2026-02-26 · 6 min
Resilience frameworks were built around infrastructure, applications and third parties. AI adoption adds model providers, inference capacity, prompt and policy configuration, and increasingly automated decisions embedded in operational processes.
The questions change accordingly. What happens if a model provider degrades or changes behavior? Which business processes now assume AI output is available and correct? Where would silent quality degradation appear before anyone notices?
Mapping AI dependencies into important business services — with tolerances, fallbacks and monitoring — is becoming a standard expectation in regulated sectors and a sensible discipline everywhere else.
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