Intelligent Decision Models for Business Management Applications

Witold Orłowski

Intelligent Decision Models for Business Management Applications

Author(s)	Prof. Dr. Witold Orłowski
Country	Poland
Abstract	Intelligent decision models have become increasingly important in modern business management as organizations generate large volumes of structured and unstructured data through digital operations, customer interactions, financial activities, and supply-chain processes. Artificial intelligence, machine learning, business intelligence, predictive analytics, optimization, and decision-support technologies provide organizations with advanced capabilities for transforming data into actionable managerial insights. This study examines intelligent decision models for business management applications, focusing on strategic planning, financial management, marketing, operations, human resource management, supply-chain coordination, risk management, and customer relationship management. A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis identifies data quality, analytical capability, technological infrastructure, managerial expertise, organizational readiness, explainability, and decision-maker trust as important factors influencing intelligent decision systems. Intelligent models can support forecasting, pattern recognition, scenario analysis, resource allocation, customer segmentation, risk identification, and operational optimization. However, implementation may involve challenges related to data privacy, cybersecurity, algorithmic bias, model complexity, technological costs, employee resistance, and inadequate analytical skills. The study emphasizes that intelligent decision models should complement managerial judgment rather than function independently of organizational objectives and contextual knowledge. Effective implementation requires reliable data, appropriate analytical methods, transparent decision processes, skilled personnel, technological infrastructure, and continuous model evaluation. The study provides a conceptual understanding of how intelligent decision models can strengthen business management by improving information processing, analytical capabilities, responsiveness, and evidence-based decision-making.
Keywords	Intelligent Decision Models, Business Management, Artificial Intelligence, Machine Learning, Decision Support Systems, Business Analytics, Predictive Analytics, Strategic Decision-Making, Business Intelligence, Data-Driven Management.
Field	Engineering
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-07-23

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Intelligent Decision Models for Business Management Applications

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