Global AI Assurance · Layer 08
AI Systemic Risk Monitor
An AI failure is rarely local. The same model, the same framework and the same inference infrastructure sit beneath controls that were designed as if they were independent. The systemic view reads incidents and dependencies together, at four levels.
Within the institution
One provider, one framework or one tool server sitting beneath controls that were assumed to be independent.
Across the group
Subsidiaries choosing the same model for the same function, so a single withdrawal degrades every entity at once.
Across the market
Peers concentrating on the same inference infrastructure, which turns a vendor event into a sector event.
Across the supervisor
A regime that assumed diversity in a layer where none exists, which is where policy attention arrives next.
Concentration reads
Illustrative readings from a sample estate. Each one is a resilience question before it is a procurement one.
Critical workflows resting on a single model provider
73 per cent of the sample estateSingle-provider withdrawal is a service-continuity event, not a procurement one.
Critical agents on one tool-server dependency
41 agentsOne infrastructure fault removes a set of controls simultaneously.
Inference performed outside the home jurisdiction
28 per cent of governed callsResidency and compellability questions apply to more of the estate than the register shows.
Embedded models with no institutional owner
39 systemsObligations exist with nobody assigned to discharge them.
Where it lands
Concentration, drift, autonomy and incident history do not produce a separate AI score for the board. They move the institution's resilience position, through the AI and Agentic Resilience dimension.