The persistent gap between SME adoption of AI-enabled tax compliance tools and large-organization adoption rates represents a theoretically underexplained phenomenon in the Industry 4.0 regulatory environment. This study examines the relationship between owner-manager psychological triggers — Perceived Regulatory Risk (PRR), Digital Self-Efficacy (DSE), and Time Pressure (TP) — and AI adoption in tax compliance, testing a mediation framework in which dual-process cognitive states mediate trigger effects on adoption. A cross-sectional survey of N = 423 SME owner-managers was analyzed using IBM AMOS 31.0 as the primary confirmatory method, supplemented by exploratory Hayes (2022) PROCESS macro version 4.2 analyses conducted after, and motivated by, the primary structural findings. The partially mediated model was confirmed as the preferred specification (Δχ²(3) = 141.084, p < .001; RMSEA = .044; CFI = .964; PCLOSE = .913; R² = .490). Five of six trigger-to-state a paths were significant, confirming dual-process activation. The primary empirical discovery was the reversal of the DSE effect on AI adoption — β = −.736, p < .001 — opposite to the hypothesized facilitation direction, producing adoption resistance rather than facilitation, and completely invariant across both trait dimensions. The b paths from decision states to adoption were non-significant at the latent level due to contextual suppression by the dominant DSE effect, confirmed through PROCESS diagnostic analyses demonstrating significant b paths in trigger-isolated models. PROCESS further identified a significant PRR × Adaptive Traits crossover interaction and an independent Adaptive Traits facilitation benefit. The findings generate a three-mechanism taxonomy of AI adoption barriers — identity-protective, resource-based avoidance, and regulatory problem-solving — each psychologically distinct and each requiring a different intervention strategy. Six post-hoc theoretical explanations, documented in Appendix A, Section A.3, are applied for the first time to this population. Eight theoretical contributions advance dual-process technology adoption theory, Identity-Based Motivation theory, MDMM application, upper echelons theory, and the methodology of contextual suppression diagnosis in SEM research.