Artificial Intelligence in Strategic Management: A Quantitative Validation of the Proposed Framework in Iraqi Public Universities
Keywords:
Artificial intelligence , Strategic management, PLS-SEMAbstract
Objective: This study aimed to empirically examine and validate the impact of artificial intelligence on strategic management, with particular emphasis on strategy formulation, strategy implementation, and strategic control.
Methods and Materials: The study adopted a quantitative, applied–developmental research design grounded in a descriptive–analytical approach. Data were collected using a structured questionnaire administered to senior managers and decision-makers within the target organizational context. The measurement instrument encompassed validated indicators of artificial intelligence capabilities and the three core dimensions of strategic management. Reliability and validity were assessed using Cronbach’s alpha, composite reliability, average variance extracted, exploratory factor analysis, and confirmatory factor analysis. Structural relationships among variables were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software, supported by inferential statistical analysis to evaluate correlations and causal paths among constructs.
Findings: The inferential results revealed a statistically significant and positive relationship between artificial intelligence and overall strategic management. Structural model analysis demonstrated that artificial intelligence exerted a significant direct effect on strategic management, explaining a substantial proportion of its variance. At the dimensional level, artificial intelligence showed significant positive effects on strategy formulation, strategy implementation, and strategic control, with the strongest effect observed on strategic control.
Conclusion: The findings confirm that artificial intelligence functions as a critical strategic enabler that strengthens the effectiveness of strategic management by enhancing analytical rigor in formulation, operational efficiency in implementation, and real-time oversight in control.
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