How Audit Readiness Capability Reshapes Organisational Knowledge Credibility: A Theoretical Model Based on Full-Volume Lossless Evidence Graphs

Against the backdrop of widespread generative AI adoption, proliferating synthetic content, and intensified data contamination and cross-platform dissemination, organizations' credibility challenges are shifting from “whether explanations are persuasive” to “whether evidence chains are verifiable, traceable, and reconstructable.” While transparency, accountability, and organizational learning research underscore the importance of disclosure, oversight, and error correction, they lack a mechanistic explanation for “evidence chain restorability” as a capability that can be systematically constructed and transformed into a credibility advantage. This paper introduces the novel construct of “audit readiness capability,” defined as an organization's capacity to sustain the traceability, reconstructability, and auditability of its evidence chain through institutionalized mechanisms for evidence capture, linkage, validation, and review during knowledge production and dispute resolution. We further employ a comprehensive, lossless evidence graph as both a prototypical implementation form and theoretical reference point to constrain the construct's boundaries and provide testable operational clues. We propose a mechanism model elucidating how audit readiness enhances the stability, transferability, and dispute-resistance of organizational knowledge credibility by promoting interpretive convergence, reducing dispute resolution costs, and increasing accountability clarity. Concurrently, we identify boundary conditions including privacy and security constraints, organizational politics, task contentiousness, and regulatory intensity, alongside twelve testable propositions and a research agenda for advancement. This paper's theoretical contributions adhere to the core review logic of conceptual papers: novel constructs, mechanism explanations, boundary conditions, and a proposition system .