<![CDATA[This study develops a prospective conceptual framework for AI-Augmented Foresight Auditing (AIFA) to strengthen Supreme Audit Institution’s capabilities in addressing complex, cross-sectoral, and long-term governance risks. Although SAIs are increasingly expected to evolve from compliance-oriented oversight toward analytical insight and anticipatory foresight, operational frameworks supporting this transformation remain limited, particularly in developing economies. Using a hybrid qualitative design, this study combines a PRISMA-informed literature review with capability gap analysis of 17 audit reports from Indonesia’s 2025 National Thematic Food Security Audit, covering 13 ministries and central agencies, as well as 2 state-owned enterprises. The proposed framework is further assessed through normative alignment with INTOSAI and OECD guidance. The findings identify five Capability Gap Categories reflecting structural tensions between cross-sectoral analytical demands and current technological-methodological capacities. In response, the study proposes a three-layered AIFA framework: a methodological core with phase-differentiated AI roles across the Y-1, Y, Y+ cycle, an ESG-oriented analytical lens, and an institutional foundation with five enabling preconditions. AIFA provides an operational pathway for SAIs to enhance foresight capability within existing audit mandates and offers a transferable model for auditing strategic national programs characterized by systemic complexity and long-term policy risks.]]>
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