Abstract
The study uses a robust descriptive cross-sectional design to explore the role of AI in management decision-making among corporate professionals in Bengaluru. This design, incorporating qualitative and quantitative methods, ensures a comprehensive understanding of the topic, providing a solid foundation for the study's findings. A sample of 300 corporate professionals was selected using stratified random sampling to ensure diversity across industries and managerial levels. Data collection included semi-structured interviews and structured questionnaires, providing a rich and varied dataset. Multiple regression analysis revealed that AI adoption significantly improves decision-making efficiency, with factors like organisational support and employee training playing key roles. ANOVA results indicated a significant improvement in strategic and operational decision-making, particularly among professionals with more AI experience. The Chi-square test demonstrated a strong association between AI experience and transparency concerns, with lower-experience professionals reporting more issues. Correlation analysis revealed key relationships between AI experience, ethical considerations, trust in AI, and perceived limitations. In conclusion, based on a comprehensive and robust research design, the study's findings have practical implications for corporate professionals in Bengaluru. The significant improvement in decision-making efficiency with AI adoption is a cause for optimism about the potential of AI. As AI experience increases, trust and transparency issues diminish. The study underscores the need for organisations to focus on training, improving transparency, and balancing human judgment with AI tools to optimise decision-making processes.
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