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The Agentic Blind Spot: Why AI Resilience Demands a System of Record

Why AI Resilience Demands a System of Record

Key Insights

1 in 5

companies has a mature model for governing autonomous AI agents.1

33%

of enterprise software applications will include agentic AI by 2028 – up from less than 1% in 2024.2

79%

of enterprises operate with significant blind spots – agents invoking tools, touching data, or triggering actions outside the scope of any monitoring or governance framework.3

37%

of CISOs cite securing AI agents as their top concern.4

Your AI stack has a recovery problem you probably can’t see yet. This Readiness Report gives CIOs and CISOs the framework to close the context gap, before an incident forces the question.

The Reality: Your AI Looks Recoverable. It May Not Be.

Most organizations managing enterprise AI have a model registry, an artifact store, a pipeline configuration manager. Each can confirm its own slice of the picture. None can confirm whether those pieces belong together, and whether they reflect the same operational state, the same moment, the same trustworthy configuration.

That’s the context gap. And it’s why recovery from an agentic AI compromise isn’t a data restoration problem. It’s a coherence problem.

The AI Resilience Readiness Report gives CIOs and CISOs the framework to close it.

What This Report Covers

Agentic AI has crossed a threshold. These systems don’t answer questions anymore. They execute workflows, coordinate with other agents, and act on production systems continuously and autonomously. That architectural shift changes the risk calculus entirely.

This report examines what readiness really means for the agentic enterprise: the four architectural layers most organizations haven’t designed for, the gaps they haven’t yet recognized, and the case for a unified system of record as the foundation for AI resilience.