What to Do After an AI Incident (A Recovery Framework)

Jul 30, 2026

👋 Hi, I am Mark. I am a strategic futurist and innovation keynote speaker. I advise governments and enterprises on emerging technologies such as AI or the metaverse. My subscribers receive a free daily newsletter on cutting-edge technology.

Most AI incidents are not technology failures. The model functioned exactly as designed. The incident was a governance failure. A biased model shipped because nobody independently tested it. A deepfake embarrassed you because you had no process to vet AI-generated content before publication. A customer-facing recommendation system recommended something inappropriate because there was no human review. Here is the recovery framework: investigation, remediation, prevention, communication.

Investigation means understanding what happened and why. Did governance processes fail? Did someone bypass approval? Was the incident caused by drift in the training data? Write a detailed post-mortem. Organizations that investigate thoroughly prevent future incidents in the same category. Organizations that blame the model and move on will have the same incident three months later.

Remediation means fixing the immediate problem. Remove the biased system from production. Audit similar systems for the same failure mode. Retrain your team on the process that failed. Document the incident and the fix. This prevents recurrence of the specific incident that just happened.

Prevention means strengthening the governance processes that failed. If independent testing failed to catch the bias, why? Was the testing insufficient? Was the tester not qualified? Did pressure to ship prevent proper testing? Fix the process itself. Dr. Mark van Rijmenam finds that most organizations need to strengthen multiple processes, not just the one that failed.

Communication means being transparent with stakeholders about what happened. Tell affected customers. Tell your board. Explain what you did to fix it and prevent recurrence. Organizations that communicate transparently recover faster and maintain trust. Those that hide incidents face compounded damage when the truth emerges later.

An AI incident is not failure. It is normal operation in a learning organization. The way you respond determines whether the incident becomes a learning opportunity or a recurring crisis. Organizations pulling ahead are those that investigate thoroughly, strengthen processes systematically, and communicate transparently. They have fewer incidents and recover faster.

Build governance that prevents and recovers from incidents. Visit https://www.thedigitalspeaker.com/intelligence-age-scorecard/

About Dr. Mark van Rijmenam: Dr. Mark van Rijmenam is a world-leading strategic futurist and the creator of the Intelligence Age Scorecard, a diagnostic assessment built on the WAVE framework from his book Now What? How to Ride the Tsunami of Change. He helps Fortune 500 companies and governments navigate AI and emerging technologies across five continents.

This article was created with AI assistance and reflects the WAVE framework methodology. For the full research-backed analysis, take the Intelligence Age Scorecard.

Frequently asked questions

Why do most AI incidents happen even when the model works correctly?

Most AI incidents occur not because the technology fails but because governance fails. Examples include a biased model shipping because nobody independently tested it, a deepfake causing embarrassment because there was no vetting process for AI-generated content, or a recommendation system making an inappropriate suggestion due to lack of human review. The underlying process, not the model itself, is usually the point of failure.

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What are the four steps in the AI incident recovery framework?

The framework consists of investigation, remediation, prevention, and communication. Investigation means understanding what happened and why through a detailed post-mortem. Remediation means fixing the immediate problem, such as removing a faulty system and auditing similar ones. Prevention means strengthening the governance processes that failed. Communication means being transparent with stakeholders about what happened and what was done to fix it.

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Why is transparent communication important after an AI incident?

Organizations that communicate transparently with customers, boards, and other stakeholders about an incident and the steps taken to fix and prevent it recover faster and maintain trust. In contrast, organizations that hide incidents face compounded damage later when the truth eventually emerges, making transparency a key factor in how well a company recovers.

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Is it enough to just fix the specific process that failed?

No, most organizations need to strengthen multiple processes, not only the single one that failed. Prevention requires examining why safeguards like independent testing did not catch the problem, whether testing was insufficient, whether the tester was unqualified, or whether pressure to ship prevented proper testing, and then fixing the broader process rather than a narrow point failure.

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