner.
Ideal Outcome: A process diagram showing: Detection (Day 0) → Initial assessment (Hours 1-4) → Legal review (Hours 4-24) → Technical investigation (Days 1-3) → Report drafting (Days 3-5) → Executive approval (Day 5) → Submission (Day 6). You've documented what happens if Day 6 falls on a weekend or federal holiday.
5. Prepare Reporting Templates
Action: Create standardized templates for the information you'll need to submit to the Commerce Department.
Verification: Your templates include fields for all likely required information: system description, incident timeline, affected parties, root cause analysis, remediation steps, and ongoing risks.
Ideal Outcome: Pre-filled templates with your organization's basic information, system descriptions for each AI model, and dropdown menus for incident types. You've mapped your internal incident classification to the federal reporting categories. Legal has reviewed the language for accuracy without admitting liability unnecessarily.
6. Assign Reporting Authority
Action: Designate who has authority to submit reports to the Commerce Department and establish escalation paths.
Verification: You have documented delegation of authority that covers normal business hours, weekends, holidays, and scenarios where the primary contact is unavailable.
Ideal Outcome: A RACI matrix showing who is Responsible, Accountable, Consulted, and Informed for each reporting decision. The Accountable person has written authorization to speak on behalf of the organization to federal regulators.
7. Integrate with Existing Incident Response
Action: Connect AI incident reporting requirements to your current incident response playbooks for cybersecurity, privacy, and other regulatory obligations.
Verification: Your cybersecurity incident response plan explicitly addresses AI systems. You've identified where AI incidents might also trigger other reporting requirements, such as NIST CSF guidelines or state breach notification laws.
Ideal Outcome: A unified incident response runbook where AI incidents flow through the same initial triage as other security events, with branching logic that adds AI-specific steps. Your team understands that a single incident might require multiple reports to different agencies with different timelines.
8. Establish Record Retention
Action: Define how long you'll retain incident records and supporting documentation.
Verification: You have a documented retention policy that meets or exceeds likely federal requirements and your organization's standard retention schedules.
Ideal Outcome: Automated archiving of incident reports, investigation notes, communications, and technical logs to a secure, immutable storage system. Records are tagged with retention dates and legal hold flags. You can retrieve a complete incident file within 24 hours if regulators request it.
Common Mistakes
Waiting for final regulations: The bill authorizes the Commerce Department to define specific requirements, but waiting for those details means you're starting from zero when deadlines hit. Build the framework now; adjust the details later.
Treating this as a legal-only problem: Your legal team can't write incident reports without technical input. Compliance requires collaboration between legal, engineering, security, and executive leadership.
Assuming your cyber incident response plan covers AI: Traditional cybersecurity incident response focuses on confidentiality, integrity, and availability. AI incidents might involve none of these—a model that generates biased outputs or fails at its intended task creates compliance obligations that your CISO's playbook doesn't address.
Over-reporting to avoid penalties: Flooding the Commerce Department with marginal incidents creates its own compliance risk. You need clear thresholds, not a policy of "report everything to be safe."
Next Steps
Schedule a tabletop exercise: Walk through a hypothetical AI incident with your cross-functional team. Time how long each phase takes and identify gaps in your process.
Review vendor contracts: If you're deploying third-party AI models, determine who bears the reporting obligation—you or the vendor. Get this in writing.
Monitor the regulatory process: Track the bill's progress and Commerce Department rulemaking. Assign someone to review Federal Register notices and update your procedures as requirements solidify.
Document your current state: Even if you're not ready to check every box on this list, document where you are today. When auditors or regulators ask what you did to prepare, "we assessed our gaps in Q2 2024" is better than "we didn't think it applied to us."
The seven-day reporting window doesn't start when regulations are finalized—it starts when you discover an incident. Your compliance posture depends on decisions you make before that clock begins.
