AI Incident Response: Updating Your Security Plan for Generative AI

Traditional incident response plans were not built for today’s AI risks. Companies now need to consider incidents involving unauthorized AI tools, confidential data entered into public AI systems, AI-generated misinformation, prompt injection, AI vendor breaches, and misuse of AI in high-impact workflows.

AI incident response should not be isolated from the broader security program. It should be integrated into existing incident response policy, privacy escalation, vendor risk management, and employee reporting procedures.

What Is an AI Security Incident?

An AI security incident is an event involving AI tools, systems, prompts, outputs, vendors, or workflows that may create security, privacy, legal, operational, or reputational risk.

Examples include an employee entering customer data into an unauthorized AI tool, source code pasted into a public chatbot, an AI vendor breach, prompt injection affecting an automated workflow, or AI-generated content being used in a harmful business decision.

Why Traditional Plans May Be Incomplete

Most incident response plans focus on phishing, malware, ransomware, account compromise, system outages, and data breaches. Those risks still matter, but AI introduces new scenarios.

For example, if confidential information is entered into an unapproved AI tool, the company needs to determine whether data was retained, who had access, whether the vendor used it for training, whether personal data was involved, and whether notification obligations apply.

Common AI Incident Scenarios

Common scenarios include confidential data entered into an unapproved AI platform, personal data processed by an unauthorized tool, source code submitted to a public chatbot, AI vendor data exposure, prompt injection, unauthorized AI browser extensions, AI-generated misinformation used in customer communication, and unapproved AI use in HR or legal workflows.

What to Add to the Incident Response Policy

Companies should add AI-related incident definitions, reporting requirements, severity criteria, investigation steps, vendor escalation, privacy review, evidence collection, and post-incident policy updates.

The policy should explain that employees must report AI-related mistakes or concerns immediately, especially where confidential information, personal data, customer data, or source code may have been involved.

Who Should Be Involved?

AI incident response may require IT, security, privacy, legal, compliance, HR, communications, vendor management, and the business owner of the affected process.

This cross-functional approach matters because AI incidents often involve more than technical containment. They may involve privacy assessment, contractual review, customer communication, employee retraining, and vendor escalation.

Post-Incident Improvement

After an AI incident, companies should update policies, training, approved tools, vendor review requirements, and technical controls. The incident should be used to improve governance, not just close a ticket.

How PolicyOS Helps

PolicyOS helps organizations update incident response policies, document AI incident requirements, assign owners, manage review cycles, and track employee acknowledgement.

Conclusion

AI changes the risk landscape. Companies should update incident response policies and plans before an AI-related incident occurs.

Use PolicyOS to keep incident response policies current as AI risks evolve.