How do organisations maintain credible professional judgment when knowledge is co-produced by artificial intelligence? Professional credibility in AI-augmented settings depends not on individual competence alone but on the structural conditions under which content is evaluated and governed. This study tests whether epistemic governance infrastructure causally shapes professional credibility judgments. A registered 2×2×2 between-subjects factorial experiment (Study 1; N = 480) with UK-based professionals held content constant while varying provenance visibility, accountability clarity, and AI disclosure framing. Provenance visibility increased credibility by 23% (η²p = .21), accountability clarity increased challenge willingness by 40% (d = 0.93), and combined governance produced 53% higher credibility. The study reveals an AI Disclosure Paradox: disclosing AI involvement reduced credibility by 16% under weak governance but had no effect under strong governance, suggesting that mandatory disclosure without accompanying governance may harm professional credibility. Governance effects were 2.6 times stronger for high-stakes claims. Senior professionals responded primarily to provenance cues; junior professionals responded primarily to accountability signals, indicating that governance systems should be experience-differentiated. A supplementary experiment (N = 240) confirmed that contestability mechanisms increased challenge behaviour by 45% (d = 0.83; see Supplementary Materials). These findings establish epistemic governance as a structurally inducible organisational capability with implications for AI policy, leadership theory, and organisational training design.
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