Risk assessments for advanced AI systems require evaluating both the models themselves and their deployment contexts. We introduce the Societal Capacity Assessment Framework (SCAF), an indicators-based approach that measures a society's vulnerability, resilience capital, and transformation potential in the face of AI-related risks. SCAF adapts established resilience analysis methodologies to the AI context, enabling organisations to contextualise risk thresholds and deployment strategies based on societal readiness. It can also support stakeholders in identifying opportunities to strengthen societal adaptation to emerging AI capabilities. By bridging disparate literatures and the "context gap" in AI evaluation, SCAF complements model evaluations to support more holistic risk assessment and governance as advanced AI systems proliferate globally.