arXiv Paper Maps Global AI Governance Incident Reporting Timelines and Risk Framework Requirements

A December 2025 academic paper published on arXiv provides a structured synthesis of binding AI governance obligations across multiple jurisdictions, with particular focus on mandatory incident reporting timelines and risk management framework requirements. The paper identifies three distinct reporting deadlines that regulated entities must observe: cybersecurity breaches must be reported within 5 days, operational disruptions within 2 days, and harms to health or the environment within 15 days. It also maps requirements for risk management frameworks covering the full AI model lifecycle, including documented policies, procedures, and methodologies for identifying and mitigating systemic risks. Although the paper is an academic work rather than a binding regulatory instrument, it draws on existing frameworks to offer a consolidated reference for compliance professionals navigating obligations across safety, security, and operational resilience domains.

The paper reflects a broader challenge facing enterprise compliance teams: AI governance obligations are proliferating across jurisdictions at an uneven pace, and no single authoritative source consolidates the resulting patchwork of deadlines and procedural requirements. Regulators in the European Union, the United Kingdom, and other jurisdictions have each advanced frameworks that impose specific incident notification duties and risk governance standards, but the timelines and scope of those duties vary considerably. Research syntheses of this kind have gained practical relevance as compliance functions struggle to maintain current awareness of divergent requirements without dedicated cross-jurisdictional monitoring infrastructure.

Enterprise compliance teams should treat the incident reporting timelines identified in this paper as a prompt to audit their existing internal escalation protocols against each applicable jurisdiction. The 2-day window for operational disruptions in particular is narrow enough to require pre-established escalation chains and clearly assigned ownership before an incident occurs. Teams should verify whether their current frameworks distinguish between cybersecurity, operational, and harm-based incident categories, since conflating these under a single reporting track could result in missed deadlines in the more time-sensitive categories. Compliance professionals should also assess whether their AI risk management documentation covers the full model lifecycle as described, including identification and mitigation methodologies for systemic risks, and should flag any gaps for remediation ahead of regulatory examinations or audits.