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Radar AI Incident Management
AI Incident Management
AI introduced a new class of incidents that organizations were never designed to manage.
RadarFirst gives teams a purpose-built, repeatable way to investigate AI incidents, assess potential impact, coordinate response, and document every decision with consistency, accountability, and traceability.
AI Introduced a New Class of Incidents
Organizations know how to respond to cybersecurity and privacy incidents.
AI introduces a different set of questions.
What AI system was involved? How did it contribute?
What role did your organization play? What harm occurred?
Who needs to be involved? And what regulatory or reporting obligations could follow?
Traditional incident processes weren’t built to answer those questions consistently.
RadarFirst turns AI incident management into a repeatable process.
Investigate What Happened
Capture the AI system involved, how it behaved, your organization’s relationship to it, resulting impacts, supporting evidence, and business context.
- Capture AI-specific incident details
- Collect evidence and context
- Accelerate investigation
- Reduce information gaps
Assess What It Means
Evaluate potential privacy, legal, operational, financial, reputational, fairness, and safety impacts through a consistent, explainable process.
- Assess impact and potential harm
- Apply structured regulatory intelligence
- Reduce subjective interpretation
- Support consistent decisions
Coordinate What Happens Next
Bring legal, privacy, compliance, security, product, and business teams together around one response.
- Coordinate investigation and remediation
- Manage escalation and approvals
- Support communications
- Maintain accountability
Platform Capabilities
Every AI Incident Is Different. Your Response Shouldn’t Be.
RadarFirst provides one consistent operational process for managing AI incidents from intake through assessment, guidance, and documentation.
Understand what happened.
- Capture AI-specific incident details, evidence, impacts, and business context with structured intake
Determine what it means.
- Evaluate potential harm and risk using a repeatable, deterministic assessment process designed for the unique characteristics of AI incidents.
Know what to do next.
- Apply regulatory intelligence and structured guidance to identify potential obligations, escalation paths, and response actions.
Prove why you did it.
- Maintain a complete, defensible record of the incident, assessment, rationale, actions, and outcome.
What is an AI Incident?
An AI incident is an event where an AI system or its output causes — or may cause — harm, risk, a policy concern, or a need for investigation or response.
Harmful or Unexpected Outputs
Investigate AI-generated content, recommendations, or decisions that create customer, business, or operational harm.
Privacy & Sensitive Data
Respond to AI incidents involving personal information, inferred data, unauthorized processing, consent, or inappropriate disclosure.
Bias & Discrimination
Investigate potentially unfair, biased, or discriminatory AI behavior and outcomes.
Unauthorized AI & Policy Violations
Respond when AI use falls outside approved policies, governance requirements, or acceptable-use standards.
Safety & Operational Harm
Respond to AI incidents that create physical, financial, safety, or operational impacts.
Features
From AI Incident to Operational Response
Purpose-built capabilities to investigate AI incidents, assess impact, guide response, and maintain a complete, defensible record.
- AI-specific incident intake
- Consistent impact assessment
- Deterministic regulatory guidance
- Cross-functional response
- Explainable system of record
Process
From AI Incident to Operational Response
Intake
Eliminate blind spots with structured incident intake.
Assessment
Evaluate applicability, risk, and obligations in minutes.
Guidance
Apply regulatory logic and decision-making models to reach consistent outcomes.
Documentation
Maintain complete, audit-ready records without manual effort.
Why RadarFirst
Built on Proven Incident Management
RadarFirst brings years of regulatory incident management experience to a new category of AI incidents.
Purpose-Built for AI
Manage AI incidents as a first-class category — not an extension of a privacy or generic compliance workflow.
Powered by RadarFirst’s Legal Engine
Apply regulatory logic consistently to reach explainable, defensible decisions.
Explainable by Design
Maintain the rationale and traceability behind every assessment, recommendation, action, and outcome.
Explainable by Design
Maintain the rationale and traceability behind every assessment, recommendation, action, and outcome.
FAQs
Frequently Asked Questions
Explore the questions privacy, legal, compliance, security, and AI leaders ask as they prepare for, respond to, and operationalize AI incidents across the enterprise.
What is AI Incident Management?
AI Incident Management is the process organizations use to investigate, assess, respond to, and document incidents involving AI systems or their outputs.
It creates a consistent operational response when AI causes potential harm, violates policies, exposes sensitive information, or requires investigation.
What is considered an AI incident?
An AI incident is an event where an AI system or its output causes—or may cause—harm, risk, a policy concern, or a need for investigation or response.
Examples include harmful outputs, bias, hallucinations, privacy concerns, unauthorized AI use, safety issues, policy violations, and security events.
How is AI Incident Management different from AI governance?
AI governance manages AI risk before an incident occurs. AI Incident Management manages the operational response when one does.
AI governance focuses on inventory, risk classification, policies, controls, and oversight. AIM focuses on investigation, assessment, guidance, response, and documentation.
How is an AI incident different from a privacy or cybersecurity incident?
AI incidents introduce context traditional incident processes may not capture, including the AI system involved, its behavior, the organization’s relationship to it, resulting harms, and AI-specific regulatory considerations.
An AI incident may also overlap with a privacy or cybersecurity incident.
Why do organizations need AI Incident Management now?
As AI adoption grows, so does the number and variety of incidents organizations need to investigate.
Most organizations still rely on processes built for privacy, cybersecurity, or general compliance. AIM provides a repeatable process built for the distinct characteristics of AI incidents. This directly reflects the customer challenge identified in the GTM talk track.
Can generative AI manage an AI incident?
Generative AI can help analyze information, but its outputs can vary. RadarFirst’s patented Legal Engine applies deterministic regulatory logic consistently to support explainable, defensible incident decisions.
Does RadarFirst automatically make AI incident decisions?
No. People remain accountable for decisions. RadarFirst’s patented Legal Engine applies regulatory logic to provide consistent, explainable assessment and guidance.
What teams are involved in AI Incident Management?
AI incident management can involve privacy, legal, compliance, security, product, AI governance, and business teams.
RadarFirst brings those teams together around one consistent incident process and system of record.
Featured Resource
When AI Goes Wrong:
Turning AI Harm into an Incident Response Process
This three-part white paper series examines AI harms through an operational incident-response lens.
Each paper provides expert insights on how organizations define AI incidents, build a structured and defensible response framework, and make critical decisions about causality, severity, escalation, and reporting.
Let’s Get Started
Trusted by leading organizations, RadarFirst enables teams to manage incidents with speed, consistency, and defensibility by standardizing how incidents are captured, assessed, and actioned.
