DEVELOPING AN INTEGRATED INDICATOR SYSTEM FOR ASSESSING ARTIFICIAL INTELLIGENCE-BASED MANAGEMENT EFFICIENCY IN ENTERPRISES
DOI:
https://doi.org/10.5281/zenodo.21639003Abstract
The rapid advancement of digital transformation has significantly increased the adoption of
artificial intelligence (AI) technologies in enterprise management. However, the lack of comprehensive
evaluation tools limits organizations’ ability to measure the effectiveness of AI-driven management systems. This
study aims to develop an integrated indicator system for assessing artificial intelligence-based management
efficiency in enterprises. The research examines the theoretical foundations of AI-enabled management,
identifies key performance dimensions, and proposes a framework of indicators that incorporates operational,
financial, technological, and strategic performance measures. Using a systematic and data-driven approach,
the study evaluates the role of AI technologies in improving decision-making quality, resource allocation,
process automation, and organizational competitiveness. The findings suggest that the proposed integrated
indicator system provides a reliable mechanism for measuring management efficiency and supports enterprises
in achieving sustainable growth and digital competitiveness. The study contributes to the existing literature
by offering a comprehensive framework for evaluating AI-based management effectiveness and facilitating
evidence-based managerial decision-making in the context of the digital economy
Keywords
artificial intelligence, management efficiency, AI-driven management, performance assessment, integrated indicator system, digital transformation, enterprise management, data-driven decision-making, business analytics, organizational performance, digital economy, key performance indicators (KPIs).References
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