| Abstract: |
This study examines the relationships among AI powered financial forecasting capability, data analytics maturity, and strategic decision quality in emerging market manufacturing firms, while assessing the moderating role of the AI governance framework. Grounded in Dynamic Capabilities Theory and Organizational Information Processing Theory, the study conceptualizes strategic decision quality as an outcome of predictive intelligence, mature analytical resources, and governance mechanisms that support the responsible use of AI generated forecasts. Employing a quantitative cross sectional design, data were collected from 385 respondents working in manufacturing enterprises across Vietnam through a five point Likert scale questionnaire. The data were analyzed using IBM SPSS version 26 for reliability assessment, exploratory factor analysis, and multiple linear regression, while Hayes’ PROCESS Macro Model 1 was applied to test the moderating effect. The findings revealed that AI powered financial forecasting capability (β = 0.580) and data analytics maturity (β = 0.601) both significantly enhanced strategic decision quality. Data analytics maturity produced a slightly stronger direct effect, emphasizing the importance of integrated data systems, analytical expertise, and evidence based organizational routines. Furthermore, the AI governance framework significantly strengthened the positive relationship between AI powered financial forecasting capability and strategic decision quality, as demonstrated by the positive interaction coefficient of 0.387. These results confirm that forecasting technology alone is insufficient and that reliable data capabilities, model validation, accountability, transparency, and human oversight are necessary to transform AI generated forecasts into informed, timely, comprehensive, and strategically aligned manufacturing decisions.
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