Intelligent Management and Artificial Intelligence: Trends, Challenges, and Opportunities, Vol.1

Purpose: This study explores the relationship between employees' effectiveness (EE) and intelligent management (InMan), focusing on how modern technologies, particularly AI, influence workplace performance. It examines whether InMan can enhance EE, and identifies key factors shaping workplace design in this context. Need for the Study: The increasing integration of AI and InMan systems in organizations raises questions about their impact on employees' effectiveness. While existing research highlights AI's benefits in various business areas, direct studies addressing its influence on EE are missing. This study fills this gap by analyzing how InMan can support or challenge employees' ability to do their tasks efficiently while maintaining work comfort. Methodology: A critical literature review was conducted using the snowball method to select and analyze specialized academic sources. Additionally, international and national reports on EE and InMan were reviewed to identify relevant trends, challenges, and opportunities. The analysis was structured within a holistic framework, considering four employee activity spheres: physical, mental, emotional, and spiritual. Findings: The study finds that InMan has the potential to enhance EE by optimizing decision-making, resource allocation, and process efficiency. However, its effectiveness depends on integrating AI with human competencies to balance high productivity and employee well-being. Key EE-related factors must be considered in workplace design using InMan. Practical Implications: Organizations should adopt a holistic approach when implementing InMan, ensuring technological advancements align with employees' competencies and well-being. Practical recommendations include designing AI-driven workplaces, fostering productivity without compromising employee comfort. The findings highlight the importance of combining human expertise with AI to achieve sustainable organizational performance.