Is your resilience keeping pace with your AI?
What happens when AI agents supporting critical financial services become unavailable? Explore what financial-services leaders revealed about their readiness, response priorities, and recovery assumptions in iluminr’s Agent Down Microsimulation.

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The findings are eye opening.
Confidence in maintaining minimum service levels in a critical service, is low.
Only 16% of resilience professionals could demonstrate confidence in maintaining minimum service levels in critical service delivery after the loss of an agentic AI vendor.
People strategies are the contingency strategy of choice after AI fails.
In attempt to recover critical services, people largely turned to people, as the most reliable option of contingency. This elevates the criticality of workforce considerations in resilience alongside AI deployment.
Design for resilience, not recovery.
Maintaining a resilient delivery of critical services to customers, came down to decisions made at time of AI deployment, not at the time of the incident.
Where your peers agreed, and where they split.
“Who else would you engage for the response? Are these stakeholders formally documented?”
“What are the key impacts you would be raising with the team to assess and prioritize?”
“With the agent running at 300% throughput, will we breach impact thresholds faster?”
“Three key response strategies are emerging for consideration. Which of these would you suggest receives the highest priority?”
“How confident are you that minimum service levels can be maintained within impact thresholds?”
“What is the one action that you believe should be prioritized to increase confidence in maintaining minimum service levels for this scenario?”
The full readout, decision by decision.

The time to have an alternate solution was long before the crisis. The idea that you could contract with another firm quickly enough is wrong.
The same scenario, run with your own teams.



View the full report.
Explore the findings and what they mean for your organization’s AI resilience.
