Sequential adoption of audit software and AI analytics: Evidence from Kuwait and the GCC

The evolution of audit technology is changing the profession, but studies conducted in Kuwait and the GCC have remained ad hoc, tending to treat traditional audit software and AI analytics as two separate entities rather than as a unified technological trajectory. This research addresses that gap by analysing the interaction of these tools as a sequential process of improving audit quality. A mixed-methods design was employed, combining a structured survey of 219 auditors and finance executives with semi-structured interviews. Analysis proceeded through hierarchical descriptive tabulation, factor validation testing, structural equation modelling (PLS-SEM), bootstrapped mediation and moderation testing, incremental value analysis, and multi-group comparison. The findings demonstrate that audit software and AI analytics are complementary rather than competing technologies: software improves process efficiency and compliance foundations, while AI analytics extends these foundations through predictive risk capabilities and fraud detection maturity. Auditor expertise, targeted training, and organisational readiness significantly moderate both pathways. Adoption of both tools in combination produced the strongest gains in audit quality, and multi-group analysis revealed contextual differences across GCC firms. This paper makes three contributions. First, it provides empirical validation of a Sequential Adoption Model, demonstrating that audit software and AI analytics are complementary and sequentially ordered phases of a single audit technology trajectory. Second, it identifies auditor expertise, targeted training, and organisational readiness as key moderators of both pathways, and documents significant contextual differences between Kuwaiti and broader GCC firms. Third, it establishes a planning-phase boundary condition: AQF-based evidence from the GCC indicates that the planning dimension (AQF 2) remains the least effectively technology-supported phase even after sequential adoption, pointing to a phase-specific gap whose mechanisms are examined in complementary conceptual work.