Cognitive and Systems-Theoretic Implications of Using NLP-Based Intelligent Systems in Strategic IT Management and Decision-Making
Keywords:
Natural language processing; intelligent systems; strategic IT management; decision-making; cognitive support; systems theory; artificial intelligenceAbstract
This study aimed to examine the cognitive and systems-theoretic implications of using NLP-based intelligent systems in strategic IT management and decision-making among managers, experts, and specialists in Tehran. This applied descriptive-analytical study was conducted using a mixed qualitative–quantitative design. The statistical population included senior IT managers, strategic planning managers, digital transformation specialists, business intelligence experts, organizational decision-makers, and academic specialists in information systems and technology management in Tehran. Using purposive sampling, 186 participants were selected, including 24 participants in the qualitative interview phase and 162 participants in the quantitative survey phase. Data were collected through a semi-structured interview protocol and a researcher-made questionnaire developed based on cognitive decision-making, systems theory, strategic IT management, and NLP-based intelligent systems. The validity of the questionnaire was confirmed by experts, and its reliability was assessed using Cronbach’s alpha. Qualitative data were analyzed through thematic analysis, and quantitative data were analyzed using descriptive statistics, Pearson correlation coefficients, and multiple regression analysis. The inferential findings showed that strategic IT decision-making effectiveness had significant positive correlations with cognitive support, strategic alignment, system integration, interpretability, trust in intelligent systems, and decision quality, and a significant negative correlation with perceived risk of excessive reliance. The regression model was significant, F(6, 155) = 41.73, p < .001, and explained 61.8% of the variance in strategic IT decision-making effectiveness. Strategic alignment was the strongest positive predictor, followed by cognitive support, trust in intelligent systems, system integration, and interpretability. Perceived risk of excessive reliance was a significant negative predictor of strategic IT decision-making effectiveness. The results indicated that NLP-based intelligent systems can enhance strategic IT decision-making when they provide cognitive support, align with organizational strategy, integrate with organizational systems, and generate interpretable and trustworthy outputs. However, excessive reliance on automated recommendations may reduce the effectiveness of decision-making by weakening human judgment and critical reflection.
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Copyright (c) 2025 Abdullateef Haghighat (Author); Shady Oyarhossein (Corresponding author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
