The Impact of Artificial Intelligence on Enterprise Decision-Making Processes

Purpose: This paper examines how artificial intelligence (AI) enhances enterprise decision-making. It explores the influence of AI tools on decision speed, accuracy, and managerial effectiveness. The study also identifies key human and organizational factors affecting implementation success. Design/methodology/approach: A quantitative survey of 92 enterprises from multiple industries was conducted. Data were collected via a structured questionnaire and analyzed using descriptive and correlation methods. The approach enables identification of relationships between AI adoption, decision efficiency, and organizational barriers. Findings: Results show that 93% of companies use AI, mainly in customer service, data analysis, and decision support. AI improves efficiency and data-driven management but faces barriers such as employee resistance and high costs. Understanding AI mechanisms and managing change are critical competencies. Practical recommendations: Companies should strengthen change management, enhance AI literacy, and address employee adaptation issues. Effective leadership and transparent communication can improve acceptance and outcomes. Aligning AI tools with human decision-making will maximize business value. Originality/value: The paper offers one of the first quantitative assessments of AI’s role in enterprise decision-making. It highlights the synergy between algorithmic and human intelligence. The study contributes to understanding how AI reshapes management practices and organizational agility.