Post-Deployment Accountability in AI Governance: A Cross-Regulatory Empirical Analysis of AI Incidents
Post-deployment accountability has become central to AI governance, yet little empirical evidence shows whether monitoring, incident reporting, and impact assessment obligations are visible when AI systems fail. This study analyzes real-world AI incidents from the AI Incident Database (2020-2026) and codes them against nine post-deployment provisions from the EU AI Act, the NIST AI Risk Management Framework, and the GDPR. The findings show substantial accountability gaps: 77.1% of incidents lack evidence of EU AI Act post-market monitoring, and 99.6% lack documented Data-Protection Impact Assessment evidence. Governance gaps are also systemic, with 9.8% of incidents simultaneously non-com...
| Authors | Ummara Mumtaz, Rabi Noor, Summaya Mumtaz |
|---|---|
| Primary category | cs.CY |
| Published | 10 April 2026 |
| Last updated at source | 10 August 2026 |
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