ARTIFICIAL INTELLIGENCE-DRIVEN DIGITAL TRANSFORMATION MODELS FOR ENHANCING ORGANIZATIONAL COMMUNICATION AND DECISION-MAKING EFFICIENCY

Abstract

This quantitative study investigated how artificial intelligence (AI) capability and digital transformation (DT) maturity influenced organizational communication quality and decision-making efficiency, with communication quality tested as a mediator and DT maturity as a moderator. The literature review synthesized evidence from 68 prior quantitative papers to refine construct definitions, measurement logic, and empirical pathways. A cross-sectional survey was conducted with 412 respondents from AI-adopting organizations across multiple sectors. Descriptive results indicated moderate-to-high levels of AI capability (M = 3.71, SD = 0.64) and DT maturity (M = 3.62, SD = 0.61). Communication quality recorded the highest mean (M = 3.84, SD = 0.59), followed by decision-making efficiency (M = 3.68, SD = 0.62), and distributional diagnostics supported parametric modeling. Measurement quality was strong (Cronbach’s α = .86–.93; CR = .88–.94; AVE = .60–.70), and CFA fit was acceptable (CFI = .95, TLI = .94, RMSEA = .05, SRMR = .04). Correlations among principal constructs were positive and significant, with no multicollinearity risk (VIFs < 2.10). Structural modeling confirmed all hypothesized direct effects: AI capability positively predicted communication quality (β = .58, p < .001) and decision-making efficiency (β = .33, p < .001), and communication quality positively predicted decision-making efficiency (β = .49, p < .001). Mediation testing showed a significant indirect effect of AI capability on decision efficiency via communication quality (β_indirect = .28, p < .001), indicating partial mediation. Moderation analysis demonstrated that DT maturity strengthened the AI-to-decision efficiency relationship (β_interaction = .14, p = .001). Overall, the findings supported an integrated mediated–moderated model explaining how AI-driven digital transformation enhances communication and decision efficiency in organizational settings.